Operational BI: The Evolution Of Business Intelligence - InformationWeek

InformationWeek is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

IoT
IoT
Software // Information Management

Operational BI: The Evolution Of Business Intelligence

A white paper released this week by The Data Warehousing Institute shows organizations slowly moving toward operational business intelligence. But the journey is sure to present a number business and technical challenges.

The concept of business intelligence is changing. Once the tools of only tech-savvy business analysts, BI is slowly evolving into a technology that merges analytics and operational processes into a unified whole.

But the road toward operational BI is sure to present a number of business and technical challenges, many of which are outlined in a white paper released this week by The Data Warehousing Institute.

TDWI believes operational BI is the "turning point" in the evolution of business intelligence, and defines it as the ability to deliver information and insights to a broad range of users within hours or minutes for the purpose of managing or optimizing operational or time-sensitive business processes.

That's a long ways from most BI deployments today. The majority of users continue to be business analysts and executives using sophisticated tools to improve the effectiveness of strategic or tactical decisions by analyzing trends and patterns in large volumes of historical data.

While BI will certainly continue to be used in that way, the full value of the technology won't be realized until it merges analytics and operational processes. But delivering BI to everyone from the shipping clerk to the chief executive has its challenges.

TDWI believes operational BI requires a rebuilding of current BI systems, so queries can be returned in seconds, not minutes or hours; reports can be updated dynamically, and the system can capture large amounts of data in near real-time without interfering with the operations of other software. In addition, as BI becomes more critical to operations, better backup and recovery systems need to be in place to prevent long periods of downtime during server outages.

Faced with such a large undertaking, it's no surprise that a lot of organizations are moving slowly toward operational BI. A TDWI survey of 423 corporate IT professionals, the majority of whom were mid-level managers in the U.S., found only a small percentage that claimed to have systems that were "fully" or "fairly" mature. "While a majority of organizations have implemented some form of operational BI, few have mature or sophisticated systems," TDWI said.

Indeed, the departments leading the way in some form of operational BI deployment are the same ones using more traditional BI tools. Those departments include finance, sales, service, and marketing.

For businesses taking BI to a new level, the biggest challenge, according to the TDWI survey, is architecting the system, followed by managing expectations of users, query performance, obtaining funding and working around technology limitations.

To reduce the number of problems, TDWI advises organizations to first define the requirements of the system to avoid building what's not needed. If users only need information that's updated twice a day, then there's no need to spend a lot more money for updates every minute.

In addition, if just-in-time data is needed, then organizations should rethink business processes to take full advantage of the capability. Other pieces of advice include setting reasonable expectations, so business users aren't surprised by results; and training users so they can reap all the benefits of faster data access.

On the technical side, organizations must decide whether to use a data warehouse, and select the right technology from three categories: data acquisition, data storage and data delivery. In addition, systems should be scalable, so they can later handle more users, connect to more data sources, and handle higher volumes of data with increased rates of throughput.

We welcome your comments on this topic on our social media channels, or [contact us directly] with questions about the site.
Comment  | 
Print  | 
More Insights
InformationWeek Is Getting an Upgrade!

Find out more about our plans to improve the look, functionality, and performance of the InformationWeek site in the coming months.

News
Becoming a Self-Taught Cybersecurity Pro
Jessica Davis, Senior Editor, Enterprise Apps,  6/9/2021
News
Ancestry's DevOps Strategy to Control Its CI/CD Pipeline
Joao-Pierre S. Ruth, Senior Writer,  6/4/2021
Slideshows
IT Leadership: 10 Ways to Unleash Enterprise Innovation
Lisa Morgan, Freelance Writer,  6/8/2021
White Papers
Register for InformationWeek Newsletters
Video
Current Issue
Planning Your Digital Transformation Roadmap
Download this report to learn about the latest technologies and best practices or ensuring a successful transition from outdated business transformation tactics.
Slideshows
Flash Poll