The amount of data we generate every day is staggering and almost impossible to wrap your head around. Every time we upload or watch a YouTube video, add to cart, send an email or WhatsApp message, tweet, or stream a movie we are creating data.

The amount of data created, transmitted across computer networks, and consumed globally is projected to be 97 zettabytes and projected to almost double by 2025 to 181 zettabytes (1). For context, a zettabyte is 1,000,000,000,000,000,000,000 bytes. That’s a lot of (ones and) zeros, but how is it possible to store so much data? Innovation and investment in things like data infrastructure, such as Databases where these gigantic amounts of information is stored.

However, just to add some additional power to that mind-boggling number, about 2.5 quintillion bytes of new data are created every day. This number is expected to grow by 23% per year (2). So where exactly is all of this data coming from?

Every minute of every day, 66,000 photos are shared on Instagram, 16 million texts are sent, 500 hours of videos are uploaded to YouTube, and 1.7 million pieces of content are shared on Facebook. Companies that want consumer dollars know this, and they aren’t standing idly by. Beyond the giants of the tech industry like Google and Amazon, small- and medium-sized enterprises increasingly depend on effective data analytics tools to get their products in front of prospective customers.

As you might have realized already, data infrastructure and data science are some of the most in demand sectors in the world today. According to the Bureau for Labor Statistics, “employment of data scientists is projected to grow 36 percent from 2021 to 2031, much faster than the average for all occupations” (4).

With all that data, we need people and companies to make sense of this increasingly complex ecosystem. Not only that, but much like the highways and other pieces of infrastructure that allow the modern world to deliver and transport goods, services, and even people from point A to point B, we need the same type of infrastructure to do the very same with our data.

Just think where we would be if the massive technology companies like Microsoft (MSFT), Alphabet (GOOGL), or Amazon (AMZN) would be without the infrastructure that allows them to transport, store, and act on the massive amounts of data they collect from consumers. Without the internet and the various other forms of data infrastructure in place, 

, the growth these companies have seen over the years would not be possible on the same scale it is today.

However, before you go off to invest in all the next big database companies or those developing data infrastructure itself, there are some things investors need to be made aware of. Here’s what investors should know about this rapidly growing industry.

Before diving into data infrastructure, let’s discuss big data – the information that companies are using to generate insights on their users – and what it is exactly. Big data has four “Vs” or measures of value: volume, velocity, variety, and veracity (5).

means that “the more comprehensive your integrated view of the customer and the more historical data you have on them, the more insight you can extract”.

means that the faster that “you can process information into your data and analytics platform, the more flexibility you get to find answers to your questions via queries, reports, dashboards, etc”.

means that “the more varied customer data you have – from the CRM system, social media, call-center logs, etc. – the more multifaceted view you develop about your customers”.

refers to the accuracy and cleanliness of customer data.

Veracity-based value refers to the accuracy and cleanliness of customer data.

These values are the goal of good data infrastructure – what will lead to useful and actionable consumer insights for the massive companies that need this data in order to grow and thrive in an increasingly competitive world. Moreover, much of that competition comes from who has the best data and is able to act on it in the most agile way.

To analyze data, you first have to store it. Many companies rely on cloud storage rather than having their own servers, but what exactly is the cloud? The cloud is typically an off-premises data center that is accessed remotely through the internet. 

 data centers, as well as other databases, allow clients to manage their data through third-party managed services, using hardware that’s run and serviced offsite by cloud companies in physical locations around the world.

In essence, these companies are creating a virtual infrastructure for the systems that used to be housed on-site in every corporation. With the overwhelming growth in data creation, physical data centers that service these cloud computing companies are multiplying, and so is investment in them.

Of course, data storage is only one component of data infrastructure, but it is a key component nonetheless. Beyond storage, data infrastructure includes the network that transfers the data, the applications that host the analytics tools and any redundancies (backups to protect your data in case of an emergency).

According to a report by the Motley Fool, “data is the oil of the digital economy” (6).

Effective data infrastructure means more money and more efficiency, and not just for retailers figuring out how to get an online shopper back to their site to add something to a shopping cart. 

