Indian Patents
Title of Invention

A NETWORK COMPONENT, A COMPUTER NETWORK SYSTEM AND A METHOD FOR TRANSFORMING ACCOUNTING RELATED DATA SETS INTO MULTI-DIMENSIONAL DATA SETS
Abstract The invention relates to aspects in context with updating a data base that is jointly used by two or more different processing mechanisms on the basis of multi-dimensional data sets. A network component performing this task includes a master data base for storing master data including static data and a multi-dimensional generic data template having predefined data fields relating to elementary information determined by the data input requirements of the different processing mechanisms. An interface is provided for receiving accounting-related data sets from a plurality of individual sub-systems. Processing resources having access to the master data base generate for each accounting-related data set one or more associated multi-dimensional data sets by deriving elementary information included in the accounting-related data set and in static data associated with the accounting-related data set and by writing the derived elementary information in corresponding data fields of the data template. On the basis of the elementary information contained in the one or more multi-dimensional data sets an elementary data base that is jointly used by the different processing mechanisms to generate report data sets is updated.
Full Text DESCRIPTION
Technical Field
The present invention relates to managing accounting-related data in a computer network.
More specifically, the invention relates to automatically generating processing-optimized
and redundancy-free data for multiple applications.
Background of the Invention
The volume of accounting-related data that is permanently generated and that has to be
regularly managed and evaluated necessitates even in small-size businesses the implemen-
tation of computer-assisted mechanisms. In larger businesses accounting-related data are
sometimes generated by dozens of individual software applications often running on dif-
ferent technical platforms.
Especially in larger businesses a single data processing (e.g. reporting) mechanism is not
sufficient for efficiently controlling all operations. Hence, different data processing
mechanism delivering different output data including required operational information are
commonly deployed. Although the data processing mechanisms differ with respect to the
generated information, they are usually based on the same or at least similar accounting-
related data received from the individual software applications.
This situation is schematically depicted in Fig. 1. In the scenario of Fig. 1 four software
applications are running in parallel in different computer networks 10,12,14 and 16. Each
computer network 10,12,14,16 comprises a central component (like an application server
or a mainframe computer) and several terminal devices like clients, presentation servers,
automatic teller machines (ATMs), etc. attached to the central component. Data received
from the terminal devices is converted by the applications running on the central compo-
nents into accounting-related data.
As illustrated for computer networks 10,12 and 14 (applications 1, 2 and 3), the account-
ing-related data generated by the individual applications are transferred to central applica-
tion servers 18,20 for being processed further. More specifically, each of the central
application servers 18,20 applies a particular processing mechanism to the accounting-
related data that are received from the computer networks 10,12,14 and produces output
data that may be used for various operational purposes. Processing instructions data to be
used by the different processing mechanisms applied by the central application servers
18,20 are stored in local data bases REF 1 and REF 2 belonging to the central application
servers 18,20, respectively.
The multiplicity of central application servers 18,20 and associated input data streams is
necessitated by the fact that different processing mechanisms (applications) are in charge
of generating the output data. These different processing mechanisms, although processing
very similar accounting-related data, usually require different input data formats or process
different informational contents included in the accounting-related data. As examples for
processing mechanisms that are performed in parallel and on the basis of similar account-
ing-related data the mechanisms of management accounting and financial accounting can
be mentioned. The first central application server 18 may thus for example be in charge of
management accounting applying accounting principles REF 1 to generate data set 1 (e.g.
in a management reporting context) and the second central application server 20 may be in
charge of financial accounting applying accounting principles REF 2 to generate data set 2
(e.g. for the computerized preparation of balance sheets and associated reporting).
As illustrated for computer network 16 (application 4), the accounting-related data may be
pre-processed locally within a particular network according to a processing mechanism
using instruction data stored in a local network data base REF 3 to generate a pre-
processed data set 3. In some cases the accounting-related data or the pre-processed data
set 3 generated within one computer network 16 may additionally (or alternatively) be
transferred to another computer network 14 for further data processing before being trans-
ferred to one or both of central applications servers 18,20.
From Fig. 1 it becomes apparent that the complexity of the data processing system as a
whole is high. Thus, the maintenance of the system is difficult. Moreover, lack of integra-
tion and lack of automation often requires manual interactions, e.g. duplicate data entries,
as well as data conversions and data transfer processes. Also, the data throughput is slow,
especially if sequential data processing as illustrated for computer networks 14 and 16 is
performed. The low data throughput implies that the closing process for reporting, e.g. for
providing specific accumulated information, takes a very long time. Currently, detailed
accounting reports can very often not be provided until 15 days and more after a specified
date like the end of the month. In this context it has to be kept in mind that in larger busi-
nesses hundreds of millions of individual data sets have to be evaluated every month.
Accounting-related data generated by the individual computer networks 10,12,14,16 as
well as output data generated by the central application servers 18,20 have to be stored
simultaneously in two or more memory locations (e.g. locally at the sites of each of the
two central application servers 18,20), leading to a high informational redundancy. This
adds to the hardware requirements and in particular to the storage costs.
A further problem associated with redundant data storage is data authentication. If the
same information is simultaneously stored in two or more memory locations, the provision
of authenticated data for e.g. official reporting purposes becomes a difficult task and re-
quires constant, and often manual, data reconciliation as indicated in Fig. 1 with an arrow
between central application servers 18,20.
One solution to the drawbacks of the scenario depicted in Fig. 1 might be to somehow
integrate the functions of the two central application servers 18,20 and the central compo-
nent of the computer network 16. However, in view of the fact that the different processing
mechanisms usually operate on different data and different data formats, such an approach
would still involve redundant data storage, and thus complex data authentication mecha-
nisms.
There is a need for a network component, a network system, a method, a computer pro-
gram product and a data structure which, in the context outlined above, allow on the one
hand for a redundancy-free provision of data for different processing requirements and
which on the other hand facilitate data authentication. Furthermore, there is a desire to
accelerate the provision of accumulated data when large amounts of data have to be han-
dled.
Summary of the Invention
This need is satisfied according to the invention by a network component for transforming
accounting-related data sets into multi-dimensional data sets which are used to update a
data base that is jointly used by different processing mechanisms like financial and man-
agement accounting mechanisms to provide report data sets. The network component in-
cludes at least one a master data base for storing master data including static data and a
multi-dimensional generic data template. The data template specifies a plurality of pre-
defined data fields (or contents) relating to elementary information that is to be processed
by the different processing mechanisms. The network component further comprises at least
one interface for receiving the accounting-related data sets from a plurality of individual
sub-systems. Furthermore, the network component comprises processing resources with
access to the master data base. The processing resources are programmable to generate
for each accounting-related data set one or more multi-dimensional data sets by deriving
the elementary information included in the accounting-related data set and in associated
static data and by writing the derived elementary information in the appropriate data fields
specified by the data template. The elementary information included in the multi-
dimensional data sets is used to update an elementary data base that is jointly used by the
different processing mechanisms.
According to the invention, all the information required by the different processing
mechanisms can be generated along a single processing chain. Thus, an output-oriented
topology is realized that strongly reduces redundancies and makes reconciliation efforts
obsolete. The information derived from a specific accounting-related data set (primary data
set) and from associated static data is included on an elementary level in one or more
