Custom Solutions, Endless Possibilities for Startups and Enterprises
CDR:- Central data repository
ADF:- Automated Data Flow
MIS :- Management information system requirements of the Bank
XBRL:- Returns to be submitted in XBRL formats
Returns to be submitted in XBRL formats as per taxonomy published by RBI
The CDR should be populated with clean and valid data and should synchronize financial and non-financial data from various source systems of the bank.
Eliminate multiple data version by creating single version of data at any point of time
Study of Existing Data Sources.
Project Planning & preparation of Software Requirement Specifications (SRS)
Data Extraction from existing applications for meeting all ADF & MIS requirements.
Data Validation mechanism.
Setting up of Central Data Repository (CDR).
Automated Extract-Transform-Load process for a near real-time/T+1 data availability for reporting.
Automated Data Flow as per RBI requirements
Data Security and Data Governance features.
Bank has provided the customer data in the Excel File
ETL Package prepared for the data extraction from the customer data excel file.
Data extracted and imported into staging table using SSIS.
Performed transformations for applying the business rule and validations on the staging server table (Raw Data).
Load data from staging database to CDR database using SSIS.
Generate the Commercial and Consumer text file including error file from ADF Application in desired format.
Software is web based, menu driven and user friendly.
Access is through user login.
User defined access control available. The access can be configured on need to know basis.
Audit trails provided for each login, logout, and Addition/deletion/modification by individual users.
Uploading of data in electronic form as well as data entry mode available.
Provision of Data Governance by using feature such as Maker / Checker.
Software compiles statements of sundry deposits, sundry credits, and suspense debits.
Is able to configure the amount in Thousands, Lakhs, and Crores.
Supports multiple currencies.
Compiles statements relating to Asset Classification, Allocation of Advances & Unrealized Interest.
Has provisions to accommodate increase in no. of branches ,zones etc and also various other fields which may come in future.
Uploading of data any number of times permitted at various stages like pre-audit, post audit and post MOC.
All the Required data from Finacle CBS and other systems (Source tables) Extracted to the Stage Database. Configurable frequency to ensure returns periodicity.
In POC bank had provided customer data in the excel file
Other set of ETL packages use this Staged Database for transformation, mapping and cleaning various data elements and loading into CDR from where the reports & returns are generated.
Generate the Commercial and Consumer text file including error file from ADF Application in desired format.
All the Required data from CBS and other systems (Source tables) Extracted to the Stage Database which acts as a single repository of data for all MIS, BI and reporting purposes. Transformation for mapping and cleaning various data elements is done at on this
Other ETL packages use this Staged Database for loading into Reporting server and CDR from where the reports & returns are generated.
Legacy system data is collected in Flat files and transfer to database through ETL packages.
Data not available in any system is fetched through data entry programs.
SSIS is used as underlying platform Integration
It is a Enterprise ETL platform
Best in class usability
Data Adaptors .Custom Data Maps and Transformation Rules .Sources – Finacal Data bases, Excel, Flat Files, etc.
.Data Validation .Data Standardization .Generation of Data Sets for .Predictive Modeling
Data Profiling – to detect defect levels in variable values
Deployment of Data Profiling functions for incremental data
Development of Business Rules for transformation / standardization
Customer ID creation
Standardization of categorical variable values
Conversion (Pin Code to City Name)
Missing value population with Business Rules
Creation of Bins for functions like frequency distribution (e.g. Age)
Develop a complete assessment of the scope and nature of data quality issues in CBS and other source databases along with existing MIS database of the Bank.
Create an inventory of data assets.
Inspect bank’s CBS and other Source data bases for errors, inconsistencies, redundancies and incomplete information in the data.
Build the foundation for future data management initiatives to provide clean, consistent, effective and efficient data.
Plan and prioritize data correction initiatives.
Identify and resolve problematic data.
Standardize, normalize and transform data before loading into bank’s CDR.
Validate and improve the overall accuracy of data.
