IBM (NYSE: IBM) made a significant announcement this week by stating its intent to expand into the big data market.
Big Blue plans to invest $3 billion to build an Internet of Things (IoT) division. This specialized division will work to harness and analyze the vast amount of data collected and created by tablets, smartphones and connected devices.
While this is a new adventure for IBM, which is quite frankly a bit late to the big data market, it’s still a significant announcement given that IBM is hard at work planning a course that will return the company to growth.
And I think it increases the likelihood of consolidation in the big data industry over the next 24 months. IBM is having to rely on acquisitions (over 50 acquisitions since 2009) to create at least some growth while its core business shrinks. And the big data industry is in that attractive window where it’s not new and emerging (meaning lower risk), and isn’t yet mature (meaning there is still a lot of opportunity).
As it looks to build its IoT division, don’t be surprised if IBM focuses on a subset of the big data market called “machine-generated” data. This includes everything from financial transactions and manufacturing data to shopping trends and online consumer behavior.
Reliance on computers, smart devices and the Internet has grown over the years. Now every online transaction is recorded in a database somewhere.
Today, around 11% of data is generated by machines. Industry analysts expect that to rise to 40% within the next six years. And IBM says that around 90% of the data created by mobile and smart devices is never analyzed, meaning there is a massive opportunity.
Machine-generated data is the most complex and most valuable form of data because it shows how machines are being used, and exactly what they’re doing.
A number of companies are working to build search engines for machine-generated data. They’re basically doing what Google (NASDAQ: GOOGL) did for Web content decades ago.
These companies are helping users find exactly what they want in an impossibly massive database, and they do it in the blink of an eye. That capability is worth a lot of money, and I wouldn’t be surprised to see IBM try and leverage its existing relationships by adding products focused on machine-generated data.
But that’s just a speculation. One more certain way to invest is to go with an emerging leader in the space, Splunk (NASDAQ: SPLK). The company develops software that it sells to large organizations, typically in the financial services, manufacturing and technology industries.
A good example of how Splunk delivers value is illustrated by this National Public Radio (NPR) case study. NPR needed help understanding its user base better, since it has millions of users accessing its service from computers and mobile devices.
NPR needed to analyze log files, which are created any time a user accesses NPR content online. Splunk’s software helped NPR do this better than any other solution out there, and NPR says it has been able to provide a much more engaged user base as a result.
Since any electronic device with an imbedded processor generates machine data, Splunk has a large and growing ecosystem of devices from which it can pull data to sell to its clients.
The trick for Splunk is to tap into the data and deliver it in a way that allows its clients to save money and/or generate new sales to their own clients. Thus far it appears to be succeeding.
Over each of the last five years annual revenues have grown by 93% (2010), 89% (2011), 83% (2012), 65% (2013) and 52% (2014). The pace of growth is slowing, since it’s harder and harder to grow by more than 50% on an increasingly larger revenue base.
Despite the slowing pace of growth, Splunk is still growing very quickly. It has a data platform that integrates with many applications that an organization uses (or might want to use).
For example, Splunk works well with products from Tableau (NYSE: DATA), another leading big data stock that specializes in business intelligence.
The more applications Splunk integrates with, the more data users can access through its software. The more data users can access, the more desirable the platform becomes and the more Splunk can charge.
For Splunk, I’m modeling in 30% to 40% annual revenue growth over each of the next three years. That would mean revenues rise by over 150% by the end of fiscal year 2017 (calendar year 2016).
Shares of Splunk, as well as many other big data stocks, are on the rise early in 2015 (though be forewarned that they are a bit volatile).
I believe the future growth prospects for the sector, and for Splunk in particular, make it extremely attractive for new investments right now. And I think that IBM’s push into big data could help the entire space over the next year by increasing M&A speculation and investor interest.
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