multi-dimensional data sets (secondary data sets) that form the basis for updating the ele-
mentary data base. In contrast to the variable accounting-related data sets which are con-
tinuously generated for individual transactions, static data are fixed or change only slowly.
The static data may include information that is required for generating the multi-
dimensional data set but that is not or not explicitly included in the accounting-related data
set. Thus, the provision of static data in the master data base helps to reduce network traf-
fic, i.e. the amount of data that has to be transferred from the sub-systems to the network
component because certain generic data common to several accounting-related data sets
need not to be transferred with each accounting-related data set to the network component.
It usually suffices to simply include a short reference to specific static data into the ac-
counting-related data set transferred to the network component and the network compo-
nent itself may then "complete" (enrich) the received accounting-relating data set by the
associated static data for the purpose of deriving the elementary information required for
generating the one or more multi-dimensional data sets.
The static (and reference) data included in the one or more master data bases may be iden-
tical with the static (and reference) data utilized by source applications generating the ac-
counting-related data sets. If required, these source applications may have access to the
one or more master data bases. The latter approach helps to further reduce data redundan-
cies.
The transformation of the accounting-related data sets into multi-dimensional data sets
may be based on technical identifiers that have a 1:1 association with identifiers provided
by the source application. In the case of a plurality of n source application. In the case of a
plurality of n source applications, a 1 :n association would exist. The tables underlying
these associations may thus be considered as lexical ontologies.
Due to the highly granular nature of the multi-dimensional data sets and their complete-
ness as regards the informational content required by the different processing mechanisms
they may form the basis for updating the elementary data base that is jointly used by the
different processing mechanisms. Furthermore, redundant data storage is avoided because
the elementary data base serves as common data base for all processing mechanisms. Ad-
ditionally, data authentication ambiguities do no longer occur since the elementary data
base can be regarded as the single source for providing authenticated data. Thus, recon-
ciliation processes as illustrated between the application servers 18,20 in Fig. 1 can be
dispensed with.
The conventional differentiation between balancing data warehousing on the one hand and
data warehousing for reporting purposes on the other hand becomes obsolete by the inte-
grated solution provided by the elementary data base. The elementary data base thus con-
stitutes an integrated source for different types of reports including search and drill down
mechanisms on e.g. balance sheet data (daily, weekly, etc.), profit center data, etc.
The elementary data base may include elementary data sets that at least partially corre-
spond to the data fields of the data template. The elementary data sets may be created or
changed by the processing resources in context with updating the elementary data base
upon generation of new multi-dimensional data sets. The processing resources may thus be
programmed to update the elementary data base by accumulating elementary information
included for example in one or more particular data fields of the multi-dimensional data
sets onto elementary data sets that are already existing in the elementary data base or that
have to be newly created. Updating of the elementary data base may be performed batch-
wise or in a continuous manner. According to a preferred continuous updating approach,
the elementary data base is updated asynchronously as soon as one or more further multi-
dimensional data sets have been generated.
In order to control the updating process, the processing resources may be programmed to
assign one or more control attributes to the multi-dimensional data sets. Control attribute
types which are to be assigned to a multi-dimensional data set may be specified by the
generic data template and may be inserted or already be included in one or more data
fields of the multi-dimensional data sets.
Based on the one or more control attributes assigned to a particular multi-dimensional data
set, the elementary information included in this multi-dimensional data set can be accumu-
lated onto elementary data sets related to the control attributes. In other words, the control
attributes may indicate the particular elementary data set onto which the elementary infor-
mation included in a multi-dimensional data set is to be accumulated, e.g. appended or
added.
The particular elementary data set onto which particular elementary information is to be
accumulated may be derived based on two or more control attributes. The individual con-
trol attributes may be independent from each other and may thus span a multi-dimensional
space. A single control attribute may often not be sufficient to unambiguously identify the
particular elementary data set onto which the elementary information is to be accumulated.
Also, the control attributes associated with the received accounting-related data sets may
be changing so that the particular elementary data set may be identified only on the basis
of the available control attributes received via the accounting-related data set.
Thus the plurality of control attributes received via an accounting-related data set may be
required to identify the relevant storage portion (elementary data set) onto which the ele-
mentary information included in a multi-dimensional data set is to be accumulated.
The control attributes may relate to various aspects. For example, a control attribute in the
form of an identification code identifying e.g. a customer, a customer position, an organ-
izational entity serving the customer or the like may be assigned. Thus, the elementary
information pertaining to this assignment can be accumulated onto the particular elemen-
tary data set related to this assignment.
Control attributes of the types specified by the generic data template or different therefrom
may also be included in the elementary data sets to assist the tasks of the individual proc-
essing mechanisms generating the reporting data sets. The control attributes associated
with the elementary data sets may for example contain structural information required to
produce report data sets in the form of balance sheets or management accounting reports.
The elementary data sets may be evaluated individually for each of the multiple dimen-
sions reflected therein. Accordingly, report data sets may be generated for an individual
dimension (attribute) of the elementary data sets.
The control attributes associated with the elementary data sets may be included in or ap-
pended to the elementary data sets and may at least in part be identical with or correspond
to control attributes assigned to the multi-dimensional data sets.
In order to enable a tracking of the information flow, one or more of the elementary data
sets stored in the elementary data base may be linked with at least one of related multi-
dimensional data sets and related accounting-related data sets. In the context of the present
invention a related multi-dimensional data set or accounting-related data set is defined as a
data set that includes or is the source of information accumulated onto the elementary data
set. Linking an elementary data set with a related data set may be performed in various
ways like by appending to the elementary data set information about the memory location
of the related data sets or vice-versa.
To cope with authorization problems, the elementary data base may be configured as the
only source for providing information for generating the report data sets. This may imply
that the different processing mechanisms generate the report data sets solely on the basis of
the information included in the elementary data base. To enhance data integrity, the ele-
mentary data base may be configured as a read-only data base with respect to all accesses
different from updating.
Besides the elementary data base and the master data base the network component may
further comprise an entry data base that serves for storing the accounting-related sets re-
ceived via the interface from the individual sub-systems. The accounting related data sets
received from the sub-systems may all have the same format or may have individual for-
mats characteristic of the individual applications that generated the accounting-related data
sets. Especially when the accounting-related data sets are received in different formats, a
data sourcing component may be provided to format the received accounting-related data
sets and to write the formatted accounting-related data sets into the entry data base. Such
an approach allows to provide the individual accounting-relating data sets in a pre-defined
format to the processing resources generating the multi-dimensional data sets.
The data sourcing component may alternatively or additionally be configured to check the
accounting-related data sets received from the sub-systems to determine data inconsisten-
cies. Mechanisms may be provided to handle exceptions in the case of inconsistencies of
one or more of the accounting-related data sets. In the case of inconsistencies, the data
sourcing component may for example re-format a received accounting-related data set or
notify an individual sub-system that a received accounting-related data set is not accepted,
thus triggering a re-transmission of the accounting-related data set or of a complete file
containing the accounting-related data set.
Additionally, the network component may comprise an item data base for storing the
