Opportunities To Play The Explosive Growth Of Big Data

by: Matthew Dow

The tremendous growth of Data from internet connected devices is nothing short of amazing. As an IT professional, I have been hearing about this trend for some time now - but it wasn't until recently that I really grasped just how big this growth is. The numbers are eye popping.

Take a look at some of these figures below, which I have sourced from this CSC website:

  • By 2020, only 8 short years away, globally stored data will grow by 4300% from 2009 levels. (That is not a typo!)
  • In 2009, there existed 0.79 zetabytes of data. A zetabyte (ZB), by the way, is 1,000,000,000,000 gigabytes.
  • In 2010, this increased already to 1.2 ZB. In other words, in 1 year, the world's data grew by 50%. That's right, in 1 year we created 50% of the data that we had created in all prior years combined! Talk about exponential growth.
  • By 2020, this will grow to 35 ZB in total.

This growth is so phenomenal that it's almost impossible to fathom. But in a practical sense, what does this mean actually,and how can we think about this in an investing frame of mind? Being more of a value oriented investor, I tend to try and avoid the high growth situations where inflated expectations can lead to very high price multiples on companies that are involved in "hot" industries or technology trends. In situations like that if the growth turns out to be a bit lower than expected, the stock prices often fall hard and quickly.

In this article first I'll give a personal slant to the Big Data story, based on my experiences in the IT field. I'll then give a few examples of companies that have favorable long term prospects benefiting from the Big Data revolution and growth of data storage in general.

My Personal Take on it

As an IT consultant for a large multinational consulting firm, I feel I'm in a good position to see how this trend is developing in the enterprise and give some insight into it. It is true that every year I see the numbers getting larger and larger - only a few short years ago we were always talking in megabytes, and occasionally gigabytes. Now it is very common to talk in thousands of gigabytes, or "terabytes".

I think it's important to note though that how relevant it is to do extensive analysis on large data sets depends greatly on the industry and type of data involved. Currently, I work for a large client with about 100,000 employees. This company is in the middle of migrating employee generated data (documents, emails, shared network folders, etc) to a new enterprise content management system (ECM). For those who don't know what this is, ECM software is frequently used by large corporations that need to organize and classify employee data in a centralized way so that it can easily be shared across the enterprise. These are not really considered "Big Data" software systems, as they are more focused on things such as: storage, document versioning, categorizing, and searching. The Big Data story is much more around having the capability to analyze huge amounts of real time data for trends and useful patterns which can be exploited for things such as marketing campaigns towards consumers. In the case of my current project, the client has about 80 terabytes of data to manage (a terabyte by the way is approx. 1000 gigabytes). The nature of the data does not require intense analytics, where they need to look for customer trends or other insights within the data. So in this example Big Data software is not really so useful.

Other organizations and types of data however Big Data software is much more useful. Take Wal-Mart (NYSE:WMT) for example, which has 1 million customer transactions every hour, and reportedly stores more than 2.5 petabytes of customer transaction data. To put that into perspective, that is about 2640 terabytes, or 33x more data than my client's 100,000 employees have created after years of working. A company like Wal-Mart is very interested to find consumer patterns in this data that help it determine its product and marketing strategies going forward.

The point I want to make with these different examples is that although the amount of data in total is clearly exploding, of course we won't need or want to analyze every bit of it - it largely depends on the context. In fact there are growing concerns about being able to keep up with even storing it all. My current client for example has simply put in some archiving rules where they will delete data that is older than a certain amount of years unless it is tagged as very important.

To be clear though, the market for Big Data information management software is still growing much faster than the traditional software market - about 10% per year. So although this is not growing at the rate of actual data growth as we saw in the beginning of the article, it is still quite impressive.

In recent years Oracle (ORCL), IBM Corp (IBM), Microsoft (MSFT) and SAP AG (SAP) between them have spent more than $15 billion on buying software firms specializing in data management and analytics. So clearly the big IT firms are taking this trend very seriously.

