By Rahul Agarwal,
Data warehousing ‘origins’
Data warehousing was conceptualized in the late 1980’s by IBM researchers to address the problems associated with the flow of data from transactional systems to decision support systems. Since then it has become an important asset for businesses worldwide as it supports analysis, reporting and other business intelligence functions by providing a single, comprehensive source of current and historical information.
RIP, Data warehouse?
With the advent of big data, the importance of the traditional data warehouse is in no way diminished; in fact, increasingly it is being recognized as a foundational building block for an effective big data and analytics strategy. The modern data warehouse can be thought of as an engine for analytics turning data into information and insight.
The current state of data warehousing technology
The first generation of data warehouses were built on Relational Database Management Systems (RDBMS). This generation was limited by its ability to handle heavy I/O demanded from users accessing large data volumes. However, today businesses want that their analytic databases generate insight from data more quickly than ever before. A number of new technologies have emerged to overcome this and other weaknesses including in-memory database technology and Netezza analytic appliance technology.
Another issue faced by companies is the reliance on business analysts/data scientists to manage the complexities associated with data acquisition, cleansing and dissemination. However, companies are facing a large supply gap of data analytics talent. This might result in analysis being late in coming or not coming at all and business users taking decisions without it. This is where technologies like IBM Watson come into play.
More “Insight” into the present and future of analytic databases
The analytic database space is undergoing tremendous change. You can join IBM’s leading technology executives in a panel discussion about analytics databases and present and future trends at Insight 2014. This panel of distinguished engineers includes Sam Lightstone, Matt Huras, Bernie Schiefer, Michael Sporer and Robin Grosset. More details about the session can found here.
About Rahul Agarwal
Rahul Agarwal is a member of the worldwide product marketing team at IBM that focuses on data warehouse and database technology. Rahul has held a variety of business management, product marketing, and other roles in other companies including HCL Technologies and HP before joining IBM. Rahul studied at the Indian Institute of Management, Kozhikode and holds a bachelor of engineering (electronics) degree from the University of Pune, India. Rahul’s Twitter handle : @rahulag80