Three Data-intensive Digital Transformation Trends for 2021

Lenley Hensarling
Chief Product Officer
February 12, 2021|6 min read

The world demands goods and services—and the digital technology that provides them—more than ever before. Enterprises that can meet this digital demand will flourish. And those that can’t will languish faster than ever.

Easier said than done. First, in the wake of COVID-19, enterprises are doing a digital “level-up” and accelerating digital transformation. In talks with industry analysts, experts, and our extensive customer base, there is intense urgency on all things digital. Companies have reaped the benefits of digital processes that don’t require physical interactions and also stumbled over the cracks of slow, inefficient, and manual business processes.

One issue that can cause digital transformation efforts to stall or even fail is poor data management. It quickly drags business processes down and raises costs exponentially. And most digital transformation is data intensive. It requires enterprises to collect, store, move, integrate, and process large amounts of data to deliver the near-instant, accurate experiences users demand.

Solutions such as Aerospike Database 5, Aerospike Connect, and Aerospike Cloud are the backbone for many of these hyperscale, real-time digital processes. And as we’ve seen with our customers, when it’s done well, there are exponential top- and bottom-line gains.

As the digital transformation race downshifts and slams the accelerator, here are three trends I see happening with data management strategies this year.

One: Attention and Advancement on Customer Data Profiles

Last year, Google said it plans to phase out third-party cookies in Chrome to protect user privacy. Many enterprises rely on cookies to profile and target customers to quickly recommend a product or decide if a transaction is fraudulent.

When cookies go away, enterprises will now have to reexamine how they gather customer intent—and process a new, more complicated mix of hundreds of data sources to know their customers’ digital behaviors. It’s a challenge and an opportunity to deliver better, more sophisticated, and secure profile-driven experiences.

Let’s look at an example in the e-commerce market. Consider the following: a consumer looks up Gore-Tex coats and then sees the ads. Today, e-commerce companies use cookies to help target, and in some cases, refine the recommendation engine. But the coat may not be in their favorite color, etc. Here lies the opportunity. E-commerce companies need to create great experiences to attract and keep customers. They can do that by crunching large volumes of data that helps them deliver the right offer at the right moment in the fastest time possible.

Two: Shrewd (and Better) Decisions on Where Workloads Run

Enterprises are continuing to migrate to the cloud, with spending expected to reach almost $500 billion by 2023. And according to Gartner, 75% of all databases will be deployed or migrated to the cloud, a major shift in a nearly $50B database market.

Operational efficiency drives much of the migration. But that efficiency and elasticity have a cost. The cost-efficiencies in the cloud come from being able to scale up (and down) based on business demands. Enterprises are finding that where they cannot take advantage of variable workloads and being able to match the infrastructure and other software spend against that, they are paying a premium and not getting the full benefit. There is a reason that hybrid cloud patterns are on the rise. Where workloads are stable or growing at a known pace, it is cheaper and more effective to run them on-premises or in a hosted environment as a private cloud.

Enterprises will become far more savvy and deliberate in deciding which workloads should be run in which clouds—public, private, hybrid, or multiple. Customers will even play an arbitrage game fitting workloads to the clouds based on the cost profile of the infrastructure supplied by a given cloud vendor. They’ll start designing for a specific cloud depending on if they need heavy compute, a lot of storage, or network bandwidth—or maybe all of it.

In a public cloud, enterprises need to understand how their workloads fit with the provider’s instance types. Is it more effective to have their workloads scale up on larger hardware instances, or do they best fit with smaller instances that can be scaled up and down in a clustered environment? Network bandwidth becomes a factor as more data has to be moved between parts of the architecture, and that is an expense.

Three: Augmentation Accelerates Digital Transformation

Above, I said digital transformation will accelerate, and that all companies will necessarily be using the latest cloud advances for all their workloads. But you’re probably asking how companies can transform to digital processes given the 30-plus years of accumulated business systems that comprise their back-office footprints.

Enter digital augmentation. Not every system or business process can—or should—be ripped entirely out and reinvented. Often, adding modern technologies around, or at the front end of, existing processes and systems can dramatically speed transformation to something familiar but far more efficient. And in some cases, complete rip and replaces just aren’t practical.

Let’s look at one area: mainframes. What? Those are still around? Yes, and they aren’t going away, especially in banking and government. They’ve captured large amounts of data—decades of data—that remains vital. Ripping them out is very costly, and many workloads still run fine on them. From a business standpoint, there is no added value in moving workloads like batch processing off a mainframe where it performs well.

But the batch process-oriented systems on mainframes were not built to deal with the scale of user interaction that going digital implies. They weren’t designed to handle data analytics and AI/MLworkloads.

Here’s a great example of augmentation. Offloading data to modern infrastructure and deploying AI/ML to that data can bring about a modern, digital process for real-time customer insights with a fraction of the effort. If companies are going to open their systems to their customers to give them the experience that they have become accustomed to through companies like Amazon and others, they need to support millions of interactions a day, all data-driven, and with an expectation of frictionless and real-time interaction. That means they have to build systems to meet those demands and those systems must be able to pass on the transactions to the back-office mainframe-based systems for further processing…and do all this in a cost-efficient way. It’s possible and practical to go digital without abandoning the accumulated business processes that business is based on.


To learn more about trends-in-practice, Aerospike encourages both users and prospects to register for the Aerospike Digital Summit 2021 from May 4-6.