Data Warehousing

Data Warehouse is a subject oriented, integrated, time-variant, non-volatile collection of data used to support the strategic decision making process of the enterprise. Data warehouse provides a common view of enterprise data. With minimum daily update commitments data warehouse provides clean, scrubbed and validated data which can be further used for analysis and decision making processes. Due to its history retention, data warehouse can grow to become the largest database in the enterprise.

Building large scale data warehouse and departmental data marts faces numerous challenges such as sound data warehouse design, managing volume, granularity and partitioning of data, data profiling, maintaining data quality and integrity, data summarization, building intermediate data staging areas and operational data store, data security, etc.

Scalable Systems specializes in all types of data warehousing architecture including Bill Inmon`s corporate information factory architecture, Ralph Kimball`s data warehousing methodology, dimensional modeling, etc. Scalable Systems specializes in all major ETL and data integration software packages including Informatica, Abinitio, Data stage, and Data cleansing/management software like Trillium, Dataflux and Syncsort, etc.

Scalable Systems offers services in Data Warehousing including but not limited to

Analysis of the source and target system and project scoping
Evaluation ETL tool, BI tool, Data Modeling tool best suited as per the requirement and budget
Requirement gathering and fact identification for the data warehouse environment
Dimensional Modeling and relational modeling
Technical architecture design including backend/staging areas and frontend/reporting
ETL architecture, design and implementation
Physical database design and implementation
Architecture, design and implementation of OLAP/Reporting
Performance tuning of Data Warehousing, Database, ETL Systems and Front End Applications
Data Warehouse deployment, training, support and maintenance
Blueprinting to manage growth of data and load balancing