multi-dimensional data sets that were generated by the first processor from the accounting-
related data sets. Thus, the item data base may be regarded as an intermediate data base
arranged between the entry data base that stores the accounting-related data sets and the
elementary data base that stores the elementary data sets. The provision of three individual
data bases (that may physically be located on a single hardware component) is advanta-
geous because it allows at any point in time to trace back the information as it proceeded
in different formats from the individual sub-systems to the various processing mecha-
nisms. In particular, it allows to determine the origin of data inconsistencies that in many
cases can only be detected at the very end of the data stream, i.e. when applying individual
processing mechanisms to the data stored in the elementary data base. In order to further
facilitate the tracking of information, the multi-dimensional data sets stored in the item
data base may be linked with at least one of the associated accounting-related data sets
stored in the entry data base and one or more of the associated elementary data sets stored
in the elementary data base.
As has been mentioned above, the elementary data base, as well as the master data base or
any other system data base or combination thereof, may jointly be used by the different
processing mechanisms. The processing mechanisms may be performed by dedicated or
shared processing resources. The processing mechanisms are configured to generate report
data sets based on the elementary data sets and, optionally, based on the multi-dimensional
data sets. In general, report generation relies on report structure information (report defini-
tion data), that may be contained in the master data base, and on appropriate data extracts
from the elementary data base or, optionally, any other system data base or combination
thereof. Thus, the one or more processing mechanisms may be configured to extract se-
lected elementary data sets stored in the elementary data base for reporting purposes. The
report definition data may specify how information included in the extracted elementary
data sets has to be accumulated or evaluated.
One or more processing mechanisms may also be configured to extract selected elemen-
tary data sets stored in the elementary data base for evaluation purposes. Based on that,
additional processing mechanisms might be in place to provide evaluation results by ap-
plying pre-defined evaluation criteria and to generate at least one of multi-dimensional
data sets and accounting-related data sets, in particular if the actual values of elementary
data sets differ from values originally extracted. The resulting multi-dimensional data sets
may be used by a subsequent processing mechanism to update the elementary data sets.
The processing mechanisms may be based on a set of processing instruction data, e.g. sets
of values and rules which have to be applied on the data to be processed to generate the
multi-dimensional data sets, the elementary data sets or the multi-dimensional data sets.
The processing instruction data may be kept outside of the program code of a particular
processing mechanism (soft coded approach) or could be part of the program code (hard
coded approach). If a soft coded approach is implemented, the processing instruction data
may be included as reference data in the static data stored in the master data base. This has
the advantage that changes to e.g. table entries on reference data are independent from
program code changes.
The processing resources may be programmed to execute at least one processing mecha-
nism to transform an accounting-related data set into one or more multi-dimensional data
sets using static data associated with the accounting-related data set. When performing the
transformation the processing resources derive the elementary information included in the
accounting-related data set and in any static data associated with the accounting-related
data set and write the elementary information thus derived in the corresponding data fields
specified by the data template, thus assembling the one or more multi-dimensional data
sets. The processing mechanism may indicate how the data template is to be applied. The
processing mechanism may for example derive the control attributes to be assigned to a
particular multi-dimensional data set, determine the particular static data associated with
the accounting-related data set, etc. Processing instruction data specific for the processing
mechanisms applied to transform the accounting-related data sets into the multi-
dimensional data sets may be stored as static data in the master data base.
Depending on the requirements, different types of accounting-related data sets may be
defined. An individual type of accounting-related data set may for example be associated
with each individual sub-system or application that generates accounting-related data sets.
For each type of accounting-related data set an associated transformation for generating the
multi-dimensional data sets may be provided. Moreover, the processing resources may be
programmed to identify for a specific type of accounting-related data set the particular
transformation (i.e. processing mechanism and associated processing instruction data)
associated therewith. Additionally or alternatively, the processing resources may be pro-
grammed to identify for a specific accounting-related data set the associated static data. To
that end the accounting-related data sets may be provided with a reference to associated
static data as mentioned above.
The network component may have a first interface to receive the accounting-related data
sets from the individual sub-systems and an additional second interface that enables an
access to the master data base. Such an access may be performed to update the master data
base. Updating the master data base may relate to at least one of the static data, (including
reference data) and the processing instruction data. The one or more interfaces of the net-
work component may be part of or in communication with the data sourcing component.
The network component may be implemented as a system including only a single tier or as
a multi-tiered system. The network component may for example be configured as a three-
tiered system including at least one presentation server, at least one application server and
at least one data base server. The one or more presentation servers may be configured to
present the individual data sets or information derived therefrom, whereas the at least one
application server may include processing resources mentioned above. The one or more
data base servers may comprise the individual data bases. Alternatively, the network com-
ponent may be configured as a two-tiered system including at least one presentation server
and at least one combined application and data base server.
According to a further aspect of the invention, a computer network system is provided that
comprises the network component (which in turn may comprise individual sub-
components) described above as well as a plurality of sub-systems attached to the one or
more interfaces of the network component. On each sub-system one or more individual
applications for generating the accounting-related data sets may be running.
The individual applications preferably provide standardized accounting-related data sets.
The provision of standardized accounting-related data sets in a pre-defined format is espe-
cially advantageous. In order to ensure that the network component can deduce from
the received accounting-related data sets information on an elementary level, the individ-
ual applications may be programmed not to perform any pre-processing with respect to the
particular processing mechanisms that are to be applied by the network component.
According to a still further aspect of the invention a method of transforming accounting-
related data sets into multi-dimensional data sets is provided. The method includes
providing master data including static data and a multi-dimensional generic data template
which has pre-defined data fields relating to elementary information determined by the
data input requirements of the different processing mechanisms. The accounting-related
data sets are received from a plurality of individual sub-systems. For each accounting-
related data set one or more associated multi-dimensional data sets are generated by
deriving elementary information included in the accounting-relating data set and in static
data associated with the accounting-related data set and by writing the derived elementary
information in corresponding data fields specified by the data template. Using the multi-
dimensional data sets, an elementary data base is updated on the basis of the elementary
information contained therein. The elementary data base is jointly used by the different
processing mechanisms.
The invention can be implemented as a hardware solution, as a software solution or as a
combination thereof. As regards a software solution, the invention relates to a computer
program product comprising program code portions for performing the above steps when
the computer program product is run on one or more components of a computer network.
The computer program product may be stored on a computer readable recording medium.
According to a further aspect of the invention, a multi-dimensional data structure
generated from a plurality of accounting related data sets using the steps outlined above
and jointly used by a plurality of processing mechanisms differing with respect to data
input requirements is provided. The data structure includes a plurality of elementary data
sets that reflect the data fields of a multi-dimensional generic data template. The data
fields reflected by the elementary data sets relate to elementary information determined
by the data input requirements of the different processing mechanisms. The elementary
data sets contain accumulated elementary information derived from multi-dimensional
