How Data is Fueling & Accelerating Digital Transformation How Data is Fueling & Accelerating Digital Transformation
A recent report from Twilio found that the global pandemic has sped up digital transformation strategies at 97% of companies. Not... How Data is Fueling & Accelerating Digital Transformation

A recent report from Twilio found that the global pandemic has sped up digital transformation strategies at 97% of companies. Not only that, but 79% of companies have also seen their digital transformation budgets increased in response to global consumer patterns shifting. The widespread closure of offices, with the subsequent and inevitable move to remote working; extended lockdown periods that have forced brick and mortar stores to quickly pivot to e-commerce; and the abrupt stop to face-to-face entertainment which has seen online platform subscriptions soar, are some of the examples that illustrate how the events of 2020 have forced businesses in all industries to prioritize digital technologies to weather the storm and stay afloat.

At the center of this urgent and necessary shift to digital is data. Every action that consumers take—ordering clothes online, buying groceries for delivery, signing up for a new streaming service—generates data. We already knew that data volumes were growing at an alarming rate year on year before 2020, but when physical interaction stopped being an option, already growing data volumes skyrocketed. This is both a challenge and an opportunity for companies looking to take advantage of this broadened view into consumer behaviors and preferences. If done well, data analytics can fuel digital transformation and take an organization to the forefront of digital innovation. 

In this article, we’ll take a look at the role data plays in fuelling and accelerating digital transformation. We’ll also look at deployment options and their impact on digital strategies, and the role automation plays in helping data teams become more agile. 

The Growth of Digital Transformation in 2021

To capitalize on the opportunities data offers, organizations must embrace data analytics as a powerful force underpinning decision-making across all areas of the business, whether supporting data experts or data consumers. Companies that apply data analytics to drive insights that support business decision-making can significantly help and accelerate their digital transformation initiatives. But this isn’t easy to achieve, and many organizations have found the technology they had in place before 2020 couldn’t cope with the new demands brought on by the pandemic. McKinsey & Company released a report in October 2020 which found that COVID-19 has accelerated the digitization of operations by three to four years. This is in line with Exasol’s report released in September 2020 that found 84% of organizations globally were under increasing pressure to make faster decisions as a result of the COVID-19 pandemic. Worryingly, Exasol’s report also found that 58% of organizations lacked access to real-time insights at the time the research was conducted. It is therefore not surprising to learn as a consequence that more than half of the respondents to McKinsey’s research said they are investing in technology for competitive advantage or refocusing their entire business around digital technologies.

Technology for Digital Transformation

Deploying the right technology to support the widespread use of data across the business is essential because, when data is used to its full potential, it can help unlock substantial opportunities. Data-driven insights into consumer behavior is just one of the ways in which organizations can gain a competitive advantage if they can harness the power of analytics. Stock management, forecasting demand, supply chain management, and risk assessment, to name a few, are other examples of areas where data analytics can significantly add value to a business. But, at a time when volumes are exploding and time windows for decision making are shortening, businesses cannot afford to wait for insights. That’s why working with an analytics stack that can deliver answers when you need them, no matter how huge the data volumes, is crucial for organizations to be able to reap the benefits of a data-first approach.


This is where the cloud comes into play. There is a lot of buzz in the industry around the benefits of the cloud. In fact, the move to the cloud has been ongoing for a number of years and is expected to continue so, but this journey accelerated significantly in 2020. But is the transition to the cloud an answer to all your digital transformation woes? There is no denying that rapid cloud adoption has enabled greater data democratization for many organizations. Making data more accessible has been a digital transformation goal for a long time, and undoubtedly the accelerated move towards the cloud has helped make this a reality. A great example can be seen at Revolut, one of the fastest-growing fintech companies in the world. Revolut has achieved true data democratization with the use of an in-memory analytics database on Google Cloud Platform. 

Data Democratization

Data, and universal access to it, is key for today’s companies to create new opportunities and unlock the value embedded within their organization—all of which can positively impact a company’s top and bottom line. True data democratization pushes organizations to re-think and maybe even restructure, which often means driving a dramatic cultural change in order to realize a positive outcome. It also means freeing information from the silos created by internal departmental data, customer data, and external data, and turning it into a borderless ecosystem of information. There is no denying the power and importance of democratizing data, and so it should be a priority for all businesses, regardless of their deployment choice. 

Despite the undeniable fact that a cloud-first deployment has benefits, in particular when it comes to democratizing data across an organization, it is important to note that the cloud is not the only way to accelerate digital transformation journeys or achieve data democratization. Many enterprises have technology stacks that are set to remain on-premises meaning there’s a strong preference for hybrid or even a fully on-prem approach. These enterprises, too, can be—and many are—at the forefront of digital innovation. There are two key elements here that go beyond the deployment choice. One, a carefully planned data analytics and innovation roadmap that is tailored to the organization’s needs. This roadmap must ensure that the technology powering any data analytics projects can adapt as the business needs shift. In an ever-changing and dynamic environment, technology should allow for the agility to pivot as needed. Second, a comprehensive data strategy that is championed by senior leadership across the organization, with a key focus on fostering a data-first culture for all teams. 

Once data is democratized and in the hands of every business unit, specialist data teams should have new-found resources to focus on value-add projects. Unfortunately, this is not always the case. Often, data teams spend too much time on manual tasks related to data preparation and engineering just so the data is in working order.  That’s why automation can help accelerate digital transformation. By taking advantage of advances in machine learning (ML) and artificial intelligence (AI) technology, automation helps improve the speed, accuracy, and performance of certain tasks. This frees up the data team’s resources and helps them focus on value-add projects that have a direct impact on a business’s bottom line. As automation technology advances, we can expect projects such as data ingestion, metadata management, and database tuning and configuration to be prioritized as they typically present the largest pain points in the data supply chain. 


The past year has been challenging, but one main positive is that it has undoubtedly accelerated digital transformation efforts across all industries. The widespread application of data analytics, the move to the cloud, and increased use of automation have been some of the trends that we’ve seen fueling digital transformation in 2020. In 2021, we’ll continue to see the cloud as a platform for innovation, though it won’t be the only one. Data analytics leaders should explore AI and ML tools as they apply to automation to release pressure from their data teams, enhance productivity and help drive innovation. Finally, as discussed in this article, no discussion about data would ever be complete without examining organizational culture and data democratization. Giving employees the power to make better-informed decisions based on data-driven insights no matter the business unit they work in is the only way to achieve true digital transformation and stay ahead of the curve in an ever-changing world. 

About the author:

Helena Schwenk writing an article on digitial transformation for opendatascience.comHelena Schwenk is analyst relations and market intelligence lead at Exasol. She specializes in markets, trends, competitive landscapes, and go-to-market strategies and acts as a conduit between the market and Exasol’s marketing, sales, and product management teams. Schwenk also works as an external spokesperson and writes and presents frequently on the issues, developments, and dynamics impacting data analytics technology adoption. Schwenk has over 24 years of experience working in the data analytics field, having spent 18 years as an industry analyst specializing in Big Data, Advanced Analytics, and more latterly AI, as well as 6 years working as both a former data warehousing and BI practitioner.


ODSC Community

The Open Data Science community is passionate and diverse, and we always welcome contributions from data science professionals! All of the articles under this profile are from our community, with individual authors mentioned in the text itself.