Bankers, for example, can use big data to help minimize risk and fraud for their clients in a world that is under 

increasing threat of hacks and other cyber crimes

. Moreover, manufacturers can use it to quickly troubleshoot problems, making better business decisions, as well as increasing operational efficiency across the organization.

 where readily available high- quality data can not only revolutionize an industry, but it can also be used to save countless lives over the long term.

For all sorts of businesses, the various benefits of using data strategically or prioritizing good data infrastructure include reduced costs, reduced time spent, optimization of product development and allocation, and more informed decision making.

According to an Advance Market Analytics report, the demand for big data as a service is driven by a few defining factors: 

An increasing demand for real time data analytics solutions

The growing use of big data to identify fraud

A significant data influx for small and medium sized enterprises that want effective data analytics tools to maximize revenue (7).

These are aided by market trends including the rise of cloud computing and the integration of big data with cloud-based services, a huge influx of data, as well as more modern business models.

How Can Magnifi Help You Invest in Data Infrastructure?

 can suggest a number of ways to gain exposure to all the innovation taking place in the data infrastructure and cloud computing industry.

Once you find investments you feel would fit well in your portfolio, you can quickly purchase those stocks or funds directly on the platform in a seamless way to enter the market. Here are a few data-themed investments you may want to consider:

Although the big data industry is still in its infancy, this opens the door to a wide variety of possibilities, especially for the early adopters. Beyond the companies looking to improve their own businesses by employing data services, there are a multitude of innovative companies streamlining huge amounts of data into useful information.

For investors, this means that there is more than one way to invest in this growing industry. Here are some common examples of searches conducted by investors interested in gaining exposure to this industry:

What are some top data infrastructure stocks?

The quickest way to compile a list of the top data infrastructure or cloud computing stocks is to run a quick search on Magnifi and let your AI investing app do all the heavy lifting. From there, you simply choose the stock that is right for you and buy it right on the app.

Data infrastructure refers to digital infrastructure that promotes and facilitates data sharing and consumption across the globe. Similar to other infrastructures, it is a structure needed for the operation of a society, as well as the services and facilities necessary for an economy to function, the data economy in this case.

Why do we need more data centers in future?

Data centers are important for the centralization of IT operations and equipment for the purposes of storing, processing and disseminating data and applications across various organizations, as well as various regions across the planet.

What are emerging trends in data infrastructure?

One of the largest emerging trends, as is true across many other industries as well is the integration of artificial intelligence and machine learning. In order for these technologies to be possible and to allow them to scale to the heights we envision them to, reliant data infrastructure is a requirement in order to transmit and store all that data.

What should I look for while investing in data infrastructure stocks?

When looking at businesses that operate in data infrastructure, it is important to understand the size and scope their business and technology has on the various other industries they are servicing. In other words, are they at the forefront of developing data infrastructure that allows these new technologies to come online or are they just a piece of the larger puzzle? Doing proper research into the stock or company should be the first thing you do.

What are the types in data infrastructure technology?

There are a wide variety of types in data infrastructure technology, but some of the main types are: cloud platforms, networks, data centers, as well as technology to ensure that all this data is stored in a secure place.

“Data Never Sleeps 10.0,” Domo, https://www.domo.com/data-never-sleeps#

Friedmann, Jonathan, “Ushering In A New Wave Of Data Acceleration” Spiceworks, 15 November 2022, https://www.spiceworks.com/tech/big-data/guest-article/ushering-in-a-new-wave-of-data-acceleration/

“Occupational Outlook Handbook: Data Scientists,” Bureau for Labor Statistics, https://www.bls.gov/ooh/math/data-scientists.htm

Mohanty, Soumendra, “The Four Essential V’s for a Big Data Analytics Platform,” 10 June 2015, https://dataconomy.com/2015/06/the-four-essentials-vs-for-a-big-data-analytics-platform/

DiLallo, Matthew, “Brookfield Infrastructure Sees a 100-Year Investment Opportunity in Data” The Motley Fool, 27 September 2020, https://www.fool.com/investing/2020/09/27/brookfield-infrastructure-sees-a-100-year-investme/

“Big Data As A Service Comprehensive Study by Application,” Advanced Market Analytics, September 2021, https://www.advancemarketanalytics.com/enquiry-before-buy/45023-global-big-data-as-a-service-market

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The information and data are as of November 15, 2022 unless otherwise noted and subject to change. This blog is sponsored by Magnifi.

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