What’s Coming Next in Big Data? Show Me the Money - Part 2

In the last post here, we looked at a number of investments in the general area of big data, and compared the fit with some data points ESG’s just collected research on for our 2014 IT Spending Intentions research report.

If you missed the first part of the story, check it out here: whate28099s-coming-next-in-big-data-show-me-the-money-part-1/index.html" style="font-size: 1.2em; line-height: 1.25;">http://www.esg-global.com/blogs/whate28099s-coming-next-in-big-data-show-me-the-money-part-1/

Continuing the same vein then:

Tidemark $1m - what they do: mobile-oriented visualization & analytics apps


Doing the statistical data analysis is only half the challenge, getting the findings to the right people and helping them to actually understand what their data is telling them is the other half. Our survey shows 28% of IT staff view visualization as one of their top investment priorities for the year to come. Vendors that can help bring the data insights to the decision makers should do well.

MemSQL $35m - what they do: an in-memory database built for speed


Many big data users are looking to move beyond historical reporting and build real-time analytics for faster response. For example, ESG research shows 34% view faster tactical response to shifting customer attitudes as a top benefit to be gained. To do this, you must be able to perform your analysis quickly, even while loading tons of new data, which is where in-memory plays.

Jut $20m - what they do: it’s all a big secret


With a team of former Riverbed hotshots, they seek to reinvent the way big data applications something, um, well, they aren’t saying, but someone clearly believes it’ll be profitable. 20% of ESG respondents said their IT spending in this area will grow by more than 5% compared with last year, so perhaps a rising tide floats this well-pedigreed boat.

Alpine Data Labs $16m - what they do: simplify the process of analyzing data sources


Collaboration is key to understanding in the world of data models, and it’s often an iterative team effort to get to the right conclusions. ESG found 36% really wanted to encourage this kind of collaboration between IT and the business units. As discussed in an earlier post, some companies are working to make that happen more readily.

IBM $1b - what they do: many things, now aiming Watson at big data


Repurposing the game-playing artificial intelligence to use machine learning in the cloud on innovation sounds like a science fiction movie plot premise, but it’s far and away the biggest financial move in recent months. Our study offered up 10 distinct benefits being sought from big data initiatives, and suprisingly ALL of them received high marks. Big incumbents can bring big resources, it will be fascinating to see how they try to out-innovate the new players above.

Topics: Data Platforms, Analytics, & AI