Business Intelligence (BI) is a broad domain and is used to
accomplish a variety of goals. Whether we’re talking about predictive analytics
or lagging KPIs, the common thread is data visualization that drives effective
The trick is recognizing the difference between a report that has a large quantity of data versus one that has the right information.
Before attempting any clean up, analyze and quantify the quality issues that you are trying to address. For example, are there any fields that are null but should have a value? Are data types enforced (only numbers in an “integer” type field, etc.)? Are values within an expected range? Is there conflicting information?
But, before jumping to fix your data issues, it’s important to establish a framework that ensures the data will be usable in the long run—not only immediately after a big cleanse, which is often time consuming and expensive. This 5-part framework provides a comprehensive approach for addressing existing data quality issues, and prevent issues from arising in the future.
It goes without saying that data is critical to make strategic decisions, to run operations, and to perform business functions.
Healthcare companies derive analytics from clinical and claims data to meet quality measures, improve care, and better manage high-cost and high-risk populations.
Manufacturing companies rely on performance data to improve efficiency, increase yields, and lower costs.
Retailers rely on data to predict trends, forecast demand, and optimize pricing.
Financial services organizations perform advanced data analytics to drive revenue and margins through operational efficiency, risk management, and improved customer intimacy.
All of these scenarios require vast amounts of data. Regardless of industry or company size, nearly every business is relying on gathering and leveraging data. Being a data-driven organization is an absolute necessity to gain a competitive advantage.
IT is uniquely positioned to have access to a comprehensive set of data which is stored on or passes through the company’s infrastructure. IT, therefore, carries a responsibility to provide end users access to this data, and to play a vital role in its effective use.
You’ve heard the phrase, “If it ain’t broke, don’t fix it.”
There are many areas in business where that advice may hold true, but your IT assets are not one of them.
IT assets—including hardware, software and data—start deteriorating the day they are acquired. Yet the tendency today is to purchase, install, and then promptly forget about a technology. Few people or companies realize that when it comes to IT assets, maintaining status quo carries great risks.
There is ample evidence that, in general, “software customizations are bad.” (So much so you might have nightmares where software customizations are vampires, haunting you, refusing to die in peace.)
But consider the other side of the coin: the risk of an organization going along with canned software functionality. This can downgrade an organization’s business practices to “average,” causing them to lose out on opportunities to improve performance.