data sets generated from the accounting-related data sets using the data template.
Brief Description of the Accompanying Drawings
Further details, embodiments, modifications and enhancements of the present invention
may be obtained from consideration of the following description of various illustrative
embodiments of the invention in conjunction with the drawings, in which:
Fig. 1 is a schematic diagram illustrating a system for generating and processing ac-
counting-related data according to the prior art;
Fig. 2 is a schematic diagram illustrating a system for generating and processing account-
ing-related data according to an embodiment of the present invention;
Fig. 3 is a schematic diagram illustrating an exemplary three-tiered server architecture
deployed for the embodiment of Fig. 2;
Fig. 4 is a schematic diagram illustrating an exemplary two-tiered server architecture de-
ployed for the embodiment of Fig. 2;
Fig. 5 is a schematic diagram illustrating the co-operation of the individual parts of the
architectures shown in Figs. 3 and 4 according to the present invention;
Fig. 6 is a flow chart illustrating the generation of multi-dimensional data sets;
Fig. 7 is an empty table illustrating a generic multi-dimensional data template used ac-
cording to the present invention;
Fig. 8 illustrates the format of two multi-dimensional data sets that have been generated
from a single accounting-related data set resulting from an ATM transac-
tion; and
Fig. 9 illustrates the exemplary format of elementary data sets onto which the multi-
dimensional data sets of Fig. 8 are accumulated.
Description of Preferred Embodiments
Fig. 2 illustrates a simplified block diagram of a computer network system according to the
present invention. The network system comprises four sub-systems 10,12,14,16 as de-
scribed in context with Fig. 1. Where appropriate, the same reference numbers will be used
throughout this detailed description and the drawings to refer to the same or like parts.
The network system depicted in Fig. 2 comprises a single central network component 30
including a master data base 32 and an elementary data base 34. The network component
30 is configured as a network node, receiving different types of accounting-related data
sets from the sub-systems 10,12,14,16 and processing the received accounting-related
data sets using different processing mechanisms to generate various kinds of report data
sets (data set 1, data set 2, ....).
More specifically, the network component 30 accumulates elementary information in-
cluded in or derived from the accounting-related data sets received from the sub-systems
10,12,14,16 onto elementary data sets stored in the elementary data base 34. The proc-
essing instruction data used by the processing mechanisms when deriving the elementary
information from the accounting-related data sets and for accumulating the derived ele-
mentary information onto the elementary data sets are retrieved from the master data base
32. Also retrieved from the master data base 32 are the processing instructions characteris-
tic of the individual processing mechanism for generating the report data sets.
Whereas in the conventional network system depicted in Fig. 1 the report data sets are
generated in a distributed manner by a plurality of network components having local data
bases, in the network system according to the invention shown in Fig. 2 only the central
network component 30 is generating the various report data sets from information that is
stored on an elementary level in the elementary data base 34. Hence, redundant data stor-
age is avoided and data reconciliation becomes obsolete. This not only reduces storage
requirements and manual interactions but also reduces the time required for evaluation
processes like reporting mechanisms. It has been found that in large businesses in which
hundreds of millions of accounting-related data sets are generated each month comprehen-
sive reports can thus already be obtained three to five days after the end of the month.
A comparison of the network systems of Fig. 1 and Fig. 2 further shows that whereas the
conventional network system of Fig. 1 involves extensive pre-processing of the generated
accounting-related data sets within the individual sub-systems (see sub-systems 14 and 16
in Fig. 1), no such pre-processing is performed in the network system according to the
invention shown in Fig. 2. Avoiding any pre-processing or at least drastically reducing pre-
processing insures that no elementary information included in the accounting-related data
sets generated by the sub-systems 10,12,14, 16 gets lost, i.e. can no longer be derived
from the (pre-processed) accounting-related data sets eventually received by the network
component 30. Refraining from or at least drastically reducing pre-processing of the ac-
counting-related data sets by the individual sub-systems 10,12,14, 16 is thus advanta-
geous when implementing the processing approach according to the invention, that is
based on the concept of centrally deriving the elementary information.
As regards possible hardware implementations of the network component 30, reference is
now made to Figs. 3 and 4.
Fig. 3 shows one possible client/server configuration, namely a so-called three-tiered ar-
chitecture in which the present invention can be carried out. According to the three-tiered
architecture, the network component 30 is separated into three functional groups: a plural-
ity of presentation servers 36, a plurality of application servers 38 and a plurality of data
base servers 40 as illustrated in Fig. 3 in a hardware-related view.
With the three-tiered architecture shown in Fig. 3, each hardware group 36,38,40 of the
network component 30 is set up to support demands of its functions. The tasks relating to
the presentation of data are handled by the presentation servers 36, which can typically be
configured as personal computers or work stations, enabling easy access to the system's
functionalities as regards the presentation and processing of enriched data sets generated
by individual applications running on the application servers 38.
The presentation servers 36 are coupled to the application servers 38 by means of a local
area network (LAN) 42 or any other type of wired or wireless network, such as a wide area
network (WAN), a wireless LAN (WLAN), a public switched telephone network (PSTN),
an integrated services digital network (ISDN), a satellite link, and the like. Also connected
to the LAN 42 via a homogeneous or inhomogeneous network 43 are the individual sub-
systems providing the accounting-related data sets. In Fig. 3 only two of the sub-systems
10,12 are exemplarily depicted.
The application servers 38 interfacing the presentation servers 36 include the processing
logic. In the present embodiment separate application servers 38 are provided for the task
of processing the received accounting-related data sets to generate multi-dimensional data
sets including the elementary information, for the task of generating and updating the ele-
mentary data base (not depicted in Fig. 3) and for the task of retrieving information from
the elementary data base in conjunction with generating report data sets. The application
servers 38 additionally provide system services such as spooling, dispatching user re-
quests, and formatting data.
The application servers 38 interface with the data base servers 40. The data base servers 40
host the master data base 32 and the elementary data base 34 that have been described in
conjunction with Fig. 2 as well as further data bases that will be described in more detail
below.
According to an alternative approach, a two-tiered architecture as shown in Fig. 4 can be
used. The two-tiered architecture schematically illustrated in Fig. 4 has similarities with
the architecture of Fig. 3. However, the functions of the application servers and data base
servers have been integrated using combined application and data base servers 41. Like in
the embodiment depicted in Fig. 3, the tasks of processing the received accounting-related
data sets, of generating and updating the elementary data base and of retrieving informa-
tion from the elementary data base in context with generating report data sets are per-
formed by three dedicated servers 41.
The presentation layer depicted in Figs. 3 and 4 includes user interfaces that are based on
WEB and MAP servers as well as on fat clients, e.g. for data presentation or work flow
control software packages.
The hardware approaches shown in Figs. 3 and 4 are advantageous in that inter-
dependencies between the network component 30 and the individual sub-systems 10,12,
... are strongly reduced. Furthermore, there is only a single point-of-entry for the account-
ing-related data sets that are provided by the sub-systems 10,12,... to the network com-
ponent 30. This is an expression of the approach of merging the streams of accounting-
related data sets that are to be subjected to different processing mechanisms. The concept
of a single point-of-entry allows to enhance data quality and enables the consistent applica-
tion of data quality checks. Another advantage of focusing the accounting-related data
streams to a single point-of-entry is the resulting single stream of information which al-
lows to accelarate data processing by applying uniform data processing mechanisms and
by introducing massive parallel processing techniques.
In the following, the basic parts of the servers depicted in Figs. 3 and 4 as well as the co-
operation of these parts in context with the processing of accounting-related data sets re-
ceived from the sub-systems 10,12,... will be described with reference to the integrated
view of Fig. 5.
As becomes apparent from Fig. 5, the network component 30 is considered to receive basi-
cally two data streams. On the one hand, the network component 30 receives application
data in the form of accounting-related data sets generated by individual applications run-
ning on the sub-systems 10,12,.... If, for example, the sub-system 10 is configured as an
ATM or a group of ATMs, an accounting-related data set for an ATM transaction may
