You can’t measure what you can’t see. If you consider this in terms of data, you also can’t analyze, curate, or leverage data blind spots to help create actionable insight.
For many business technologists and business intelligence professionals, blind spots and data gaps create functional frustration and make it harder for teams to deliver data-driven value back to the business. But what does this mean in practice? How does lacking visibility impact line-of-business objectives, and what can businesses do to get information operations back on track?
The Current State of Sight
Recent survey data makes it clear: Data visibility is a problem for organizations. Fifty-two percent of data professionals pointed to lack of visibility across the IT environment as their top challenge—lack of proactive alerts was a distant second at 37%.
It makes sense: While seeing data end-to-end is relatively easy when data warehouses and storage repositories are under one roof. Blind spots most often occur with the addition of multiple cloud storage instances, geographically disparate backup solutions, shadow SaaS applications, and the increasing use of the Internet of Things (IoT) devices to track, manage, and monitor business operations.
Put simply, teams have more data to work with—but significantly less visibility.
The Problems of Data in the Dark
Data in the dark comes with several challenges for data professionals, including:
Context matters when it comes to making data-driven decisions. Suppose teams don’t have access to all available data. In that case, they could miss key indicators that could help pinpoint more effective actions. Context also helps ensure that decisions are not made using information that’s out-of-date and no longer relevant.
As noted by Tech Target, one of the biggest challenges with big data is finding and fixing data integrity and quality issues. Add in a lack of visibility, and this challenge can quickly become a significant problem: Data you can’t see may mean bad data is contaminating good data and skewing the ability of businesses to make the right decisions.
Data warehouses, backup facilities, and analytics solutions naturally scale as businesses grow. But without clear sightlines into where data is stored, how much data you have, and how much room you need, it’s easy to over- or under-spend on data scaling investments. Both cases are problematic: Spend too much, and you’re paying for wasted space. Spend too little, and you could face significant performance problems as resources are taxed to the limit.
The Potential of 20/20 Vision
With better insight into where data is located, what it’s being used for, and how it relates to business objectives, companies are better prepared to conduct real-time analytics that drive strategic decision-making.
Consider the use of customer data. In isolation, customer data points have some value but limited scope. For example, historical transaction data points to a pattern of purchasing; however, when combined with information about customer service calls, social media engagement, and website visits, companies can create a complete picture of the consumer journey. This “customer 360” view makes it possible to pinpoint areas for improved service delivery or experience personalization that can help reduce customer churn or expose additional revenue opportunities.
But achieving 20/20 vision doesn’t happen overnight. Along with clear goals for data, such as increasing customer spend or improving consumer satisfaction, businesses need tools capable of shining a light on disparate data sources. These include everything from hybrid cloud data warehouses to edge data management solutions and enterprise data integration platforms—anything that shortens the distance between data and action and makes it possible to close current data gaps.
Data blind spots lower data-driven business value. See what matters with solutions that empower end-to-end visibility.