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Implementing an in-memory data management environment: how to start, what to know

Lee Chew Tan, Vice President & General Manager, HP Servers, Enterprise Group, Hewlett-Packard Asia Pacific and Japan | Aug. 21, 2015
Here's how businesses can turn information into business advantage in real time.

This vendor-written piece has been edited by Executive Networks Media to eliminate product promotion, but readers should note it will likely favour the submitter's approach.

Most of us don't need to be reminded how much useful data there is for the taking. And most businesses also know that if they aren't using the data they collect in some kind of intelligent way, their companies will be out of business in a few short years. Quickly turning data into business insights is not just a nice-to-have option. It's now an essential element for increasing and retaining customers, as well as delivering new products and services.

Think about the online retailers that have those flash sales and replace items that have sold out with similar ones as shoppers are viewing the screen? They are able to track what is being sold in real time while providing the shopper with a better customer experience that lets them see what is actually available for purchase.

So why aren't more businesses able to turn information into business advantage in real time? Big data environments are extremely complex, and businesses are challenged with multiple instances, multiple tools, and legacy databases, all of which lead to complexity and cost, and make it hard to consistently get the data they need.

In-memory computing is rapidly changing the way businesses process information. It uses in-line memory instead of disks for storing data, which means fewer CPU instructions and quicker seek-times during the data query process on complex and often massive data sets. The result is much faster performance. What once took hours or days to process now takes minutes to seconds. Business leaders can make faster decisions based on real-time information and IT can quickly deliver analytics and insights without impacting their current day to day operations. Database managers spend less time moving and managing data and more time analysing it.

SAP HANA, for example, takes advantage of in-memory computing technology to enable real-time data access. It also provides a common platform across the entire SAP landscape within an enterprise to simplify how data is stored, managed and analysed. Your business can glean faster real-time insights from your SAP environment and make better business decisions.

While you would love to transform your IT this way, getting to faster data analytics, a more scalable data warehouse and the ability to migrate all business applications to one underlying database is more of a journey. More than likely your environments are crammed with legacy databases that are complicated and disconnected. And it takes more than in-memory data management software to achieve your business objectives.

It's critical that your infrastructure correctly match the in-memory data management software you select. That's why more IT executives and managers are making long-term, strategic architectural bets for their data centres and data management platforms. You need to develop the right strategy, delivery model and partnerships to minimise risk and disruption to datacenter operations during deployment as well as to scale as your data grows while maintaining high performance.


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