Potential Companies to Invest in as Big Data Plays

As a more value focused investor, I like to look for out of favor or underpriced companies, with good long-term prospects and what I perceive to be limited downside risk.

Where can you find this in the high growth expectations of Big Data? Many companies are involved in Big Data, besides the ones just mentioned above. To name a few other prominent ones: EMC Corp (EMC), Teradata (NYSE:TDC) and Tibco (NASDAQ:TIBX). Of all these companies, the most attractive in my opinion is EMC. EMC doesn't appear that expensive with an EV/EBITDA of around 10 and a forward P/E of only 13. This is quite low, as 35 analysts covering the company have an average 5 year EPS growth rate at nearly 15%.

EMC is the largest provider of data storage platforms in the world, and has traditionally always had a strong Storage business even before the term Big Data existed. Some other characteristics of EMC are summarized below:

Summary Highlights of EMC

Criteria Comments
Business Prospects

Very diversified portfolio, with Storage products for both the large and medium sized enterprises. Also a security division, 80% ownership in the strongest virtualization company (VMWare), Greenplum Big Data platform, IT management and Cloud computing platforms.

Strong growth prospects in all of these areas in the coming 5-10 years should bode very well for the company long term.

Conservatively Financed More than 5.5B in cash, and a total debt/equity ratio of only 0.08.
Shareholder Friendly

The company has consistently repurchased shares of both EMC and VMWare stock in the past few years.

Valuation (Margin of Safety) Assuming on average of 10% EPS growth in the next 10 years, a discount rate of 6%, and a confidence margin of 75%, I calculate an intrinsic value around $30/share.
Predictable Earnings In only 10 years, Sales have gone from $5B to $20B. Earnings have largely increased in line, rising from 0.22/share to 1.10/share.

In conclusion, I think EMC is a great company that is currently trading at a fair price. I've added it to my watch list. At $27.20/share, my estimate is that the margin of safety is only 11%, based on the conservative growth estimates I assumed. As I don't like betting too much on anticipated growth, in this case I would wait a few months to see if there is any pullback in the price to the $23 or $24 range before considering more seriously whether to purchase or not.

Note: For those who may have read some of my focus articles, I generally use a 10-point system to evalute companies. The criteria listed above are part of my system. You can see an example here. In the case of EMC I won't get into that much depth in this article.

Before closing I'll leave you with one out-of-the-box company completely different than EMC that I have a long position in. This is 21 Vianet Group (VNET). Vianet is a small-cap company (market cap of $600 million), which is the largest private data center provider in China. It is not directly a big data analytics play, (it is not a software company actually) but I think a very intriguing company to ride the overall growth of data storage. This will happen even quicker in China than many other countries. A lot of fast-growing Chinese web companies are using Vianet as a hosting provider. The company has a forward P/E of only 16, which is quite low as the 6 analysts covering the stock have a 5-year EPS growth rate of 20%. The company trades just under $12/share, down significantly from its IPO price near $18/share in early 2011. The company's prospects have not really changed, but it has been out of favor, as it has gotten punished due to general ethical concerns with Chinese reverse merger small-cap companies trading on U.S. exchanges, many of which have been accused of fraudulent accounting practices. VNET however does not deserve to be grouped in this category, as it has gone through a proper IPO on the U.S. markets and is a much larger and established company that has not shown signs of this kind of behavior.

In conclusion, there are lots of potentially attractive investments in companies that have great prospects due to the Big Data revolution. I recommend you seriously consider looking at some of these names to add to your portfolio, particularly on a pullback in price or at a time when they are temporarily out of favor. The long-term growth of Data volume in the coming years is just too great to ignore.

If Mr. Market offers you a discount on any of these great companies make sure you are ready to go shopping.

Disclosure: I am long MSFT, VNET. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

About this article:

Author payment: $35 + $0.01/page view. Authors of PRO articles receive a minimum guaranteed payment of $150-500.
Want to share your opinion on this article? Add a comment.
Disagree with this article? .
To report a factual error in this article, click here