It’s Big Data Week here in Silicon Valley with data experts from around the globe convening at Strata+Hadoop World San Jose for a packed week of keynotes, education, networking and more - and SnapLogic was front-and-center for all the action.
SnapLogic stopped by theCUBE, the popular video-interview show that live-streams from top tech events, and joined hosts Jeff Frick and George Gilbert for a spirited and wide-ranging discussion of all things Big Data.
First up was SnapLogic CEO Gaurav Dhillon, who discussed SnapLogic’s record-growth year in 2016, the acceleration of Big Data moving to the cloud, SnapLogic’s strong momentum working with AWS Redshift and Microsoft Azure platforms, the emerging applications and benefits of ML and AI, customers increasingly ditching legacy technology in favor of modern, cloud-first, self-service solutions, and more. You can watch Gaurav’s full video below, and here:
Next up was SnapLogic Chief Enterprise Architect Ravi Dharnikota, together with our customer, Katharine Matsumoto, Data Scientist at eero. A fast-growing Silicon Valley startup, eero makes a smart wireless networking system that intelligently routes data traffic on your wireless network in a way that reduces buffering and gets rid of dead zones in your home. Katharine leads a small data and analytics team and discussed how, with SnapLogic’s self-service cloud integration platform, she’s able to easily connect a myriad of ever-growing apps and systems and make important data accessible to as many as 15 different line-of-business teams, thereby empowering business users and enabling faster business outcomes. The pair also discussed ML and IoT integration which is helping eero consistently deliver an increasingly smart and powerful product to customers. You can watch Ravi and Katharine’s full video below, and here:
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.
- 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.
- 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.
- 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?
- 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.
- 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.
- 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.
We have a slight problem at SnapLogic. While we spend a vanishingly small percent of the day watching adorable cat videos on the Internet, it seems our CEO always shows up behind our desks while doing so. If only we knew when our CEO was nearby and could get an alert when he was.
Continue reading “Enterprise IoT: Watching Cat Videos Without Getting Caught (or, How I Learned to Stop Looking Over My Shoulder and Trust the CEO Proximity Alert”
Today’s post comes from Joseph A. di Paolantonio, an industry expert working at the convergence of IoT with data management and analytics at DataArchon.com and the Boulder BI Brain Trust. Leveraging a career that started with renewable energy research in graduate school and industry, developing risk assessment models and algorithms for aerospace systems, and managing teams for enterprise data warehousing, BI and data science, Joseph is defining sensor analytics ecosystems to bring value from the IoT.
What’s IOT All About
We have been asking what the IoT is all about for a very long time. Since Kevin Ashton first coined the phrase in 1999, and perhaps even since Nikola Tesla first played with a remote control boat in 1898. For many, the simple act of connecting a device, not a computer, not a router, to the Internet is enough. But even if everything around us, in work, at home, for business, for play, was connected..Does this make the Internet of Things? Does this fulfill much of the hype or any of the stories surrounding the IoT? Not at all.
Continue reading “The Evolution of IOT Data Management with Joseph A di Paolantonio”
Interested in connected devices and the Internet of Things? Tomorrow, SnapLogic product manager and IoT expert Shayne Hodge will be the featured presenter on an O’Reilly Media webinar titled: “The CEO proximity warning device: Prototyping a cellular, GPS-enabled cloud-connected IoT device.” Register here to secure a spot.
Continue reading “O’Reilly Webcast ft. SnapLogic IoT Expert”
In this latest installment of our ongoing IoT blog series, we’re going to start discussing a more extended pipeline that we’ve installed here at SnapLogic HQ (as promised in the last post). Space prohibits us from showing all the details of how it works, but we’ll hit the high points in this post and the next.
You may have, at some point in your career, been in a meeting that has gone overtime. (You may be in one right now). You’ve probably wished for something to stop the meeting. Well, the Internet of Things is here to grant your wish.
We’re going to create a pipeline to activate a conference room meeting-is-over signal, the Luminescent Evanescent Apparatus for Voiding Engagements.
Continue reading “Practical Enterprise IoT: The Luminescent Evanescent Apparatus for Voiding Engagements”
The last post in this ongoing IoT series detailed the creation of a cloud-based Ultra Pipeline to do the bulk of the work for our IoT application. We described the following application:
- A sensor somewhere (on-premises, from an API, etc.) that produces data that includes a “color” payload;
- An LED on-premise, attached to our local network, conveniently hooked up to look like a REST endpoint;
- Two pipelines, one on-premise, one in the cloud.
Continue reading “Building an IoT Application in SnapLogic, Part II: Speeding Through the Last Mile”