Imagine the Internet back in its infancy.
There was a lot of content being created, but things were not easy to find. Then along comes Google (NASDAQ: GOOG), and suddenly it’s easy to find what you want.
Google’s search engine became the gold standard for Internet search, and it still is.
Over the years our reliance on computers, the Internet, and even Google has grown. Now, every online transaction is recorded in a database somewhere.
This is just the beginning of a growing data set called “machine-generated data”. It includes everything from financial transactions and manufacturing data, to shopping trends and online consumer behavior.
Today, around 11% of data is generated by machines. Industry analysts expect that to rise to 40% within the next six years.
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.
Because of the potential, a number of companies are working to build search engines for machine-generated data – essentially to do what Google did for web content.
They’re helping users find exactly what they want in an impossibly massive database, and do it in the blink of an eye. That capability is worth a lot of money.
One of the emerging leaders in the space is 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 NPR 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 them 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 out there 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 SPLK 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 were absolutely pummeled earlier in 2014. After a multi-year run that saw many Big Data stocks soar several hundred percent, the sector was ripe for a correction.
That happened, and now shares of Splunk, as well as many other Big Data stocks, are on the rise again. I believe the future growth prospects for the sector, and for Splunk in particular, make it extremely attractive for new investments right now.
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