2014 Technology Predictions Series: Pentaho on Big Data

As 2013 winds down, it’s only natural for people to make personal New Year’s resolutions for 2014. It’s also a perfect time for technology industry predictions.

This is the second installation in our multi-part “Technology Predictions for 2014″ series in which industry providers—from Big Data to cloud to mobile—share their predictions about the hot tech trends that will take center stage in 2014. We’ll be sharing all the predictions we’ve heard with you over the next several days.

Big Data in 2014

.

Big Data is a topic that we at siliconANGLE have been eyeing like hawks in 2013. From our written coverage of how AWS is reshaping the Big Data marketplace to theCUBE’s live coverage at events such as BigDataNYC 2013, we have been sharing with you the very latest developments in Big Data. So, what’s in store for Big Data in 2014?

Saggi Neumann, co-founder and CTO of Xplenty, a cloud-based, code-free, “Hadoop as a Service” platform, shared his four predictions for Big Data in 2014 in the first installation of our series.

In this second installation, we hear from Pentaho, a provider of open-source reporting, analysis, dashboard, data mining and workflow capabilities. Quentin Gallivan, CEO of Pentaho, made some predictions for Big Data in 2014 in his “Big Data 2014: Powering Up the Curve” blog post. With his permission, we share those predictions with you here.

Prediction No. 1: The Big Data “power curve” in 2014 will be shaped by business users’ demand for data blending. Customers like Andrew Robbins of Paytronix and Andrea Dommers-Nilgen of TravelTainment, who recently spoke about their Pentaho projects at events in NY and London, both come from the business side and are achieving specific goals for their companies by blending big and relational data.

Business users like these are getting inspired by the potential to tap into blended data to gain new insights from a 360 degree customer view, including the ability to analyze customer behavior patterns and predict the likelihood that customers will take advantage of targeted offers.

Prediction No. 2: Big Data needs to play well with others. Historically, Big Data projects have largely sat in the IT departments because of the technical skills needed, and the growing and bewildering array of technologies that can be combined to build reference architectures. Customers must choose from the various commercial and open-source technologies including Hadoop distributions, NoSQL databases, high-speed databases, analytics platforms, and many other tools and plug-ins. But they also need to consider existing infrastructure, including relational data and data warehouses and how they’ll fit into the picture.

The plus side of all this choice and diversity is that, after decades of tyranny and “lock-in” imposed by enterprise software vendors, in 2014 even greater buying power will shift to customers. But there are also challenges. It can be cumbersome to manage this heterogeneous data environment involved with Big Data analytics. It also means that IT will be looking for Big Data tools to help deploy and manage these complex emerging reference architectures and to simplify them. It will be incumbent on the Big Data technology vendors to play well with each other and work towards compatibility. After all, it’s the ability to access and manage information from multiple sources that will add value to Big Data analytics.

 

RELATED:  Is hyperconverged worth it for your business? | #NEXTConf

 

 

 

 

 

 

 

 

 

 

Prediction No. 3: You will see even more rapid innovation from the Big Data open source community. New open-source projects like Hadoop 2.0 and YARN, as the next-generation Hadoop resource manager, will make the Hadoop infrastructure more interactive. New open-source projects like STORM, a streaming communications protocol, will enable more real-time, on-demand blending of information in the Big Data ecosystem.

Since we announced the industry’s first native Hadoop connectors in 2010, we’ve been on a mission to make the transition to Big Data architectures easier and less risky in the context of this expanding ecosystem. In 2013, we made some massive breakthroughs towards this, starting with our most fundamental resource, the adaptive big data layer. This enables IT departments to feel smarter, safer and more confident about their reference architectures, and open up Big Data solutions to people in the business—whether they be data scientists, data analysts, marketing operations analysts or line of business managers.

Prediction No. 4: You can’t prepare for tomorrow with yesterday’s tools. We’re continuing to refine our platform to support the future of analytics. In 2014, we’ll release new functionality, upgrades and plug-ins to make it even easier and faster to move, blend and analyze relational and Big Data sources. We’re planning to improve the capabilities of the adaptive data layer and make it more secure and easy for customers to manage data flow.

On the analytics side, we’re working to simplify data discovery on the fly for all business users, and make it easier to find patterns and catch anomalies. In Pentaho Labs, we’ll continue to work with early adopters to cook up new technologies to bring things like predictive, machine data and real-time analytics into mainstream production. As people in the business continue to see what’s possible with blended Big Data, I believe we’re going to witness some really exciting breakthroughs and results.

 

RELATED:  Handling the heavy data flow with custom teams | #HPEdiscover

Click here for the first installation of our “Technology Predictions for 2014″ series, in which we heard Big Data predictions from Xplenty.

Click here for the third installation, in which we heard Big Data predictions from Alpine Data Labs.

Click here for the fourth installation, in which we heard Big Data predictions from MapR Technologies.

Click here for the fifth installation, in which we heard Big Data predictions from Think Big Analytics.

Click here for the sixth installation, in which we heard Big Data predictions from SGI.

Click here for the seventh installation, in which we heard Mobile predictions from SAP.

Click here for the eight installation, in which we heard Mobile predictions from RadiumOne.

Click here for the ninth installation, in which we heard Cloud predictions from NetApp.

Click here for the tenth and final installation, in which we heard Cloud predictions from F5.

Suzanne Kattau

Suzanne Kattau (formerly Suzanne Harnos) is Editor at SiliconANGLE where she focuses on cloud technology, consumer news and trends. She is a veteran computer journalist based in New York. Previously, Suzanne was an associate editor at BZ Media’s Software Development Times. Before that, she was an online editor at Ziff Davis Enterprise’s eWEEK and technical editor at CMP Media’s InternetWeek. She graduated from Hofstra University with a Bachelor’s degree in English.

SIGN UP FOR THE SiliconANGLE NEWSLETTER!

Join our mailing list to receive the latest news and updates from our team.

SIGN UP FOR THE SiliconANGLE NEWSLETTER!

Join our mailing list to receive the latest news and updates from our team.
Share This

Share This

Share this post with your friends!