In the era of big data, where systems are readily available and relatively inexpensive for capturing transactional and operational information, there is an all-too-prevalent belief that having the highest possible volume of data available for mining and analysis is the key to discovering hidden truths in customer or employee behavior. Unfortunately, the assumption that “more is better” leads only to significant data quality issues and having more of the wrong data or, at the very least, more of the wrong type of data for answering your critical questions.
It is well understood in business management circles that “What gets measured, gets managed.” Unfortunately, just having massive amounts of data to sift through doesn’t necessarily mean anything is being measured, nor does it mean that measurements can be created in order to make use of that data. Without appropriate data quality measures in place, whatever is collected might not yield the exact, specific data necessary. Instead, teams of analysts sift through the data, looking to find the closest possible variables that meet their needs, which could mean they aren’t using data that addresses current requirements at all. The outcome of this process? Inaccurate analyses yielding flawed decisions and all because the source data didn’t allow for greater precision. Even when the data is valuable, it may be hidden under mounds of irrelevant information and require excessive processing just to be rendered useful.
In order to overcome the chaos associated with irrelevant or inconsistent data, organizations need to establish a data quality program based on solid, proven data governance fundamentals. Data Clairvoyance has a team of experienced professionals who can overcome this chaos and develop your roadmap towards sustainable data management, establish fundamentally sound future-state architecture, and yield useful, insightful analytics that allow you to identify and capture emerging opportunities.
To begin developing data quality solutions that eliminate the noise and enable efficient data analysis, contact Data Clairvoyance for more information.