How data contextualization can close the gap between analytics and decisions

Most companies have turned to data to guide and inform critical decision making. And while most organizations have all the data they need (and then some) there is still a large gap between collecting data and using it for decision making. For businesses to stay competitive and keep up with the ever-changing digital landscape, they must embrace the future of business intelligence and find the right tools to bridge that gap.

The Current Problem

Gartner predicts that total analytics use will increase from 35% to 50% by 2023. However, in a study by McKinsey & Co. they found that only approximately a third of decisions were both timely and of good quality. To make the most of the vast amounts of data being collected, businesses must make more decisions based on data and be confident that they’re using good data to reach the desired results.

Unfortunately, many businesses struggle to make sound decisions based on their data due to a lack of time, energy, and resources to do so. The data that is being collected today is exponentially larger and more complex than ever before, and many analytics tools have not kept up. As a result, many organizations rely on humans to do the lion’s share of collection, analysis, and contextualization of their data. This can result in errors, inaccurate data, and a huge lag in getting projects completed. And that time lag could result in a project ultimately being useless or slow, inaccurate decision making. That could have negative consequences, from a decline in sales to ineffective marketing strategies, and more.

The Solution

What businesses need are new tools that can augment and support their human resources to achieve quick and actionable decision making – a platform that allows them to see the big picture in one place. 

The key to bridging the gap between data collection and meaningful insights is data contextualization – a way to make sense of what vast volumes of data are saying. At its simplest, data contextualization means adding related information to any data to make it more actionable. Doing so allows trends, patterns, and correlations to stand out against a background of context, getting you a lot more value from your data. 

Oftentimes, complicated dashboards and other tools pull data from multiple, disparate sources and the end results require a data scientist (or a whole team) to explain it in meetings, calls, and emails. This can lead to that dreaded time lag as more time is spent explaining data than acting on it. However, data contextualization combined with the simplicity of using one platform, can eliminate the need for hours of human explanation and clear a path for automated, easy to understand insights. Data contextualization can also help teams save time, money, and effort as a team of data scientists is not required to understand the results and it makes complex data relationships easy to understand. 


Gone are the days of stakeholders making decisions based on intuition, historical frameworks, or guesswork. The future of decision making is now, and it’s data-driven. But businesses have to be sure they’re making the leap from data analysis to actionable insights, and doing so with accuracy. Organizations must take on new tools, such as data contextualization platforms to cut down on lags and human error. At a time when decisions need to be made faster than ever, businesses can’t afford to miss out on what their data is telling them. 

If your team is looking to close the gap between analysis and action, reach out to Gemini Data today. We’ve eliminated the complexity of data operation down to a single platform that supports it all, and gives you the data when you need it, at the time you need it. With our platform, you can effectively reduce the cost of data ownership and get your insights quickly and easily.

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