include a code identifying the particular sub-system, (i.e. a particular ATM or group of
ATMs), a code identifying a customer, a code identifying a particular customer account,
a transaction value and a code relating to the transaction currency. The data sets may be
provided to the network component 30 in a standardized format or - with respect to legacy
systems - in a format that is not standardized but transformable to the required standard
format.
On the other hand, the network component 30 receives master data and updates for master
data. The master data may for example include static data and processing instruction data.
Static data include objects, rules, hierarchies and reference data like lookup tables or tables
of valid values containing a code and a description. Static data are applied to the different
types of data sets like accounting related data sets, multi-dimensional data sets, elementary
data sets, etc.
All the data received from the outside are received via a central data sourcing component
44. The data sourcing component 44 may perform certain pre-processing and data enrich-
ment tasks that do not diminish the informational content of the data received from the
outside and may take the form of a separate server. As becomes apparent from Fig. 5, the
data sourcing component 44 comprises two individual interfaces 44a, 44b for separately
receiving application data in the form of accounting-related data sets on the one hand and
master data (including static data, processing instruction data and updates) on the other
hand.
The data received from the outside are transferred via the data sourcing component 44 into
dedicated data bases. More specifically, the accounting-related data sets received via the
first interface 44a are stored in an entry data base 46, whereas the master data received via
the second interface 44b are stored in the master data base 32. The network component 30
further comprises an item data base 48 for storing multi-dimensional posting related data
sets as well as an elementary data base 34 for storing elementary data sets, e.g. elementary
balance-related data sets.
Additionally, the network component 30 comprises processing resources that are symboli-
cally illustrated as separate processors 52, 54, 56, 58. The processing resources can be
configured as central processing units (CPUs), micro controller units (MCUs), digital sig-
nal processors (DSPs), or the like. It is possible to integrate the individual processors 52,
54,... into fewer components or into a single component or to distribute the task of an
individual one of the processors 52, 54,... among several processors. The processors 52,
54,... are part of the application servers (reference numeral 38 in Fig. 3 and reference nu-
meral 41 in Fig. 4) and configured to perform individual processing tasks in context with
the present invention.
Now the cooperation of the individual parts of network component 30 depicted in Fig. 5
will exemplarily be described in context with transforming an accounting-related data set
generated by an ATM into several multi-dimensional data sets which are used to update
the elementary data base 34.
The accounting-related data set is received via the first interface 44a of the network com-
ponent 30. The interface 44a serves as single point-of-entry for all accounting-related data
sets regardless of their origin.
The ATM data set received by the first interface 44a may have a standardized or a non-
standardized format. In order to streamline the processing tasks performed within the net-
work component 30 it is advantageous to process the accounting-related data sets within
the network component 30 in a standardized format. Thus, the data sourcing component 44
formats any non-standardized accounting-related data sets and writes the formatted (stan-
dardized) accounting-related data sets into the entry data base 46. The formatting is done
such that no elementary information contained in the received accounting-related data sets
gets lost. The entry data base 46 is thus filled with accounting-related data sets having a
standardized format.
It should be noted that the applications running on the individual sub-systems are config-
ured such that no pre-processing is performed that diminishes the informational content
originally generated. Here, the term informational content relates to all informational as-
pects required by the processing mechanisms performed by the processor 58 to generate
the required information, i.e. in the present embodiment the processing mechanisms of
generating balance sheet data sets for official reporting purposes on the one hand and re-
port data sets for e.g. management accounting purposes on the other hand.
Besides formatting any non-standardized accounting-related data sets the data sourcing
component 44 is configured to check the received accounting-related data sets to ensure a
complete, timely and accurate delivery of the data sets from the individual sub-systems. In
the case of inconsistencies as regards the data set content, format, etc., the data sourcing
component 44 allows to handle exceptions. Handling exceptions may include completing a
received accounting-related data set (if possible), notifying a transmitting sub-system of
the inconsistency, triggering a re-transmission of a file containing the accounting-related
data set, etc.
The second interface 44b enables updates of the static data that are stored in the master
data base 32. In general, changes to table entries on static data occur independent from the
delivery of accounting related data sets, occur at different points of times and are made
available for processing mechanisms at a certain point of time for which data consistency
can be guaranteed. Static data are kept outside of the soft-coded program code for the
processing mechanisms, by which they are applied when processing accounting-related
data sets or multi-dimensional data sets or elementary data sets or the like.
As soon as a new accounting-related data set is stored in the entry data base 46, it is auto-
matically retrieved by the processor 52 that applies a central processing logic (CPL) to the
retrieved accounting-related data set. Thus, the CPL processor 52 operates asynchronously.
It should be noted that any data sets retrieved from the entry data base 46 are not immedi-
ately deleted but remain in the entry data base for tracking the flow of information at a
later point in time if required.
The basic task of the CPL processor 52 is to generate one or more multi-dimensional post-
ing-related data sets from an individual accounting-related data set retrieved from the entry
data base 46 as will now be explained with reference to the flow chart of Fig. 6.
In a first step 610 the CPL processor 52 identifies the type of accounting-related data set
retrieved from the entry data base 46 and the processing mechanism that has to be applied
by the CPL processor 52 to transform the accounting-related data set into the one or more
multi-dimensional posting-related data sets. In the present case the CPL processor 52 thus
determines that an ATM data set has been retrieved from the entry data base 46 and that
accordingly an ATM transformation routine has to be applied to this data set. Other types
of accounting-related data sets that may be identified by the CPL processor 52 could in-
clude data sets relating for example to e-banking transactions like an electronic funds
transfers or the like.
Additionally, the CPL processor 52 identifies for the retrieved ATM data set the associated
static data. The static data associated with the ATM data set can for example be deter-
mined using the customer account identificator included in the ATM data set as a refer-
ence.
Using the customer account identificator as reference, the CPL processor 52 retrieves in
a next step 620 associated static data about a customer involved, the customer's position
involved, the entity serving the customer etc. from a look-up table or any other suitable
data structure stored in the mater data base 32. The CPL processor 52 further retrieves the
appropriate ATM transformation and generation rules from the master data base 32 in or-
der to produce multi-dimensional data sets as required by the multi-dimensional generic
data template.
An exemplary generic data template reflecting multi-dimensional attributes is partially
depicted in Fig. 7. The generic data template basically includes a plurality of predefined
data fields that specify all the elementary information required by the various processing
mechanisms applied by the processor 58 to generate different kinds of report data sets. In
other words, the data fields of the generic data template reflect the combined input re-
quirements of the plurality of different processing mechanisms that are to be performed at
a later point in time. Also, the generic template is configured to be applicable to all types
of accounting-related data sets that may be received via the interface 44a or that may be
generated by processing mechanisms within the network component 30. In the embodi-
ment depicted in Fig. 7 the generic data template is comprised of 30 different data fields.
Depending on the particular report requirements, the number of individual data fields may
be increased or, to a certain degree, decreased.
In a next step 630 the CPL processor 52 processes the ATM data set retrieved from the
entry data base 46 and the associated static (and reference) data retrieved from the master
data base 32 to derive the elementary information included therein. This task is performed
under the control of the applicable ATM transformation rules retrieved from the master
data base 32. The transformation rules specify how and which multi-dimensional posting-
related data sets are to be generated in a further step 640 by the CPL processor 52 from the
ATM data set and the associated static data. In the exemplary case of an ATM data set the
transformation rules specify that two individual multi-dimensional posting-related data
