7 Data Predictions for 2017

As data increasingly becomes the means by which businesses compete, companies are restructuring operations to build systems and processes liberating data access, integration and analysis up and down the value chain. Effective data management has become so important that the position of Chief Data Officer is projected to become a standard senior board level role by 2020, with 92 percent of CIOs stating that a CDO is the best person to determine data strategy.

With this in mind as you evaluate your data strategy for 2017, here are seven predictions to contemplate to build a solid framework for data management and optimization.

  1.  Self-Service Data Integration Will Take Off
    Eschewing the IT bottleneck designation and committed to being a strategic partner to the business, IT is transforming its mindset. Rather than be providers of data, IT will enable users to achieve data optimization on a self-service basis. IT will increasingly decentralize app and data integration – via distributed Centers of Excellence based on shared infrastructure, frameworks and best practices – thereby enabling line-of-business heads to gather, integrate and analyze data themselves to discern and quickly act upon insightful trends and patterns of import to their roles and responsibilities. Rather than fish for your data, IT will teach you how to bait the hook. The payoff for IT: satisfying business user demand for fast and easy integrations and accelerated time to value; preserving data integrity, security and governance on a common infrastructure across the enterprise; and freeing up finite IT resources to focus on other strategic initiatives.
  1. Big Data Moves to the Cloud
    As the year takes shape, expect more enterprises to migrate storage and analysis of their big data from traditional on-premise data stores and warehouses to the cloud. For the better part of the last decade, Hadoop’s distributed computing and processing power has made it the standard open source platform for big data infrastructures. But Hadoop is far from perfect. Common user gripes include complexity and instability – not all that surprising given all the software developers regularly contributing their improvements to the platform. Cloud environments are more stable, flexible, elastic and better-suited to handling big data, hence the predicted migration.
  1. Spark Usage Outside of Hadoop Will Surge
    This is the year we will also see more Spark use cases outside of Hadoop environments. While Hadoop limps along, Spark is picking up the pace. Hadoop is still more likely to be used in testing rather than production environments. But users are finding Spark to be more flexible, adaptable and better suited for certain workloads – machine learning and real-time streaming analytics, as examples. Once relegated to Hadoop sidekick, Spark will break free and stand on its own two feet this year. I’m not alone in asking the question: Hadoop needs Spark but does Spark need Hadoop?
  1. A Big Fish Acquires a Hadoop Distro Vendor?
    Hadoop distribution vendors like Cloudera and Hortonworks paved the way with promising technology and game-changing innovation. But this past year saw growing frustration among customers lamenting increased complexity, instability and, ultimately, too many failed projects that never left the labs. As Hadoop distro vendors work through some growing pains (not to mention limited funds), could it be that a bigger, deeper-pocketed established player – say Teradata, Oracle, Microsoft or IBM – might swoop in to buy their sought after technology and marry it with a more mature organization? I’m not counting it out.
  1. AI and ML Get a Bit More Mainstream
    Off the shelf AI (artificial intelligence) and ML (machine learning) platforms are loved for their simplicity, low barrier to entry and low cost. In 2017, off the shelf AI and ML libraries from Microsoft, Google, Amazon and other vendors will be embedded in enterprise solutions, including mobile varieties. Tasks that have until now been manual and time-consuming will become automated and accelerated, extending into the world of data integration.

6. Yes, IoT is Coming, Just Not This Year
Connecting billions and billions of sensor-embedded devices and objects over the internet is inevitable, but don’t yet swallow all the hype. Yes, there is a lot being done to harness IoT for specific aims, but the pace toward the development of a general-purpose IoT platform is closer to a canter than a gallop. IoT solutions are too bespoke and purpose-built to solve broad, commonplace problems – the market still nascent with standards gradually evolving – that a general-purpose, mass-adopted IoT platform to collect, integrate and report on data in real-time will take, well, more time. Like any other transformation movement in the history of enterprise technology, brilliant bits and pieces need to come together as a whole. It’s coming, just not in 2017.

  1. APIs Are Not All They’re Cracked Up to Be
    APIs have long been the glue connecting apps and services, but customers will continue to question their value vs investment in 2017. Few would dispute that APIs are useful in building apps and, in many cases, may be the right choice in this regard. But in situations where the integration of apps and/or data is needed and sought, there are better ways. Case in point is iPaaS (integration platform as a service), which allows you to quickly and easily connect any combination of cloud and on-premise technologies. Expect greater migration this year toward cloud-based enterprise integration platforms – compared to APIs, iPaaS solutions are more agile, better equipped to handle the vagaries of data, more adaptable to changes, easier to maintain and far more productive.

