Dark Data

Missed Opportunities Hiding in Plain Sight

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Every company strives to make the best decisions possible and having all of the relevant data is a crucial element to achieve that goal. As our world moves increasingly to the cloud and becomes vastly more interconnected, the volume, variety and velocity of the data being generated creates a growing mountain of dark data that cannot be analyzed by traditional means.

What is Dark Data?

Dark data is defined as the data you’re storing, but not analyzing. Typically this data is being held for compliance reasons or security policies that sits around doing nothing but taking up space. It’s not data that fits easily into relational (e.g. MySQL) databases so traditional BI vendors cannot help you do anything with it. So it sits there, collecting metaphorical dust meanwhile you may be sitting on missed opportunities to save cost, find efficiencies or provide better customer service.

Why is Analyzing Dark Data Important?

If your company is making decisions based on partial, incomplete or inaccurate data, you’re putting your entire organization at risk. You need an analytics platform that was architected for today’s decision-making requirements. One that can ingest all types of data no matter what its structure or where it lives.

More than 70% of all business data is never used for analysis because most traditional analytics tools only work with structured data.

One that has the power and performance to give you the answers you need, when you need them. And one that can harness the power of AWS to take action and bring the insights to you using the latest in automation and machine learning. Including all of your data into your decision making is no longer optional, it’s essential.

With traditional analytics, nearly 80% of the time spent on projects is spent on labor-intensive (and often soul-crushing) data preparation. But with Qrvey, data prep and transformation can be streamlined and automated so you can focus on insights, not input.

The world has moved beyond structured data, isn’t it time your analytics moved beyond just visualizations?

Learn more about Qrvey’s data management capabilities for SaaS applications

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