The Data Warehouse Revolution Is Coming

Tom Traubitz

Modernizing the data warehouse is no longer just a passing thought in most major enterprises, but is increasingly becoming the imperative. A centralized structure for all our data that took shape in the ’90s is increasingly appearing to be outdated and incomplete as the sole architecture for business analytics.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, 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 an 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 analyses ever more quickly. Business problems like fraud detection, real-time Web interactions, customer service, and customized consumer offers all become increasingly part of this to speed the decision-making process. For example, SAP customers already are reaping the fruits of this trend towards more powerful computing by combining core business applications and operations with in-memory computing. This enables real-time 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 with our applications and BI tools.

Sound like too much?

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.

Hyperconnectivity is here and it’s not going away. Learn more about Live Business: The Digitization of Everything.

This article originally appeared on Traubitz.com.


Tom Traubitz

About Tom Traubitz

Tom Traubitz is a Senior Director of Product Strategy with the Product and Innovations Group at SAP. He specializes in enterprise-class data warehousing and analytics. Tom has spent the past 25 years designing, engineering, testing, and marketing large scale, networked information management systems for a wealth of clients throughout the United States and the world.