I could go on and on, if for no other reason that predictions are informed “best guesses” about the future. If I’m wrong on two or three of my expectations, my peers will forgive me. In the rapidly changing world of technology, batting .400 is a pretty good statistic.

SnapLogic Sits Down with theCUBE at AWS re:Invent to Talk Self-Service Cloud Analytics

SnapLogic was front-and-center at AWS re:Invent last week in Las Vegas, with our team busier than ever meeting with customers and prospects, showcasing our solutions at the booth, and networking into the evening with event-goers interested in all things Cloud, AWS and SnapLogic.

Ravi Dharnikota, SnapLogic’s Head of Enterprise Architecture and Big Data Practice, took time out to stop by and visit with John Furrier, co-founder of the live video interview show theCUBE.  Ravi was joined by Matt Glickman, VP of Products with our partner Snowflake Computing, for a wide-ranging discussion on the changing customer requirements for effective data integration, SaaS integration, warehousing and analytics in the cloud.  

The roundtable all agreed — organizations need fast and easy access to all data, no matter the source, format or location — and legacy solutions built for a bygone era simply aren’t cutting it.  Enter SnapLogic and Snowflake, each with a modern solution designed from the ground-up to be cloud-first, self-service, fully scalable and capable of handling all data. Customers using these solutions together — like Kraft Group, owners of the New England Patriots and Gillette Stadium — enjoy dramatic acceleration in time-to-value at a fraction of the cost by eliminating manual configuration, coding and tuning while bringing together diverse data and taking full advantage of the flexibility and scalability of the cloud.

To make it even easier for customers, SnapLogic and Snowflake recently announced tighter technology integration and joint go-to-market programs to help organizations harness all data for new insights, smarter decisions and better business outcomes.

To watch the full video interview on theCUBE, click here.

Making Workday Faster for Vassar College

Last week we attended Workday Rising in Chicago where we talked to attendees about integrating Workday with the rest of their IT ecosystems. The real stars of the show, however, were our customers from Vassar College who gave a brief presentation at our booth to discuss their journey from finding the need for an integration vendor, to assessing different platforms, to ultimately choosing SnapLogic’s elastic integration platform as a service (iPaaS).vassar-college-image-edited

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SnapLogic CTO James Markarian on DisrupTV

SnapLogic CTO James Markarian recently appeared as a guest on DisrupTV, a weekly live-interview web-series produced by analyst firm Constellation Research and hosted by R “Ray” Wang and Vala Afshar. The trio discussed a variety of enterprise topics including modern data management, data lake strategy considerations and big data analytics.

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SnapLogic CTO James Markarian Discusses the Evolving Big Data Landscape on theCUBE

SnapLogic was in New York this week for Strata + Hadoop World NYC, and our CTO James Markarian took the opportunity to sit down with Dave Vellante and George Gilbert, hosts of theCUBE, for a wide-ranging discussion on the shifting big data landscape.

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Customer Webinar with Box: Connecting SaaS Apps & Data

Join us on Thursday, September 22nd during this live webinar to hear SnapLogic customer Alan Leung of Box talk about how he architected and implemented Box’s connected infrastructure of SaaS applications like Salesforce and Zuora and cloud data stores such as Amazon Web Services.

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SnapLogic Summer 2016 Release Now Available

Another release is in the books – today we announced the Summer 2016 SnapLogic platform update, along with several additions and improvements to our Snap library.  The release brings additions for big data integration, self-service integration, and enterprise governance and control.

As our VP Engineering Vaikom Krishnan put it:

SnapLogic Summer 2016 Release
SnapLogic Summer 2016 Release

“SnapLogic continues to break down the barriers between data and application integration in the enterprise with a converged platform that is built for self-service. The Summer 2016 release further enhances our Snap library and resources for Snap developers to help support our vision of ‘anything, anytime, anywhere’ integration.”

Highlights of this “Snappy” release include:

  • New Snaps for Apache Hive and Teradata
  • Major updates to Snaps for Anaplan and Tableau
  • Enhancements to the Mapper Snap that make it faster and simpler to search, filter and map the entries in a complex schema tree
  • User-defined pipeline parameters can now be logged and retained with runtime history in order for administrators to audit API usage and quickly debug pipeline performance issues
  • A new, seamless way to auto-shard documents across all nodes in a SnapLogic data processing Snaplex, leveraging the power of all nodes and boosting data integration performance 
  • Users can now limit invocation of triggered tasks to one instance at a time for more granular control and to avoid overloading resources.

We’re also excited for the launch of the new  Snap developer site. It’s easy to use, mobile-friendly and full of practical guidance for our customers and partners building and maintaining their own Snaps.

For more information on the Summer 2016 release, including demo videos, see: https://www.snaplogic.com/summer2016