So much attention is being brought to new technologies like Business Intelligence tools and analytics platforms. This attention isn’t unwarranted. The potential for BI, analytics software, and even artificial intelligence is almost limitless and will likely change how companies do business for decades to come. The issue is, in the rush to adopt these incredible technologies, many companies neglect a crucial component to these technologies' effectiveness: data quality.
Data Quality’s Role in Business Intelligence
Business Intelligence tools and analytics software runs on the data provided to them. In this sense, these solutions are only as good as the data supplied to them by the data sets being utilized. If the combined data sets consist of old, incomplete, or inaccurate information, the BI and analytics programs will simply display and interpret poor bad data in a more visual way for users. It may look presentable, but poor data in a nice graph or bar chart is still just bad data masquerading as insight.
With this reality in mind, it isn’t going to far to say that an investment in BI or analytics software, without first addressing data quality needs, is a wasted investment.
How to Address Data Quality
Before basing crucial business decisions on your current databases, it’s imperative that you ensure the metrics you use to run your business are as accurate as possible. The best data quality solutions empower users to set their own data quality guidelines, write their own rules, prioritize issues, and take control of their data. After all, there is no one-size-fits-all solution to addressing data quality issues. The best tools, however, focus on making the data quality process as simple as possible to recognize issues before they end up ruining your BI tools and analytics software and negatively impacting your business decisions.
So, where can you get started on your data quality initiative? We can help. Sign up for a free, one-on-one demo that will speak to the challenges your organization is facing. You can also follow us on Facebook, Twitter, or LinkedIn to get more data quality news and updates on our data quality software.