We all know the world is changing in profound ways. In the last few years, we’ve seen businesses, teams, and people all adapting — showing incredible resilience to keep moving forward despite the headwinds. To shed some light on what to expect in 2022 and beyond, let’s look at five major trends with regard to data. We’ve been watching these particular data trends since before the pandemic and seen them gain steam across sectors in the post-pandemic world.

When you take your car in for a repair, it’s almost inevitable that the mechanic will identify additional problems you didn’t realize you had. But there’s positive flip side to that coin — sometimes when you solve one problem, you end up unexpectedly creating solutions for other challenges—that was the case for this global automotive supplier. In 2019, this automotive supplier set a goal and created a roadmap to integrate its master data.

Sometimes it can feel like you’re stranded on a data island, scratching “SOS” in the sand in hopes of catching the eye of anyone who can rescue you. Companies everywhere are facing an explosion of data — with more data sources, more shadow IT, more people demanding access, and a growing number of business problems that can only be solved with data. As your company’s data leader, every one of those problems lands on you.

In the latest installment of the EMEA Influential Women in Data webinar series, we welcomed Shirley Collie, Chief Health Analytics Actuary at Discovery Health to discuss everything from how the pandemic has impacted working, to the opportunities within data, and the importance of intentionality.

The telecommunications industry has been doing well since the pandemic started (not that many would notice). Revenues have remained relatively stable, while consumption has gone up, as virtual engagement has become the primary mode of operations for many businesses (and families!) In the mean-time, digital transformation has been accelerating both as a means to respond to the pandemic, and as a mechanism to drive costs down further, allowing for margin growth.

For almost a decade now, global business leaders have heralded the beginning of the Fourth Industrial Revolution, which refers to how technologies like AI, robotics, IoT, autonomous vehicles and computer vision are blurring the lines between the physical, digital, and biological spheres. Industry 4.0 has paved the way for transformative changes in business, unleashing advances in business process automation in the front and back office, driving unprecedented productivity and growth.

The road to the data-driven enterprise is not for the faint of heart. The continuous waves of data pounding into ever-complex hybrid multicloud environments only compound the ongoing challenges of management, governance, security, skills, and rising costs, to name a few. But Hitachi Vantara has developed a path forward that combines cloud-ready infrastructure, cloud consulting and managed services to optimize applications for resiliency and performance, and automated dataops innovations.

Organizations today face challenges from rapidly changing markets, new technologies, and the need to build new modern apps running in a multicloud environment. For this reason, business leaders are demanding faster delivery of new applications, services, and insight, requiring greater agility and efficiency from IT. Enterprises, rightly so, are investing in modernizing their on-premises infrastructure with increased use of the cloud.

Although many enterprises are at varying stages in their cloud journeys, most are adopting distributed mixes of on-premises and public cloud environments in order to maintain certain data and applications close by, while making others more accessible and available online. With such distributed cloud networks, core tenants of the enterprise, such as management, scalability and security, become increasingly challenging. There is a path forward, however.

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists. This unprecedented level of big data workloads hasn’t come without its fair share of challenges.