sets have to be generated as illustrated in Fig. 8.
From Fig. 8 it becomes apparent that, applying the ATM transformation rules, the CPL
processor 52 generates a first posting-related data set titled "Debit Customer
Account" and a second posting-related data set titled "Cash Turnover". As can be seen, not
all predefined data fields of the generic data template are applicable to the ATM data set.
Consequently, individual ones of the predefined data fields remain empty or can be omit-
ted (e.g. data fields 6 and 8 titled "Cost Center" and "Complex Contract", respectively, or
data field 15 titled "Bank Position ID" of the first posting-related data set).
The generic data template depicted in Fig. 7 and the data sets shown in Fig. 8 are multi-
dimensional in that they include a comparatively high number of pre-defined data fields.
Depending on the input requirements of the processing mechanisms, the generic data tem-
plate may include more than twenty or even more than forty predefined data fields. Due to
this multi-dimensionality of the generic data template, the individual posting-related data
sets generated by the CPL processor 52 on the basis of this generic data template are also
multi-dimensional in that they include much more information than conventional data sets
used for posting purposes.
Also, the information contained in the individual multi-dimensional posting-related data
sets generated by the CPL processor 52 is in general much more elementary than the in-
formation contained in conventional data sets used for posting purposes (that have only to
satisfy the input requirements of one single processing mechanism). The fact that the
multi-dimensional posting-related data sets generated by the CPL processor 52 on the one
hand have a high informational content as regards the combined input requirement of a
plurality of processing mechanisms and on the other hand include information on a very
elementary level is beneficial as regards reducing data redundancy and increasing data
throughput.
The transformation routine performed by the CPL processor 52 includes a control logic
that assigns control attributes to the posting-related data sets. The control attributes control
the later accumulation of the elementary information in the elementary data base 34 and
the generation of report data sets. The assignment of the control attributes is performed
entirely automated based on the individual transformation routine and the information
contained in the accounting-related data sets as well as in the associated static data. In gen-
eral, the control attributes reflect the level of detail and dimensions of reports that can be
generated as well as the technical flexibility and capabilities of the overall system.
The control attributes assigned by the CPL processor 52 include different predefined codes
required for accumulating the elementary information in the elementary data base and for
generating the report data sets by the different processing mechanisms. Thus, the control
attributes may for example include a General Ledger (G/L) account code and a currency
code (both required for the processing mechanism of generating financial accounting re-
ports) and a profit/cost center code and a customer ID code (both required for the proc-
essing mechanism of generating management accounting reports).
The individual multi-dimensional posting-related data sets generated by the CPL processor
52 (like the two posting-related data sets shown in Fig. 8 generated for an ATM data set)
are stored as separate items in the item data base 48. When storing the multi-dimensional
data sets in the item data base 48 the CPL processor 52 links each data set stored in the
item data base 38 with the corresponding accounting-related ("parent") data set stored in
the entry data base 46. This might be done by appending to each posting-related set a ref-
erence to the memory location of the parent data set in the entry data base 46.
The posting-related data sets stored in the item data base 48 are retrieved by a processing
mechanism running on the posting processor 56. The posting processor 56 has the task of
updating the elementary data base 34 on the basis of the elementary information contained
in the multi-dimensional data sets stored in the item data base 48. The elementary data
base 34 is configured as a relational data base having read-only restrictions with respect to
all accesses different from the updating process performed by the posting processor 56.
This guarantees a high integrity and authenticity of the information stored in the elemen-
tary data base 34.
The posting processor 56 accumulates the elementary information included in the posting-
related data sets onto already existing or newly created elementary data sets stored in the
elementary data base 34. This accumulation is performed taking into account the individ-
ual control attributes assigned by the CPL processor 52 under additional control of (post-
ing) control data stored as processing instruction data in the master data base 32.
In the case of the exemplary ATM transaction resulting in the exemplary multi-
dimensional posting-related ATM data sets shown in Fig. 8, the posting processor 56 ac-
cumulates the transaction amount included as elementary information in data fields 29 and
30 (Debit/Credit) of the posting-related data sets onto those elementary data sets in the
elementary data base 34 that are associated with exactly the same set of individual control
attributes (indicated as data fields 1 to 19ff. in the posting-related data sets of Fig. 8).
Thus, the G/L account code, the customer ID code and all the other codes fulfill their func-
tionality as control attributes. In the exemplary embodiment discussed here the various
combinations of control attributes define more than 800 million different elementary data
sets, each elementary data set being specified by a particular combination of control attrib-
utes. This high number of elementary data sets is a consequence of the highly granular
nature of the multi-dimensional posting-related data sets and a pre-requisite of the multi-
ple reporting mechanisms that are to be performed using the elementary data base 34 as
single source of information.
In Fig. 9 two exemplary elementary balance-related data sets generated by repeatedly ac-
cumulating different multi-dimensional ATM data sets as those depicted in Fig. 8 are
shown. As becomes apparent from Fig. 9, the values included in data fields 29 (Debit) and
30 (Credit) of the multi-dimensional data sets shown in Fig. 8 are accumulated onto the
data fields titled "Live to Period Debit", "Live to Period Credit", "Period Net Debit" and
"Period Net Credit" of the individual balance-related data sets shown in Fig. 9. This accu-
mulation is performed taking into account the temporal information included in data field
28 of the multi-dimensional posting-related data sets.
The individual elementary balance-related data sets stored in the elementary data base 34
reflect balance information generated by repeatedly accumulating particular data included
in individual posing-related data sets. The multi-dimensionality of the posting-related data
sets allows to define a plurality of 20, 30 or more key fields in the relational elementary
data base 34 without the necessity to duplicate individual accumulated amounts. The key
fields of the elementary data base 34 relate to the control attributes included in the posting-
related data sets like a profit or cost center code, a customer ID or the like.
It should be noted that the balance-related data sets are shown in Fig. 9 in their logical
structure. Due to the relational nature of the elementary data base 34 the individual data
fields of a balance-related data set may be dispersed over various individual tables.
The posting processor 56 may operate asynchronously or perform the postings batch-wise.
When the posting processor 56 updates the elementary information contained in elemen-
tary data sets on the basis of elementary information included in a posting-related data set
retrieved from the item data base 48, the posting processor 56 additionally performs a link-
ing operation appending a reference to the retrieved multi-dimensional posting-related data
set to the updated elementary data set and/or vice versa.
Since the elementary data sets stored in the elementary data base 34 are updated on the
basis of the elementary information included in the posting-related data sets, the elemen-
tary data sets correspond to individual data fields of the posting-related data sets (and thus
to data fields of the generic data template as shown in Fig. 7). It is ensured that the infor-
mation is kept in the elementary data base 34 on a very granular and elementary level,
which helps to keep the processing mechanisms operating on the elementary data sets
very generic. This is in contrast to the conventional processing mechanisms which in
general do not operate on elementary information but on pre-processed information.
The elementary data sets stored in the elementary data base 34 are retrieved by the report-
ing processor 58 when performing different processing mechanisms like a financial ac-
counting mechanism or a management accounting mechanism to generate respective report
data sets (data set 1 to data set 4 in Fig. 5). Processing instruction data characteristic of the
different processing mechanisms are stored as master data in the master data base 32. The
processing mechanisms may simply be adapted by updating the respective processing in-
struction data stored in the master data base 32.
The report data sets like a balance sheet data set generated by the report processor 58 may
be transferred via the LAN 42 depicted in Fig. 3 and Fig. 4 to the presentation servers 36
for being displayed on a local graphical user interface (GUI) or they may be transferred via
any other data transfer mechanism to other computer systems as well, e.g. for consolida-
tion processes on group level.
The elementary data sets stored in the elementary data base 34 are not only retrieved by the
