How Big Data will change your life in 2017
With this week's announcement that ERP vendor Infor will be acquiring cloud BI player Birst, the consolidation of the analytics world continued. Even as new startups in the machine learning/AI space get funded, the number of independent players in the BI and Big Data world continues to dwindle.
Also read: Infor buys business analytics vendor Birst
In its press release on the acquisition, Infor made its case pretty clear, saying:
BI companies provide the analytics platform but don't understand industry processes and potential insights. Application companies understand the processes and industries but have lacked the platform to render data and analytics.
Put the two together, the thinking goes, and you really have something.
Infor isn't the only company to think so. Consider the following acquisitions in the data and analytics world:
- Salesforce acquired BeyondCore in 2016
- Workday acquired Platfora, also in 2016
- ZenDesk acquired BIME in 2015
Do you see a pattern? All three are SaaS providers: Salesforce covers the CPM space, Workday the Human Resources/Human Capital Management area, and Zendesk focuses on customer service/experience and help desk implementations. Infor and all three of the above benefit from strong, native analytics functionality, and none of them had it before the above acquisitions.
Still not convinced? Consider Progress Software's acquisition of DataRPM, announced earlier this month, which allows Progress to add predictive analytics and other cognitive functionality to its stack of business application development tools and tech. Analytics in business software is a thing.
A great number of acquisitions have taken place in the data and analytics space. I covered a bunch in 2015 and then another batch last year.
With the Infor/Birst announcement, it seemed worthwhile to cover some more.
Just as the acquisitions discussed above fall into groupings, so too do the other deals I want to discuss here, so let's approach it that way.
Analytics for analytics
Let's start with acquisitions of data-oriented software companies by other data-oriented software companies. A great place to start is Syncsort's acquisition of Trillium. The latter company focused on data preparation and cleansing, making it a great combination with Syncsort. Why? Because if there's one place where a lot of so-called "dirty data" is born, it's on the mainframe, and that's the platform on which Syncsort focuses its Big Data efforts. Syncsort saw a gap in its own stack, a company that could cover it, and acquired it to address the deficiency.
Qlik did something similar, when it acquired geo-analytics/GIS provider Idevio, to make map-oriented analytics far more powerful than what Qlik has had native to its platform. And given that Idevio's product was already packaged as a Qlik add-in, the fit was a good one in technology terms, not just in terms of wants and needs.
Next in the cover-the-gap category is Cloudera's acquisition of Sense.io in 2016. Sense's data science collaboration tooling fit really well into Cloudera's strategy to go beyond the vanilla Hadoop distribution business.
Sense's product, which Cloudera has integrated as its "Data Science Workbench" component, meshes well with Hue, Cloudera Manager, and especially Cloudera Navigator. These components aren't just management consoles, they're tooling, and they make Hadoop and Spark far more useful and productive. Data scientists will now join other constituencies in benefiting.
The ultimate aid in making things turn-key is actual services delivered by consultants. Not all customers want this, but for those who do, a good consulting org is critical. Teradata saw this when it acquired Think Big Analytics in 2014, and it apparently saw it again when it acquired UK-based Big Data services firm Big Data Partnership last summer and merged it into Think Big.
I know I'm only citing one deal for an entire category. But consider the global systems integrators (SIs), like IBM and HPE, or the major professional services firms, like Accenture. Big data, predictive analytics, and AI are now huge opportunities for each of these firms. Services and analytics go together. Acquisitions and partnerships will facilitate that.
Get (analytics) onto my cloud
The next and richest category is that of cloud-based analytics services. There are three deals that fit here. Let's start with SAP's acquisition of Hadoop as a Service provider Altiscale. SAP figured Altiscale could give them a great Hadoop story in the cloud, and augment HANA as it does so. Hard to blame them.
Next, data science community and competition platform Kaggle was acquired by Google just last month. Kaggle is being integrated into Google's cloud platform, giving Google both community credibility and added expertise to deliver on its cloud data and AI platform promises.
Amazon Web Services (AWS) made a somewhat similar choice when it picked up harvest.ai, in a deal that aimed at adding security and threat detection for its customers to its broad cloud platform. While not an analytics play per se, harvest uses AI technology in its threat detection pursuits and thus AWS picks up both IP and people that could address AI offerings more directly.
Not to be outdone, Microsoft, which has made several analytics and AI-related acquisitions that I've covered before, made another one in January of this year: Montreal-based Maluuba. That company concentrated on natural language processing, machine reading and writing, and AI more generally. While Microsoft hasn't explicitly said that Maluuba's technology and people will be deployed to the Azure cloud platform, it would be hard to imagine them not being integrated into everything going on under the Cortana Intelligence umbrella.
Also read: Microsoft buys deep-learning startup Maluuba
Shopping carts at the ready
Whether it's BI and Big Data software companies enhancing their products, an analytics platform company building out its services organization, enterprise application providers embedding analytics capabilities in their products, or each of the major public cloud providers building out its AI capabilities, the analytics shopping spree is in full swing.
With so many indie analytics companies continuing on in business, and so many new ones being funded, especially in the AI world, we can certainly expect more deals. Sometimes all these data startups seem like farmed produce, with the bigger players poised to harvest and eat them. That seems to be the innovation food chain right now... and appetites haven't abated.