As you read this, thousands of computers across the world are tracking you. Data firms can guess your gender, age, education, and income levels based on which pages you visit, how long you visit them, and even how fast you scroll through the text.
Now, consider that you’re just one out of billions of people connected to the web. Big Data is watching everyone, and its products serve as virtual gold in today’s digital economy. In fact, Big Data is so big that one private intelligence firm uses it to predict terrorist attacks.
If you’ve got money to invest in Big Data and cloud computing technology, what basics should you know beforehand? Why are Big Data and cloud computing such massive industries? And, most importantly, which stocks could make wise bets today, and which ones should you avoid for now?
What Is Cloud Computing, and How Big Is This Industry?
For the purposes of this article, we’ll be combining Big Data with cloud computing. Yes, there are differences between the two, but these two industries are so intertwined that, in some cases, they’re practically the same entity.
Let’s define these two things first, though. Cloud computing refers to computing services accessed through the internet that are often spread across several networks that can span entire continents. If you’ve ever used Google, Facebook, or Adobe’s online services, you were using cloud technology.
Cloud computing is more than just a giant, interconnected storage drive. Clouds merge a network of computers and apps into one streamlined unit, amplifying processing power, scalability, storage capacity, and uniformity of performance while also minimizing maintenance costs and operational failures. Basically, clouds are Big Tech’s ultimate wet dream come true.
Big Data, on the other hand, refers to when you have more data than you can process on a single server, or the velocity of the incoming data is too high to deal with using conventional methods. Big data can involve streams of database information — structured and unstructured — that businesses collect at a rapid, ever-increasing pace. Big Data often requires cloud computing to collect, store, and analyze all that information. (Note: this is a simplistic definition of a tech category that is massive and exponentially growing. So take this with a grain of salt.)
Right now, the Big Data industry generates about $140 billion annually. According to one report, that could approach $230 billion by 2025.
So if you’re wondering if there’s money to make by investing in Big Data and cloud technology, the answer is yes.
On that note, cloud computing’s financial outlook appears even more promising than Big Data’s. Last year, the cloud computing market was valued at around $199 billion. One report estimated that by 2027, the cloud market could be worth $760 billion.
The global economy and our daily humdrum lives become more dependent on digital tech by the day. That alone should signal that cloud computing and Big Data are worth your investment. But there’s another critical reason to anticipate these industries rising in value over the next decade.
Why Investors Should Buy Cloud Computing Stocks
While it’s a given that Big Data and cloud computing will continue growing, most folks are oblivious to these industries’ near-future market potential.
You’ve probably heard of machine learning and artificial intelligence (AI). The basics of machine learning are self-explanatory: coders program computers to learn from the data those computers collect. At the moment, machine learning is elementary and entirely binary. Computers currently cannot think like humans can, but they can compute data exponentially faster than us. Google’s DeepDream, for instance, uses machine learning to interpret artistic styles and create new images. While DeepDream isn’t “thinking” in the conventional sense, it is learning and creating.
True AI, according to cognitive scientists like Douglas Hofstadter, is any computing system that can analyze other systems and analyze itself in a way that allows it to implement useful changes to itself and other systems. For computers to accomplish this, they must understand how symbols convey meaning. In other words, they need emotions so they can make informed decisions regarding what needs to change and why.
What Big Tech today refers to as AI isn’t really AI. It sounds cool in media interviews and on press releases, but we’re not quite there yet.
However, computing made a giant leap toward AI with a class of machine learning called deep learning. Deep learning is a computing process where code can rewrite itself based on new data. It started with image analysis, and now deep learning can distinguish objects among audio and text, too. To put it another way, deep learning is teaching computers how human languages work, which is one step away from developing emotions.
According to ARK Invest, an investment advisor focused on “disruptive innovation,” deep learning dominated cloud computing as of last year, meaning it powered almost all large-scale internet services, from searches to social media. This is why Facebook and Amazon’s targeted ads come eerily close to reading our minds. In a way, they actually are reading our minds by gathering billions of data points on our behaviors, then assessing those points in novel and useful ways. (They’re also scanning our supposedly private communications to one another, but that’s another story for another day.)
Deep learning can do much, much more than just tailor ads to our latest whims, though. Self-driving cars, automated manufacturing, conversational computers like Alexa, pharmaceutical research, space exploration, online shopping, retail shopping, agriculture, mining, civil engineering, health care, drone deliveries, financial services, cybersecurity, mass surveillance, and even mass media will depend on deep learning’s exponential advancements over the next decade.
The Top Cloud Computing Stocks to Watch
Since Big Data and cloud computing require a lot of capital resources, giant firms are best equipped to manage these technologies. That simplifies things for new investors.
Easy bets here include companies like Alphabet ($GOOGL), which owns Google, and Amazon ($AMZN). Name any industry, and Alphabet’s probably got its digital fingers in it somehow. That, and Google’s search engine determines where web traffic goes based on its own page ranking algorithms.
As for Amazon, its Amazon Web Service (AWS) infrastructure practically runs the entire internet right now. Do you already own stock for Netflix, Slack, Zoom, Pfizer, Disney, Comcast, or Samsung? If so, then you’ve already invested in Amazon via AWS, too.
Other top-performing cloud computing stocks include Adobe ($ADBE), Microsoft ($MSFT), Salesforce ($CRM), and Alibaba ($BABA). To compare, Adobe’s price grew by about 25% over the last year, while Alphabet and Google grew by nearly 40% each.
Stock hype and a company’s ubiquity can mean slower growth compared to newer upstart firms. Indeed, Alphabet, Amazon, and Facebook’s stock prices have remained relatively steady for the past few months, so the big fellas aren’t exactly quick-and-easy cash as of this writing.
