5500 Viewpoints at Strata+Hadoop World (Includes Video)

With a record-setting audience and hundreds of solutions being touted, Strata+Hadoop World in NYC was the place to learn about all the wild and wonderful ways companies are transforming their capabilities with big data and analytics.

Watch the video for my reactions from the show floor and read my further thoughts on the conference below. 

I go to a lot of vendor and industry events--it's the known perils of the job. Generally, the quality is quite good. Ok, maybe the food quality is variable, but I love the open exchange of ideas on new technologies and future plans. They are usually a fine venue for lively discussions and debates around market maturity, product maturity, and on some notable nights out, product marketer maturity. But there is one event that is really starting to be the highlight of my travel schedule and that's Strata. Ok, Strata+Hadoop World if you insist.

The recent showing in NYC was staggering for the diversity of ideas and opinions on how the world of big data and analytics will evolve. One of my favorite comments was Cloudera's Mike Olson saying, "this is the year we'll see Hadoop disappear," meaning that the focus on real world use cases will start to outweigh the specific technical features. In fact, a common theme was using big data to achieve both social and commercial good. 

A few other highlight moments from the keynotes were:

  • Sharmila Mulligan of ClearStory Data saying traditional BI dashboards were "look, but don't touch" and that we need to move beyond this to interactive engagement and storytelling. This is absolutely where the practice needs to go to engage business users, not just data scientists.
  • Miriah Meyer of University of Utah discussing data visualization and proclaiming, "there are colors, there are circles, it's amazing how much everyone loves circles." You really need to understand what your teams are trying to see and say to make the reports be meaningful.
  • Amanda Cox of the New York Times pointed out that "the annotation layer is super important" in data visualization, and generally questions of "how?" and "why?" are more interesting than "where?" and "what?" Big data isn't just a reporting tool for facts or the truth--the interpretation matters a lot.
  • Joseph Sirosh of Microsoft calling for a marketplace around big data tools and sharing his thoughts on how to combine machine learning with cloud accessibility. With this leading into Microsoft's broad new partnerships announced with both IBM and Cloudera, you can see a new spirit emerging.

You can also find many more comments, quotes, and observations from the event in my twitter feed or watch the video above for some thoughts on the vendors and their themes.

I'd like to also call out a few interesting players on the scene, each doing more cool stuff:

  • Interana - Only recently out of stealth mode, this team of big data rockstars looks poised to offer another order of magnitude performance gain, enabling companies to tackle harder questions for businesses.
  • RapidMiner - With a play on predictive analytics, easy graphical integration, and cloud economics, now seems in position to align the technology to the challenges outlined above. New president and COO Michele Chambers is a solid leader for the technology.
  • Skytree - For hard core machine learning and advanced analytics techniques, check out their solutions--they appear particularly ahead in the area of IoT where scale will jump again. Bringing Ray Villeneuve on board as CEO will accelerate their penetration.
  • BlueData - Bringing the simplicity and orchestration of private clouds to Hadoop, companies wanting to quickly provision servers, pick distributions, and even run and monitor jobs will see significant value.
  • Platfora - A lot of vendors talk about end-to-end solutions, but the integrated offerings here will eliminate a lot of the architecture work, allowing more immediate focus on developing strategic insights.

All of this shows a segment of the IT market that is coming alive to new possibilities and a macroenvironment of collaboration, competition, and innovation around big data and analytics that will be tremendously impactful in the years to come.

Video Transcript

Hello, this is Nik Rouda, Senior Analyst of ESG, talking about big data solutions.

And here today I'm at Strata+Hadoop World at Javits Center in New York City. It's been a very exciting show this year, 5,000 attendees. We're talking about a whole range of big data solutions. There's many of the big names in the industry, obviously being well represented, from Cloudera, Hortonworks, MapR and Pivotal and Hadoop Distributions, and people up and down the value chain from there. Everybody is really excited about this being the time when we move beyond the technology.

We're really trying to get to looking at how do these solutions add value to the business and really understanding where does the technology give you that lever point to better understand your data and really make a business application from it. A lot of different examples here at the show. I look forward to talking through some of them with you.

So we've seen a number of different technologies come to play, but more importantly, we've seen a number of different challenges people are trying to solve. One of the first ones, really, is data preparation. How do I get my data ready so that I can go do the analysis I need to do to get information to derive value from it.

We've seen a number of companies really focused on this space, from Trifacta and Paxata. Of course, Informatica talks a lot about ETL. Oracle is in the picture. Even companies like Platfora are now focusing more on data preparation as part of their story. Figuring out how do we get the data ready. How we join different data sources? How do we do that combination that really provides the data magic? That's one theme.

Another big piece has been consumption models. Obviously a lot of people come to big data thinking we're going to do open-source and commodity, but others are looking at different ways to do this. They can do big data as a service, and companies like Altiscale or Treasure Data are figuring out there is a ready market that want a quicker time to value and don't necessarily care about owning the infrastructure, they just want to be able to manage this.

At the same time, you see new appliance-type solutions, people like Cray and Oracle's big data appliance coming out and saying, "We have the right technology pre-integrated and ready to go, purpose-built for scale and for added reliability." A third piece we really see is more advanced analytics techics. People are starting to look at more graph analytics.

Also trying to see is machine learning ready for prime-time and at what point do more real applications of internet of things come in to play as we start to instrument more parts of our life, more parts of our business? How can we really put that to play? And obviously that becomes a big data challenge very very quickly, exponentially increasing the amount of storage available.

So really a lot going on here, a lot of different plays. It's been exciting to be at the show and definitely contact ESG if you'd like to hear more about what we're doing. Thank you.

Topics: Data Platforms, Analytics, & AI ESG on Location