Modernizing the data warehouse is no longer just a passing thought in most major enterprises, but is increasingly become the imperative. A centralized structure for all our data that took shape in the 90’s is increasingly appearing to be outdated and incomplete as the sole architecture for business analytics.
Why is this?
Three trends are working strongly against the centralized, single-database approach to the data warehouse. First, is business is becoming increasingly transacted through web and digital interfaces. Just as the ATM displaced human interactions for banking transactions, now business are interacting with the customers, employees, partners, and even machines through digital interaction. And that interaction is creating a wealth of data, if we can leverage it.
Second, but strongly correlated with the first is the proliferation of data sources and the amount of data with which business professionals want and need to engage. It is becoming increasingly difficult or impractical to move such vast amounts of data. In some cases, it might even make sense that the data be treated as impermanent stream of time-sensitive content. The practicality of dealing with big data and its consequences begs for new solutions over centralized of reservoirs of storage.
The third trend is continuation of increasing pace of digital transactions. The demand is always to conduct business more quickly and efficiently. This pressure, usually spawned by competition places increasing strain to make decisions and analysis ever more quickly. Business problems like fraud detection, real-time web interactions, customer service, and customized consumer offers all become increasingly part of this his speed decision making process.
SAP customers already are reaping the fruits of this trend towards more powerful computing. Leveraging power of SAP HANA, SAP’s business suite S/4HANA powerfully combines core business applications and operations with in-memory computing. This enables real-time operations. By extending this idea to warehouse, real-time business operations.
What is needed is a new approach to the data warehouse. We need an approach that combines the power of an in-memory data engine with access across a range of data sources and stores. A new system for managing the data warehouse would need to understand multiple temperatures of data (that is, how important and urgent data is) as well as be able to work with vast distributed technologies such as Hadoop. Of course such an engine would need to understand streams and other forms of temporal data. And most importantly, we would need a warehouse that with our applications and BI tools.
Sound like too much?
Well, at SAP we’ve been revolutionizing the platform for data analysis. We invite you to find out more about a data warehouse system that can do all this and more: a revolution in data warehouse management is coming this September.
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This content was originally posted on the
Traubitz blog.
