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Enterprise Data Warehousing and Business Intelligence
As part of our Enterprise Data Warehousing and Business Intelligence (EDW and BI) practice, we deliver Data Infrastructure solutions, analytical architecture services and power user tool-chest services. As part of Data Infrastructure services, we provide services such as Extract, Transform and Load (ETL), Staging Hub Development and Maintenance, Data cleansing, Enterprise Application Integration, Data Migration, Operational Data Store (ODS) and Data Warehouse (DWH) development and maintenance services. The tools that we use in this service oriented ETL framework are Informatica, Datastage, Oracle Warehouse builder on databases such as Oracle and SQL Server 2005. We offer the following Services:
> Data Warehouse Architecture Assessment, Strategy and Development
> Business Activity Monitoring and Performance Management
> Data Warehouse and Business Intelligence Maintenance Services |
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BI / DW Consulting
- Assessment of Data Warehouse
Architecture
- Tools Evaluation and Recommen
dation
- Data Warehouse Performance
Tuning |
Data Warehousing
- Data Modeling
- Data Cleansing and ETL
- Meta Data Management
- DW Migration / Convergence
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Reporting & Analysis
- Enterprise Reporting
- Management Performance Scorecards
- Online Analytical Processing (OLAP) Reporting
- Report Migration / Upgrades
- BI Reporting |
Support & Maintenance
- Long Term Maintenance and Support
- Dedicated Offshore Development Center
- 24 X 7 Support
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Approach
The Rocsys Business Intelligence team comprises of professionals with deep understanding of Business Intelligence Applications and technology architecture of Data Warehousing solutions. Rocsys adopts an Iterative Warehouse Development Strategy that results in real, immediate and high profile benefits, higher ROI and reduced TCO. Rocsys follows three types of approaches:.
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| Data-Driven |
Demand-Driven |
Goal-Driven |
| The data warehouse development strategy is based on the analysis of organizational data models and relevant transactions. The requirements are the last thing to be considered in the decision support development life cycle, they are understood after the DW has been populated with data and results of queries have been analyzed by users. This approach ignores the needs of DW users a priori. |
The first stage of this approach is the derivation process which determines goals and services the organization provides to its customers. Then the business process is analyzed to highlight the customers and their transactions with the process under study. In a third step, sequences of transactions are transformed into sequences of existing dependencies that refer to information systems. The last step identifies measures and dimensions needed for design. |
This approach assumes that the organization goal is the same for everyone and the entire organization will therefore be pursuing in the same direction. It is proposed to set up a first prototype based on the needs of the business. Business personnel define goals and gather, prioritize as well as frame business questions supporting these goals. Later the business questions are prioritized and the most important ones are defined in terms of data elements, including the definition of hierarchies. |
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| Methodology |
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Planning: Planning activities focus on the preparation of Business Cases, definition of the required BI infrastructure and defining BI roadmap.
Scoping: Scoping activities relate to the initiation of a BI project and include development of the Business Assessment, Requirement Collection, Project Definition, Project Planning and Project Team.
Design: This phase includes Analysis and Design activities to create DW Architecture, Conduct Technology involved and Data Quality Assessment, Design Data Models, Metadata Repository, ETL Application and BI Reports.
Code Building: Code construction phase during which all physical Data Models, ETL Code and BI Reports have been constructed.
Testing: Testing activities focusses on Unit testing, System Integration Testing, User Training and User Acceptance Testing. Testing includes quality checking of all ETL code and BI reports constructed.
Deployment: Solution deployment planning rollout and Production Rollout execution activities including User Training and Production deployment of BI databases, Metadata Repository, ETL code and BI Report.
Support: Post production implementation activities focused on BI application Monitoring and Support, including monitoring of Data Load Logs, Data Volumes, Data Auditing, Report Usage frequencies and Change Tracking. |
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