We have spent a decade or more hearing endless accolades about the benefits of analytics. What a lot of those articles left out is that analytics isn’t easy. It has immense potential for companies that are great at working with data. Unfortunately, that’s not a lot of companies.

These struggles are obvious in the statistics. Bad data alone costs the US more than $3 trillion, suggesting that data is both an asset and an obstacle. Or it can be ignored – up to 73 percent of the data that companies own is not used for analytics. Given those issues, it’s not surprising that around 70 percent of companies aren’t getting the value they expected from data.

This problem is more than annoying, it’s serious. Companies invest heavily in data initiatives. They depend on them just as heavily to guide decision making large and small. An ineffective data strategy is a lost opportunity and, potentially, a serious liability. Instead of writing your own approach off, take these simple steps to streamline data analytics.

Think of Data Collectively

The scope of big data is one of the biggest challenges. Resist the temptation to break data down into smaller sets. It may make things more manageable, but it also makes your insights incomplete and inaccurate. Working with all of your data at once does not have to be a stumbling block. You simply need an analytics tool that makes the integration and discovery process easy.

Train Your Focus

Once you have all your data in once place you can focus on specific aspects without worrying that something is being omitted or overlooked. One of the things that cripples data initiatives is being too broad. Companies don’t have specific questions they want answered, and, consequently, don’t really know what to do with the data. Start by determining what you need and want to know. Then rely on an analytics solution that allows you to query the data directly instead of searching inside it aimlessly.

Double Check Everything

Data analytics is excellent at identifying trends and patterns, but it’s up to you to interpret them. Before rushing to any judgments, double check your insights. For instance, if you notice that costs are going up on a one product, find out if they’re rising on other products too. Just because data analytics is seamless does not mean it has to be reckless. A good analytics tool should make cross-referencing easy.

Embed Your Solution

It doesn’t matter if you have the best analytics solution in the world: If it’s hard to access, users will avoid it. The same is true if the solution is confusing, or complex. Companies select between users ignoring a business tool or else using it improperly, neither of which are positive. Embedded analytics from ThoughtSpot works inside existing applications and workflows. Data becomes a tool that is accessible to all literally on demand.

Rely on Visualizations

Data is rather dry on its own. The fact and figures could all be perfect, but if they exist just as columns of numbers, they don’t make much impact. Visualizations are an easy way to turn analytics into actionable ideas and clear takeaways. Information expressed visually is easy to digest and easy to remember. It also condenses a lot of data into one straightforward presentation.

You can spend a lot of time and grief trying to diagnosis what is wrong with an analytics initiative. It could be a lot of things, but, realistically, it’s most likely your analytics solution. Technology is the portal between you and your data. It can either help you collect, organize, manage, and analyze all your information. Or it can do just the opposite. If you’re looking for solutions, start with the most obvious problems.


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