Accelerate your operational analytics
Operational analytics are critical to business success. Whatever back-end system powers them (online transaction processing database, data warehouse, data mart and so on) operational analytics can deliver the insights that drive real time decisions in today’s dynamic business environments.
Typically, operational analytics involve interactive database queries. For example, you might use operational analytics to look up information about specific customers, accounts or, if you’re a healthcare professional, patients. This information, contextualized within graphs, charts, dashboards and other operational visualizations, can help your business better engage with customers. Likewise, similar fast database queries and guided analytics can deliver real-time operational insights into financial, human resources, inventory management and other operational decisions.
To rapidly deliver the right information to drive the right decisions, you must have an operational database platform that has been optimized for high-performance analytics and query throughput. At the same time, the platform should be simple to install, configure and administer, thereby reducing the burden on IT staff.
IBM has significantly refreshed the PureData System for Operational Analytics (PDOA) solution to support the most demanding requirements. PDOA is built on IBM Power Systems servers with IBM System Storage and is powered by IBM DB2 software with row-based data partitioning. This latest refresh offers:
- Accelerated performance with the help of new, more powerful servers that leverage POWER8 technology and improved tiered storage. The tiered storage uses IBM FlashSystem storage for the "hot" or frequently accessed data and spinning disks for "cool" data.
- Enhanced scalability that allows the system to grow to peta-scale capacity. In addition, nodes of the refreshed system can be added to previous generations of PureData System for Operational Analytics, thus providing better technology investment protection.
- Reduced data center footprint as a result of increased hardware density.