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Why Embedded Analytics 2.0 Will Change the BI Market

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Why Embedded Analytics 2.0 Will Change the BI Market

As data analytics proliferates, it grows more and more complex. This is driving embedded analytics 2.0 and leaving standard analytics solutions in the dust.

· Big Data Zone
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Data analytics has transformed the way we do business.

Today, business users at all levels look to data to drive decision-making. And they need analytics tools that not only connect and process complex data but also translate that information into useful and understandable insights.

Welcome to the brave new world of embedded analytics 2.0.

Gone are the days when analytics required a data specialist to prepare data, run queries, and translate findings for business users. Today, embedded analytics 2.0 pairs a customer’s need for self-service analytics with a vendor’s need for a fully customizable, API-first, embeddable solution.

The problem? Most analytics solutions aren’t keeping pace.

Evolution of the Embedded Analytics Market

As Aberdeen Group puts it:

“With so many of today’s critical applications migrating to a cloud or hybrid environment, and many of these applications utilized largely on mobile devices, providers supporting embedded BI have their work cut out for them.”

You not only have to create better BI but you also need to be able to fit that BI into an ever-changing IT environment so your users can work seamlessly. It may seem like a challenge but don’t worry. Among other benefits, leaders in embedded analytics are 66% more likely to see an increase in organic revenue and 2.2x more likely to drive an increase in average deal size.

What’s Driving Embedded Analytics 2.0?

The ability to capture and interpret raw business data has turned the invisible visible.

Now that companies can identify trends, better allocate resources, understand customer behavior more deeply, and even predict what happens next, data analytics has grown increasingly important.

But as data analytics proliferates, it grows more and more complex. And this is driving embedded analytics 2.0 (and leaving standard analytics solutions in the dust) for two reasons.

First, the widespread use of analytics means it’s no longer the domain of data scientists or analysts. Where analytics was once translated for business users by data specialists, today users with little or no analytics background need to access and interpret data.

Second, businesses are looking for more (and better) ways to extract fresh insights and answer more complicated, important, and wide-ranging business questions. This often entails connecting multiple data sources and processing more sophisticated queries.

These two trends net out with one result: business users need analytics solutions that transform more complex data into easy-to-interpret results.

Standard Analytics Solutions vs. Embedded Analytics 2.0

So, why are standard analytics solutions getting left behind?

In the early days, data analysts and data scientists were at the helm of analytics, acting as middlemen for business users with no analytics background.

Because data analytics has transformed the business landscape so quickly, many standard analytics solutions remain designed for a specialized analytics user. They pull data from a few sources and crank out queries dependent on an extensive (and expensive) IT infrastructure, then produce somewhat obscure results using predetermined formulas that leave users scratching their heads.

Today, businesses users of all levels need self-service analytics — tools that help them connect complex data, run queries quickly on standard hardware and mobile devices, and generate actionable insights.

Compared to standard analytics solutions, embedded analytics 2.0 streamlines data analysis using commodity hardware. It’s flexible, scalable, and easy for users to ask — and answer — more sophisticated business questions.

But customers aren’t the only stakeholders demanding a new breed of analytics.

Vendors need analytics solutions specifically designed to be embeddable. Wasting time on solutions that treat embeddability as an afterthought puts schedules, budgets, and competitive advantage at risk.

The faster vendors can go to market with embeddable self-service analytics tools, the bigger advantage they’ll have.

For vendors, embedded analytics 2.0 solutions are consummately customizable. They deliver the benefits of a proprietary analytics solution without the headaches or resource sink. Vendors get a market-leading analytics tool that provides a competitive advantage without dragging down development or postponing a launch.

Embedded analytics 2.0 is a win for customers and a win for vendors. And that’s what true business transformation is all about.

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Topics:
business intelligence ,embedded analytics ,data analytics ,big data

Published at DZone with permission of Shelby Blitz, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

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