Big data is without a doubt 1 of the top 5 BI trends of 2012. The hype around big data has driven many companies to hoard massive amounts of structured and unstructured information in the hope of unearthing useful insight that will help them gain competitive advantage. Admittedly, there is significant value to be extracted from your company’s growing vault of data; however it is data quality – not necessarily quantity – that is your company’s biggest asset. So here are 3 reasons why you should devote more of your IT budget to data quality:
1) Because good data quality sets the stage for sound business decisions.
Sensible business decisions should be based on accurate, timely information coupled with the necessary analysis. Decision-makers need to be equipped with facts in order to plan strategically and stay ahead of the competition – and facts are entirely based on having correct data. Though it’s not as “sexy” as big data, mobile BI, or cloud, data quality should be the foundation of all of these other initiatives.
Admittedly, achieving data quality is tough. Gartner analyst Bill Hostmann says, “Regardless of big data, old data, new data, little data, probably the biggest challenge in BI is data quality.” It crosses department lines (both IT and business users must take responsibility), and processes that have multiple levels of responsibility often suffer from the “everyone and no one is responsible” conundrum. It’s also a complex process that requires laying out common definitions (what is a customer, what are our conventions for company names – Inc. or no Inc. – for example), performing an initial data cleanse, and then keeping things tidy through ongoing data monitoring, ETL, and other technologies.
But ensuring that your data is timely, accurate, consistent, and complete means users will trust the data, and ultimately, that’s the goal of the entire exercise if you see this first reason as the most important. Trusting the data means being able to trust the decisions that are based on the data. Clean up the data you have in place, then you can move on to a strategy that incorporates additional sources of big data.
2) Because you have to.