Actian Blog / Insight to Insights

Insight to Insights

INsights

A fellow recent hire at Actian, Walter Maguire, told me that many organizations get frustrated with having to wait into the late morning for decision support databases to be loaded and indexed or OLAP cubes to be populated with transactional data before sales analysis can be performed. This is not a new problem. I remember when I worked for British Telecom, our biggest worry was to complete the overnight batch updates to our mainframe CA-IDMS database, so we could start the IBM CICS transaction processing service, allowing employees to accept bill payments and check balances.

In the retail business, knowing how products are selling is critical. In the days before in-store POS systems sent daily updates to HQ, I worked at Coppernob, who owned 126 Top Shop stores. Every Saturday night, couriers collected Kimble tags containing bar-codes that we scanned on Sunday to create reports showing sales across the UK. The Ingres database would index the sales tables to work out what designs where hot that week.

Today, fashion retailers such as Kiabi use Actian Vector to analyze sales data, applying predictive analytics on markdowns to improve marketing campaigns. Now they can track marketing offers to select the most productive markdowns. Kiabi use Actian Vector to speed up the time it takes to gain insights. The chart below shows the performance difference they saw when comparing using their Oracle RDMS directly versus using Vector:

Kiabi’s performance test of Actian Vector query acceleration compared to standard Oracle

Having the ability to bypass the bulk update and indexing process gives organizations more time to gain more insights. You can view the full Kiabi case study here.

About Pradeep Bhanot

Product Marketing professional, Author, Father and Photographer. Lives in California and Berkshire. Indian. Born in Kenya. Lived in England through disco, punk and new romance eras. Worked with Oracle DB2 databases at Oracle, British Telecom and Watson Wyatt. VSAM at CA Technologies and Serena. SQL Server at 1E and BDNA.