report processor 58 but also by the evaluation processor 54. The evaluation processor 54
performs processing mechanisms that are based on applying pre-defined evaluation criteria
stored as processing instruction data in the master data base 32 and on determining if indi-
vidual values contained in the extracted elementary data sets differ from actual values.
Should this be the case, the evaluation processor 54 generates compensated multi-
dimensional data sets as well as compensated accounting-related data sets as required. Any
newly created and compensated accounting-related data set stored by the evaluation proc-
essor 54 in the entry data base 46 is then retrieved by the CPL processor 52, which proc-
esses the retrieved data set as explained above to generate one or more compensated multi-
dimensional posting-related data sets that are stored in the item data base 48. The compen-
sated multi-dimensional data sets thus generated may then be used by a subsequent proc-
essing mechanism to update the associated elementary data sets in the elementary data
base 34.
Although preferred embodiments of the present invention have been illustrated in the ac-
companying drawings and described in the a foregoing detailed description, it will be un-
derstood that the invention is not limited to the embodiments disclosed, but is capable of
numerous rearrangements, modifications and substitutions without departing from the
spirit and scope of the invention as set forth and defined by the following claims.
We claim:
1. A network component (30) for transforming accounting-related data sets into
multi-dimensional data sets which are used to update a database (34) that is used
by two or more different processing mechanisms (58) for providing report data
sets, comprising:
at least one master database (32) for storing master data including static
data and a multi-dimensional generic data template, the data template
specifying pre-defined data fields relating to elementary information
determined by the data input requirements of the different processing
mechanisms;
at least one interface (44) for receiving the accounting-related data sets
from a plurality of individual sub-systems (10, 12, 14, 16);
processing resources (52) having access to the master database (32), for
generating from an accounting-related data set one or more associated multi-
dimensional data sets by deriving elementary information included in the
accounting-related data set and in static data associated with the accounting-
related data set and by writing the derived elementary information in
corresponding data fields specified by the data template; and
an elementary database (34) updated on the basis of the elementary
information contained in the one or more multi-dimensional data sets,
wherein the elementary database (34) is jointly used by the different
processing mechanisms (58) to generate report data sets.
2. The network component of claim 1, wherein
the elementary database (34) includes elementary data sets that correspond to the
data fields of the data template at least partially.
3. The network component of claim 2, wherein
the processing resources (56) are programmed to update the elementary database
(34) by accumulating elementary information included in the multi-dimensional
data sets onto newly created or already existing elementary data sets.
4. The network component of claim 3, wherein
the processing resources (52) are programmed to assign one or more control
attributes to the multi-dimensional data sets, the control attributes being inserted
or included in one or more data fields of the multi-dimensional data sets and
controlling the process of accumulating the elementary information onto the
elementary data sets.
5. The network component of claim 4, wherein
the one or more control attributes of the multi-dimensional data set include at
least an identification code.
6. The network component of one of claims 2 to 5, wherein
one or more of the elementary data sets are linked with at least one of the multi-
dimensional data sets accumulated thereon and the accounting-related data sets
associated with the multi-dimensional data sets accumulated thereon.
7. The network component of one of claims 2 to 6, wherein
the processing resources (58) are programmed to generate the report data sets by
applying the processing mechanisms to a plurality of the elementary data sets
stored in the elementary database (34).
8. The network component of claim 7, wherein
the elementary database (34) is configured as the only source for providing
authorized information for generating the report data sets.
9. The network component of one of claims 1 to 8, wherein
the elementary database (34) is configured as a read-only database with respect to
all accesses different from updating.
10. The network component of one of claims 1 to 9, wherein
processing instruction data characteristic of the different processing mechanisms
are stored as master data in the master database (32).
11. The network component of one of claims 1 to 10, further comprising
an entry database (46) for storing the accounting-related data sets received via the
at least one interface (44) from the sub-systems (10,12, 14, 16).
12. The network component of claim 11, wherein
at least one data sourcing component (44) is configured to format the accounting-
related data sets received from the sub-systems (10,12,14,16) and to write the
formatted accounting-related data sets into the entry database (46).
13. The network component of one of claims 1 to 12, further comprising
an item database (48) for storing the multi-dimensional data sets generated by the
processing resources (52).
14. The network component of claim 13, wherein
the multi-dimensional data sets stored in the item database (48) are linked with at
least one of the associated accounting-related data sets stored in the entry database
(46) and one or more of the associated elementary data sets stored in the
elementary database (34).
15. The network component of one of claims 1 to 14, wherein
the processing resources (52) are programmed to transform the accounting-related
data set into one or more multi-dimensional data sets using the static data
associated with the accounting-related data set.
16. The network component of claim 15, wherein
different types of accounting-related data sets are defined and wherein for each
type of accounting-related data set an associated transformation is provided.
17. The network component of one of claims 1 to 16, wherein
the processing resources are programmed to identify for a specific accounting-
related data set at least one of the associated static data and the associated
transformation.
18. The network component of one of claims 1 to 17, wherein
the at least one data sourcing component (44) is configured to check the
accounting-related data sets received from the sub-systems (10,12,14,16) and to
handle exceptions in the case of inconsistencies of one or more of the accounting-
related data sets.
19. The network component of one of claims 1 to 18, wherein
the network component (30) is implemented as a three-tiered system including at
least one presentation server (36) for presenting individual data sets or
information derived therefrom, at least one application server (38) and one or
more database servers (40) including one or more of the databases (32, 34, 46,
48).
20. The network component of one of claims 1 to 18,
wherein the network component (30) is implemented as a two-tiered system
including at least one presentation server (36) for presenting individual data sets or
information derived therefrom and at least one combined application and database
server (41).
21. The network component of one of claims 1 to 19, wherein
the processing resources (54) are programmed to access the elementary database
(34) for evaluation purposes during which at least one of new multi-dimensional
data sets and new accounting-related data sets are generated.
22. A computer network system comprising the network component (30) of one of
claims 1 to 21 and a plurality of sub-systems (10,12,14,16) attached to the
network component (30), wherein on each sub-system (10,12,14,16) one or
more individual applications for generating the accounting-related data sets are
installed.
23. The computer network system of claim 22, wherein
the individual applications provide standardized accounting-related data sets.
24. The computer network system of claim 22 or 23, wherein
the individual applications are programmed not to perform any pre-processing
with respect to the processing mechanisms applied by the network component
(30).
25. A method of transforming accounting-related data sets into multi-dimensional
data sets (48) which are used to update a database (34) that is used by two or more
different processing mechanisms (58) to provide report data sets, comprising:
providing master data including static data and a multi-dimensional generic
data template, the data template specifying pre-defined data fields relating to
elementary information determined by the data input requirements of the
different processing mechanisms;
receiving the accounting related data sets from a plurality of individual sub-
systems (10, 12, 14 16)
generating for an accounting-related data set one or more associated multi-
dimentional data sets by deriving elementary information included in the
accounting related data set and in statis data associated with the accounting
related data set and by writing the derived elementary information in
corresponding data fields specified by the data template; and
updating a elementary data base (34) on the basis of the elementary
information contained in one or more multi-dimensional data sets, wherein the
elementary data base (34) is jointly used by the different processing
mechanisms to generate report data sets.
26. A computer program product including programe code portions for performing
the steps of claim 25 when the computer program product is run on one or
more components of a computer network.
27. The computer program product of claim 26, stored on a computer-readable
recording medium.

