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Zoomdata 2016 Prediction: Big Data "Analytics Anywhere" in 2016

Virtualization and Cloud executives share their predictions for 2016.  Read them in this 8th Annual VMblog.com series exclusive.

Contributed by Justin Langseth, CEO and Founder of Zoomdata

Zoomdata Sees Big Data "Analytics Anywhere" in 2016

If a web site isn't properly indexed and discoverable on Google, it's like it doesn't even exist today. In 2016, we'll see enterprises render similar judgment against their data. Data will be used heavily when it is available in modern architectures and easy for any business user to access. Data will wither that is trapped in walled gardens or challenging for business users to tap. It sounds simple, but as we approach 2016, the real business value of analytics on top of enterprise data is closer to being unlocked than in any period in history.

I see three major trends emerging in 2016:

1. AWS QuickSight Raises Table Stakes for BI / Analytics Capabilities

At Re:Invent, with the release of QuickSight, Amazon released a fast, easy and inexpensive (1/10th the cost of Cognos) platform for any business user to query and visualize data stored in the AWS cloud. The announcement directly threatens the fat margins and future viability of traditional BI and analytics vendors. It's clear that 2016 is going to see a major shake up in how enterprises interact with data, and who wins and loses with these new expectations.

The enterprise buyer's evaluation across BI and analytics solutions historically forced unnatural choices. The real-time reporting solutions couldn't handle legacy data. SaaS BI tools required you to move all your data to the cloud. Legacy BI tool built for desktop couldn't handle big data volumes. The big data analytics products required a redundant investment in datacenter server clusters and operated with all the transparency of a black box. Each choice has its tradeoff. None delivered on the promise of tapping into all of your data from one plane. That capability would give organizations a return on their data visualization and analytics investments an order of magnitude greater than what's possible today.

In 2016 -- on the basis of what's now so cheaply available on Amazon -- I believe it's going to be table stakes for BI and analytics vendors to: (1) be deployable in the cloud or on premises; (2) be able to handle streaming data AND historical data; (3) be easy to use for any business user.

2. Streaming Architectures Go Mainstream

Traditional, batch-oriented data warehouses pulled data from multiple sources at regular periods, bringing it to a central location and assembling it for analysis. With streaming architectures--driven largely by the widespread adoption of technologies like Apache Spark, Kafka, and Storm--queries are pushed to the data source and run locally. This makes computations faster, and removes the need to move enormous chunks of data over the network to process remotely.

What this means for data analytics is no more batching data and wrangling it through ETL, data harmonization, and other old-fashioned techniques.

In 2016 enterprises will accelerate the move from batch to streaming with analytics that are also closer to real-time, and far less computationally expensive. We'll see more emphasis on "time to visualization" (the time from when a user asks a question to when the user is seeing / interacting with results). And sub-second response time on queries even on billions of rows of data (previously unheard of) will also become table stakes for solutions in the category.

3. Analytics, No Longer Just Something You "Log In" To

In 2016, I believe we're going to see BI and analytics evolve to an operational requirement, horizontal across business functions--and less of "something you log into."

Enterprises want to make the recommendation analytics part of shopping apps. They want the monitoring and exception analytics to be part of the Network Operating Center apps.

Analytics are becoming context-driven, embeddable services that inform critical business decisions, and are pushed to individual users to explore. In 2016 we will see analytics becoming multi-tenant services, embeddable and extensible for interaction with data in sub-second times.

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About the Author

Justin Langseth is CEO of Zoomdata.

Zoomdata is Justin's 5th startup -- he previously founded Strategy.com, Claraview, Clarabridge, and Augaroo. Justin is an expert in big data, business intelligence, text analytics, sentiment analytics, and real-time data processing. He graduated from MIT with a degree in Management of Information Technology, and holds 14 patents. Zoomdata has raised $22 million in venture funding from Accel, NEA and others.

Published Thursday, November 05, 2015 6:32 AM by David Marshall
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