There’s a reason big data is big. The amount of information that is being collected is staggering and that can make investing in it complicated.
“It’s a digital transformation,” says Rob Strechay, vice president of products at Zerto, a disaster recovery software company in Boston. “Most organizations are still trying to learn what big data means to them.”
Like squirrels collecting nuts for a long winter, companies are gathering as much data as possible via the internet of things, the nebulous network that connects anything digital.
“Many companies are collecting everything because they don’t know what they need yet,” Strechay says.
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It’s quickly amounting to more data than any human can possibly comprehend as companies grapple with how to drive insights into action.
“Almost everything you do leaves a digital trail,” says Wayne Ferbert, co-founder of Zega Financial, a registered investment advisory headquartered in West Palm Beach, Florida, that takes a snapshot of more than 200 data points — including search engine results, engagement and volume on interactions on websites — for more than 2,000 publicly traded companies to track and find outliers within the market. “But big data isn’t useful without analysis.”
That’s because big data still suffers from a lot of quality problems, Ferbert says, and has to be extensively “scrubbed” where incorrect, incomplete or duplicated information is removed and then analyzed. That means many companies are accessing information from multiple providers, typically at least two different third-party vendors, he says to cross-check and verify the data is “clean” and accurate.
To capture that digital footprint, many companies are using artificial intelligence and machine learning to help organize, qualify and manage the data.
“It’s a tsunami,” Michael Skok, co-founding partner at Underscore.VC and an entrepreneur-in-residence at Harvard Business School. “Up until 18 months ago, almost everyone was prepared to make sense of that data, but the sheer volume of data has beyond that and it’s no longer feasible to gain insights into this data without deep learning, machine learning and artificial intelligence.”
Big data is becoming more accessible. As the cost of purchasing big data has come down, Ferbert says the ability to buy it is going up.
“To get access to advanced big data research in the past, you needed to be a very wealthy institutional investor to get access through a hedge fund,” Ferbert says. “But now big data is more accessible.”
Amazon.com (ticker: AMZN) is one the biggest resellers of big data, Ferbert says, and many stock researchers will look for transactions such as the number of Cisco Systems ( CSCO) routers being sold on eBay ( EBAY) and third-party sellers to see if a spike in sales might indicate a product refresh is coming with new inventory.
“There’s a lot of ways to imply trends, and sometimes it’s dangerous because you have to make a lot of assumptions,” he says.
To capture the trend, Skok suggests investors look at software service and application companies that are being built on top of the infrastructure and data storage framework. Focus on companies involved in fundamental analytics and infrastructure that can make sense of the data, while making companies and employees more productive.
“If you are an investor, the trick is time it right,” Skok says. “Which is always difficult.”
Companies are preparing to get hacked. “The security aspect is daunting,” Strechay says. Although he sees a lot of cloud vendors touting how much security they have, he says servers and data storage remain large targets.
“People worry about data security and the physical security of data servers showing up on Google maps,” he says, not only from a hacking perspective but someone trying to break inside to steal or corrupt data.
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Strechay says his company works with a “government entity” in the U.K. that gets hit with CryptoLocker ransomware that locks up a server nearly once a week. Although he says ransoms aren’t ever paid out, they have to assume they are going to get hacked and whatever information that is inside will become public.
“It’s a fact of life today that at some point you are going to get hacked,” Strechay says. “You aren’t planning not to get hit, you are planning what to do when it happens and how to recover.”
Where to look. Although Ferbert says based on his company’s analysis the technology sector will likely see a small correction at the end of the third quarter, companies such as Intuit ( INTU), NetGear ( NTGR), Nvidia Corp. ( NVDA) and Qualcomm ( QCOM) might be a good place for investors to look since they’ve all had positive digital trends as of late and are deeply embedded in data analytics.
Besides Amazon, which recently struck a major deal with VMware ( VMW) to create a hybrid cloud in partnership via its Amazon Web Services, other big players include Alphabet ( GOOG, GOOGL), Microsoft Corp. ( MSFT), International Business Machines ( IBM), Oracle Corp. ( ORCL), SAP SE ( ADR) and HP ( HPQ), Skok says, as well as some that haven’t gone public.
There’s also PureFunds ISE Big Data exchange-traded fund ( BIGD). Launched in July 2015 under the ticker BDAT, the fund, which recently had $1.18 million, down from $2.5 million in total assets, revamped earlier this year.
The fund changed its component eligibility requirements in the index methodology guide to companies that derive its revenue from selling its data analytics software and services. Previously it had focused on big data developer and service providers as well as companies that aggregates massive data sets.
Top holdings include software-focused Pros Holdings ( PRO), Nielsen NV ( NLSN), Hewlett Packard Enterprise Co. ( HPE), SAP SE ( SAP) and New Relic ( NEWR), a software analytics company.
“It’s about doing something that hasn’t been already done before,” says Andrew Chanin, CEO of PureFunds in New York, whose company launched the PureFunds ISE Cyber Security ETF ( HACK).
Cautionary advice. Some experts say that doesn’t always make for a great investment.
“I’d like to see the fund become a little more established,” says Greg Ostrowski, managing partner at Scarborough Capital Management in Annapolis, Maryland.
With an expense ratio of 0.75 percent and bid-ask spread of more than 1 percent, Jeff Ptak, global head of Morningstar’s manager research team in Chicago, says although Morningstar doesn’t cover this ETF, he’s not a fan of how thinly traded it is.
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“Investors haven’t achieved great outcomes with narrowly-oriented products that tend to be pretty volatile,” he says. “We can get excited about the theme, but if we can’t trade it efficiently, we can end up getting eaten alive by transaction costs.”
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How to Invest in Big Data originally appeared on usnews.com