The invention relates to aspects in context with updating a data base that is jointly used by two or more different processing mechanisms on the basis of multi-dimensional data sets. A network component performing this task includes a master data base for storing master data including static data and a multi-dimensional generic data template having predefined data fields relating to elementary information determined by the data input requirements of the different processing mechanisms. An interface is provided for receiving accounting-related data sets from a plurality of individual sub-systems. Processing resources having access to the master data base generate for each accounting-related data set one or more associated multi-dimensional data sets by deriving elementary information included in the accounting-related data set and in static data associated with the accounting-related data set and by writing the derived elementary information in corresponding data fields of the data template. On the basis of the elementary information contained in the one or more multi-dimensional data sets an elementary data base that is jointly used by the different processing mechanisms to generate report data sets is updated.

Documents:

608-kolnp-2006-granted-abstract.pdf

608-kolnp-2006-granted-claims.pdf

608-kolnp-2006-granted-correspondence.pdf

608-kolnp-2006-granted-description (complete).pdf

608-kolnp-2006-granted-drawings.pdf

608-kolnp-2006-granted-examination report.pdf

608-kolnp-2006-granted-form 1.pdf

608-kolnp-2006-granted-form 18.pdf

608-kolnp-2006-granted-form 2.pdf

608-kolnp-2006-granted-form 3.pdf

608-kolnp-2006-granted-form 5.pdf

608-kolnp-2006-granted-pa.pdf

608-kolnp-2006-granted-reply to examination report.pdf

608-kolnp-2006-granted-specification.pdf


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Patent Number 233010
Indian Patent Application Number 608/KOLNP/2006
PG Journal Number 13/2009
Publication Date 27-Mar-2009
Grant Date 25-Mar-2009
Date of Filing 15-Mar-2006
Name of Patentee UBS AG
Applicant Address BAHNHOFSTRASSE 45, CH-8001 ZÜRICH, SWITZERLAND.
Inventors:
# Inventor's Name Inventor's Address
1 SCHAFFLÜTZEL, THIERRY STEINACKERSTRASSE 20, CH-8962 BERGDIETIKON
2 AERNE, BRUNO LANGACKERSTRASSE 24, CH-8952 SCHLIEREN
3 BLATZ, JÜRGEN CANTEGREL, F-24170 CARVES
4 MACHE, CHRISTOPH UNT. HOFBERGSTRASSE 14, CH-9500 WIL
PCT International Classification Number G06F 17/30
PCT International Application Number PCT/EP2004/009654
PCT International Filing date 2004-08-30
PCT Conventions:
# PCT Application Number Date of Convention Priority Country
1 03019778.4 2003-08-29 EUROPEAN UNION