If you’re thinking about investing in smaller (but not small) cloud companies with greater potential for long-term capital gains, look into DataDog ($DDOG), Domo ($DOMO), Fastly ($FSLY), Workiva ($WK), Pinduoduo ($PDD), JD.com ($JD), and DocuSign ($DOCU), or cloud-based security firms like Crowdstrike ($CRWD) and Zscaler ($ZS).
Of course, if doing your homework on all these different companies strikes you as daunting, you can always leave the heavy lifting to an ETF. Some ETFs that handle cloud computing and Big Data are First Trust Cloud Computing ($SKYY), Global X Cloud Computing ($CLOU), and Future Analytics Tech ($AIQ).
Don’t forget about ancillary businesses, either. Cloud computing and Big Data need things like high-end processors to keep operations running smoothly. While most clouds currently utilize Intel’s x86 architecture, Amazon, Microsoft, and Apple are already switching to ARM and RISC-V, which perform faster than x86. ARM also possesses better power efficiency, which means fewer overheating issues, too. ARK Invest predicts ARM and RISC-V technology may replace Intel’s x86 within the next decade: “Together, [ARM and RISC-V] could grow 45% per year to reach $19 billion in CPU revenue and $100 billion in server revenue by 2030.”
If you’re banking on cloud computing, Big Data, and AI, you might want to throw a few bucks into NVIDIA ($NVDA), which bought the pioneer of ARM processing, Arm, for $40 billion last year.
Examples of Cautionary Tales in Cloud and Data Investments
Oof, avoiding cloud stocks is trickier than, say, avoiding unwise bets in cannabis or electric vehicles. That’s partially due to the nature of cloud computing and how cloud infrastructures often interpenetrate one another. For example, Netflix and Disney+ compete with Amazon Prime Video, yet both Netflix and Disney have partnered with Amazon to use Amazon’s cloud service, AWS.
Another reason why clear losers (and, to a lesser extent, winners) can be tricky to pin down is due to fickle social psychology. Stock trading is often irrational. Last week’s painful dip among tech stocks illustrates this: Rumors that the Federal Reserve would raise interest rates led to widespread sell-offs within every tech sector, followed by slow recoveries (and dips again) after the Fed’s chairman promised interest rates would stay put until 2023.
Regardless, some cloud computing stocks haven’t done so hot over the past few years, despite the market’s boom. For example, IBM ($IBM), at one time the leader of PCs, proved milquetoast for nearly eight years straight, with steady price declines over the last four years. IBM’s future may improve now that it’s new CEO is pushing its hybrid cloud services, but only time will tell.
Nutanix ($NTNX) serves as another cautionary tale in the cloud computing space. Its current stock price is roughly half of what it went for in the summer of 2018. Back then, Nutanix’s virtualization and storage services were hot, but subscriptions didn’t pan out like investors hoped. However, Nutanix’s stock has consistently risen since the COVID-19 pandemic hit the US, so it may pay off in the coming years. Or... it might slump once again after the pandemic officially ends.
Going back to processors, Intel may be an unwise bet due to how slow it’s rolled out new tech. AMD ($AMD) saw nice gains in 2019 due to its GPUs’ popularity for AI, and that momentum could persist for cryptocurrency mining. However, AMD’s a smaller operation than Intel or NVIDIA, and its processor tech remains leagues behind NVIDIA’s advancements.
Finally, Facebook ($FB). This is an unpopular opinion, but Facebook may not be as lucrative as analysts say it is. Last week, the company flexed on the entire country of Australia, and lost. (Google, on the other hand, handled the Australia thing with grace.) Furthermore, Facebook’s revenue depends heavily on ads, and market research suggests its ad model may not be terribly effective. On top of all that, antitrust suits could spell disaster for investors (or not, as Microsoft proved years ago).
What’s the lesson here? First, a company’s debts and dividends aren’t always smoking gun indicators of stock price. Stock prices are largely dictated by supply and demand, and demand can be easily swayed by bullshit. Second, that same bullshit can trigger bullish runs based on hype.
If You Have $500, How Should You Invest It in Cloud Computing and Big Data?
Before you invest a single dollar into cloud computing, decide whether you’re going for a long-haul hold or if you’re speculating for a quick buck. If it’s the latter, understand the risk of losing that money is high right now. Tech stocks skyrocketed over the last year, thanks to COVID-19.
If vaccine rollouts end the world’s social distancing policies, there’s a good chance tech stocks may sink across the board. At any point during this summer onward, investors may move their money into more tangible areas like banking, government bonds, and entertainment.
But you’re in this for the long-haul, right? In that case, rookies should drop $200 into cloud computing and/or Big Data ETFs. Make sure you follow those ETF portfolios so you know which companies they’re invested in, which can guide your trades in the future.
Since ETFs are low risk, gains tend to be lower with them, too. For bigger gains (but greater risk), spread another $200 across the top data daddies: Alphabet, Amazon, Microsoft, and Alibaba.
Reserve that last $100 for whatever you want. You could put it into ancillary companies like processor makers, cybersecurity firms, or smaller businesses that you suspect may blast off one day.
Watch how the stock prices move over time. If something looks like a loser, sell it, cut your losses, and reinvest into one of your winners.
As always, never invest money you can’t afford to literally throw away. All investments carry risk. What looks like a winner today could flip into a loser tomorrow. And note that nothing you just read is tried-and-true financial advice. They’re merely suggestions. For solid advice based on your investment goals and resources, hire a financial advisor.