A Brief Summary of Data Warehousing

Data Warehousing pic
Data Warehousing
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Timothy Valihora, president of TVMG Consulting, Inc., is required to manage technical architecture for his job. Timothy Valihora has over 20 years of work experience in this area, with a main focus on data governance, data warehousing and data conversions.

Mr. Valihora is now one of the foremost experts in “Open IGC” which involves creating technical assets within the IBM Information Server Information Governance Catalog (IGC) via “Bundle.zip” technology. Once custom technical assets are created within IGC the REST API is used to create assets and map them to their associated terms. If no ‘metabroker’ or connector exists – within IIS – simply stated – the REST API must be used to create the asset within the governance catalog.

Tim Valihora is an expert in all aspects of IBM IGC, Open IGC and the REST API.

A data warehouse differs from a traditional database in that it is designed for query and analysis, whereas a traditional database is designed for transaction processing. A data warehouse typically contains historical data derived from transaction data, and includes a relational database as well as an extraction, transportation, transformation, and loading (ETL) solution, an online analytical processing engine, and client analysis tools, among other data-managing applications.

Data warehouse projects usually require a cross-functional team of people with either business or IT experience, although often at least one person will fulfil more than one role on this team. Role assignments depend on the size of the project as well as each individual’s availability and experience. The project requires representatives to fill a large number of roles including business sponsor, analytic application developer, technical architect, and data modeller.