Last week, we held a webinar, The Modern Data Warehouse – A Hybrid Story. As the world of data evolves ever so quickly, it transforms the industry and creates a need for new approaches to business intelligence. Data warehousing technology that worked well for years, serving its purpose to manage and understand business driven data, is now falling short for some.
During the session, Duane Schafer, Director of Perficient’s Microsoft BI Practice, first reviewed what makes up a traditional data warehouse, discussing both logical and physical architecture, and stressors to the traditional data warehouse that drove the need for change. Gartner reported in The State of Data Warehousing in 2012, “Data warehousing has reached the most significant tipping point since its inception. The biggest, possibly most elaborate, management system in IT is changing.”
Duane went on to describe this change, and what was behind it, including recent findings from TDWI Research. and shared his thoughts around a modern DW alternative, and answered a common question – How does this affect our ‘traditional’ DW approach? As is often the case with a more modern alternative, there are new capabilities that make it a worthwhile choice. For the modern DW, these capabilities include:
- Scaling out relational data to petabytes / scale out technologies within the Parallel Data Warehouse
- Scaling out “Big Data” / scale out non-relational data in HDInsight (for Azure or PDW)
- In memory columnstore for next generation performance (up to 100x faster and 10x compression)
- Great performance for mixed workloads / query performance at scale
- Integrating relational data and Hadoop
As well as forecasting capabilities in Power View for Office 365 and Microsoft Azure Machine Learning.
For the full webinar replay, including the Q&A portion, click here.