How to Invest in Data Infrastructure?

15 Nov 2022

Investing Interests
Lines of computer code in red, purple, teal and white.

181,000,000,000,000,000,000,000 bytes or 181 zettabytes - the amount of data projected to be consumed by 2025

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Investing in Data Infrastructure

The amount of data we generate every day is staggering. 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 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.

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.

Data science is one of the most in demand sectors in the country. 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. Here’s what investors should know about this growing industry.

What is data infrastructure?

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

Volume-based value 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” (6).

Velocity-based value 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” (7).

Variety-based value 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” (8).

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.

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. Cloud data centers 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 companies are multiplying, and so is investment in them.

Storage, of course, is only one component of data infrastructure. 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).

Why invest in data infrastructure

According to a report by the Motley Fool, “data is the oil of the digital economy” (9).

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. Moreover, manufacturers can use it to quickly troubleshoot problems, making better business decisions.

For all sorts of businesses, 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 1) an increasing demand for real time data analytics solutions, 2) the growing use of big data to identify fraud, and 3) a significant data influx for small and medium sized enterprises that want effective data analytics tools to maximize revenue (10). These are aided by market trends including 1) the rise of cloud computing and the integration of big data with cloud-based services, 2) a huge influx of data, and 3) more modern business models.

How to find data infrastructure investments

The big data industry is still in its infancy. 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:

References:

  1. “Data Never Sleeps 10.0,” Domo, https://www.domo.com/data-never-sleeps# (https://www.domo.com/data-never-sleeps#).
  2. 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/ (https://www.spiceworks.com/tech/big-data/guest-article/ushering-in-a-new-wave-of-data-acceleration/)
  3. “Data Never Sleeps 10.0,” Domo, https://www.domo.com/data-never-sleeps#
  4. “Occupational Outlook Handbook: Data Scientists,” Bureau for Labor Statistics, https://www.bls.gov/ooh/math/data-scientists.htm
  5. 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/
  6. Mohanty, Soumendra, “The Four Essential V’s for a Big Data Analytics Platform.”
  7. Mohanty, Soumendra, “The Four Essential V’s for a Big Data Analytics Platform.”
  8. Mohanty, Soumendra, “The Four Essential V’s for a Big Data Analytics Platform.”
  9. 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/ (https://www.fool.com/investing/2020/09/27/brookfield-infrastructure-sees-a-100-year-investme/)
  10. “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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