About the Webinar
This presentation explores data warehousing not merely as a technical solution, but as a critical business capability for achieving strategic goals. It addresses the common pitfalls of data warehousing projects, arguing that most failures are not due to technology, but to poor planning, lack of organizational data literacy, and a failure to address the underlying data quality. The core message is that “garbage in, garbage out” is always true, and that a successful data warehouse is built on a foundation of clean, organized data.
The presentation outlines good data warehousing practices that prioritize:
- Engineering and Architecture: Emphasizing that effective data warehousing requires skilled engineering talent and a holistic, adaptive architectural approach, rather than a prescriptive, cookie-cutter method.
- Data Preparation and Quality: Highlighting the need to separate “the wheat from the chaff,” with a focus on eliminating redundant, obsolete, or trivial (ROT) data before it enters the warehouse.
- Iterative Development: Advocating for a continuous improvement cycle (plan, do, check, act) to iteratively refine the data warehouse in alignment with strategic business direction.
- Business Alignment: Stressing that data warehousing must be driven by business needs and a clear strategy, with a focus on using warehousing capabilities to solve specific business challenges rather than just building a large repository.
The ultimate goal is to reframe data warehousing as a means to increase organizational capabilities, improve operations, and create new strategic opportunities, thereby providing a clear, measurable return on investment.
About the Speakers
Peter Aiken, Ph.D. is an acknowledged Data Management authority, an associate professor at Virginia Commonwealth University, president of DAMA International, and associate director of the MIT International Society of Chief Data Officers. For more than 40 years, Peter has learned from working with hundreds of Data Management practices in more than 30 countries. Among his 13 books are the first on making the case for data leadership (CDOs), the first focusing on data monetization and modern strategic data thinking, and the first to objectively specify what it means to be data-literate. International recognition has resulted from these and a (pre-Covid-19) intensive worldwide events schedule. Peter also hosts the longest-running Data Management webinar series on dataversity.net. Before Google, before data was big, and before Data Science, Peter founded several organizations that have helped more than 200 businesses leverage data – specific savings have been measured at more than $1.5 billion. His latest venture is Anything Awesome.
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