Various research efforts and customer conversations clearly indicate that the data exploration and data preparation stage of the analytic lifecycle is complex and time consuming. Scarce data scientist or data analyst resources are spending the majority of their time on data preparation tasks vs. spending their time on deriving insight that can drive the business. One aspect of addressing this challenge is to ensure that the data management processes that are used to support advanced analytics are optimized for performance and scalability. This topic will become more important as organizations tackle big data – not only big data volume, but also the variety of data sources such as social media sources.
We have sponsored a monograph report with David Stodder, from TDWI, to explore this topic in more depth. The report, Seven Keys to High Performance Data Management for Advanced Analytics, will soon be available and a webinar will be held on Wednesday, December 15th at 12 PM EST / 9 AM PST to preview the paper.
Dave will examine seven key technology trends in high performance computing that are changing the landscape for advanced analytics and enabling organizations to solve pressing data management challenges they are facing with traditional ETL and data warehousing systems.
The webinar will cover:
- Seven steps you can take to leverage high-performance computing for advanced analytics
- How in-database processing and ELT can increase the speed and manageability of analytics
- Why in-memory processing is important for complex analytical query performance and how you can avoid potential problems with this approach
- How workload management can help you gain the benefits of grid and parallel computing for advanced analytics
To register, click here.
Check back here for the link to the published report.
