In-memory analytics: Strategies for real-time CRM

Published: November 23, 2010

Executive summary

For years, the process of devising customer data queries and creating business intelligence reports has been a lengthy one. That’s because the information needed must be pulled from operational systems and then structured in separate analytical data warehouse systems that can accept the queries. Now, however, we are on the brink of true “inmemory analytics,” a technology that will allow operational data to be held in a single database that can handle all the day-to-day customer transactions and updates as well as analytical requests — in virtually real time.

The advantages of in-memory analytics are many: Performance gains will allow business users to retrieve better queries and create more complex models, allowing them to experiment more fully with the data in creating sales and marketing campaigns, and to retrieve current customer information, even while on the road, through mobile applications. The resulting boost in customer insights will give those who move first to these systems a real competitive advantage. Companies whose operations depend on frequent data updates will be able to run more efficiently. And by merging operational and analytical systems, with their attendant hardware and software, companies can cut the total cost of ownership of their customer data efforts significantly.

To drive the shift to this new technology, CIOs must make sure the business understands its advantages in terms of better customer intelligence and lower overall cost. To do so, they must make a strong business case for the transformation — always a challenge with business intelligence systems — including ease of use, better analytical reports, and better decision making. And they must devise a governance strategy to manage the technology’s rollout and monitor its use.

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In-memory analytics: Strategies for real-time CRM