It is important to determine expected usage patterns for business intelligence and analytical applications before design, and to evaluate their actual usage after implementation to gauge success. Building an analytical solution can be an arduous task. Many factors are required
Every data warehouse and business intelligence initiative has risks. Learn to identify them at the start and select the optimal remedy or mitigation technique to address each risk. It is essential to identify the potential risks within every project and
Explaining data warehouse automation can be challenging, but all data warehouse / business intelligence professionals should understand the concepts and practices. Data warehouse automation is not some sort of wizardry. It does not automagically build, model, and load a data
Three steps can help any organization develop the right architecture for business intelligence, analytics, or a re-design of a data warehouse The best place to start is at the beginning. Does the effort involve building a solution that includes reporting,
Successful re-architecture of data warehousing / business intelligence / analytics environments pose business challenges in addition to information technology issues Many large corporations across a variety of industries face the reality of re-architecting data warehouse environments to accommodate business intelligence
Rather than apply new words or phrases to poor data architecture concepts, learn how a data strategy should influence effective data architecture, especially for analytics and business intelligence People love buzzwords. Sometimes people think the quality of a solution improves
All successful business intelligence / analytics endeavors are based on a formal strategy and use a best-practices based methodology, even in agile environments. Many companies do not have a data strategy, which is a basic component for successful management of
Applying DevOps-style test automation to projects can guarantee a high level of data quality in any business intelligence / analytics initiative. Introduction According to a CIO.com article, Gartner Group recently stated that between 70 and 80 percent of business intelligence initiatives
Data extraction, transformation, and loading processes enable many activities in information technology projects. Understanding the concepts and practices of ETL is essential for all data and technology professionals IntroductionData extract, transform, load (ETL) is a process of copying data from
Preparing a data warehouse testing strategy can ensure the successful development and completion of end-to-end testing of any data warehouse, data mart, or analytical environment. Introduction Organizations need to learn how to build an end-to-end data warehouse testing strategy. This
