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 Services -- Data Management -- Data Warehouse

     Data Warehouse is the most important component of business intelligence solution for any organization.  We can provide assistance in designing data warehouse architecture, implementing ETL modules, data access front-end and provide advance data analysis services.  

     Designing data warehouse architecture. Right data warehouse architecture is critical in effectively managing knowledge in organizations.  It needs to be inclusive, flexible and expandable.  We have implemented many data warehousing solutions and our experience can be very beneficial in setting the blues print for your business intelligence solution.

     Design and deployment of ETL (Extract Transform and Load) modules.  On average 70 to 80% of effort would be spent on extracting, transforming and then loading the data.  The ETL module needs to meet many stringent requirements; it needs to support complex transformations, be scalable, expandable and provide low latency.   This is why most often the failure in data warehouse deployment lays in ETL implementation.  The process of extracting, transforming and loading data can be spec out and develop by our ETL specialists who understand the ETL challenges.  We are familiar with different tools and languages such as:  AbInitio, Oracle Warehouse Builder,  PL/SQL, Informatica, Decision Stream, SAP BW,  … To mention a few

     Front end development.  Creating the front end, maintaining it and responding to many new requests can be demanding and code intensive.  Many of these tasks can be also spec out and develop by our IT professionals.  We are very capable of creating sophisticated interfaces for data reporting, OLAP tools, “score cards” or GIS data depictions.  Also, we can be very helpful the front end maintenance and up keep.  Our specialists are familiar with the following tools; MS Analytical Services, Cognos, Business Objects and Microstrategy.


Past engagements

 

     For a large city (1.3 million citizens) planned, designed and implemented a large data warehouse (1.8 million clients’ records) collecting data from various social services agencies or departments.  Data coming from very diverse systems, some of the sources required real time synchronization.

 

     Planned, designed and implemented a data warehouse in a state department managing a budget of $ 1 billion.  The data warehouse housed data from various disperse and not connected sources.

 

     For a human services department (with budget of $0.8 billion)at a large urban area (1.3 million citizens) planned, designed, implemented and maintained its data warehouse.