In the roaring 2020s, data will be your most vital asset

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In the 1920s, as the great influenza pandemic of 1918 faded and a synergy of technological processes, increased mass commercialization and increased employment resulted in a massive economic boom. This period, now known as the Roaring Twenties, was a time of immense optimism and opportunity. And history, as it tends to do, has come full circle again.

In the 2020s, we are emerging from a pandemic again and the US economy, after a year of devastating setbacks, is preparing for unprecedented growth. And this time around, the Roaring Twenties won’t bring mass manufacturing and increased migration to cities like a century ago. It will bring the power of context to the concept of data discovery with automated analytics poised to catapult itself into the future in an event that will be told in the history books for decades to come.

As the economy grows, data continues to grow in tandem. Numbers and finances exist on two sides of the same ever-vital coin, with increased efficiency for data collection advancing the capacity for economic growth, and vice versa. The US economy is expected to rebound in the coming months— Deloitte forecasts that 2022 will surpass their prepandemic assumption, and more so, the setbacks and scars that so many economists have warned about in the early months of the pandemic appear to have been avoided entirely.

And we are entering this period of economic growth in a simultaneous technological acceleration. The productivity trends that were in place before the pandemic, including the concepts of telecommunity and e-commerce, accelerated dramatically during the long periods of pandemic containment when we were working, shopping and entertaining entirely at home. When the world stopped, data was our lifeline. Our collaboration, communication and business transactions have all become entirely data-driven. And even as the pandemic begins to abate, a better understanding of our data – and its status as our most needed asset – only becomes more critical.

The most important by-product of this technological revolution will be a vast expansion of the GDP.

Some companies will have a significant advantage over others in this boom. Companies that are already using AI in their data functions are best positioned to handle this rapid growth, because understanding the data you have is a critical and complex step in business development, a step that must be conquered before these breakthroughs. data can be translated into actionable business intelligence.

But most organizations don’t have a complete picture of the data that feeds them. They need a deeper insight into where their data comes from, where it’s used and who it belongs to. Only with this information and intelligence can they use that data to make better decisions on everything: privacy, security, and data governance.

The faster data grows, the more urgent it becomes for companies to rethink their data management. This urgency is amplified by a global source of privacy and personal data protection, ranging from the European Union’s GDPR and the California Consumer Privacy Act, to impending new legislation in Virginia, Colorado and Ohio. Globally, similar regulations are about to be finalized in India and China, cementing the reality that no matter which corner of the globe you operate from, privacy and security regulations are in place. data protection is no longer a nagging possibility. They are absolute certainty.

And as these regulations become more widespread, organizations are forced to offer more transparency and choice to their consumers. The immediate result of this change is a new awareness among organizations about the data they collect, process and share, and an overhaul of their thinking about how exactly they find and manage their data.

The focus should now be on scaling with strategy. It is a moment which calls for a threefold concentration: on the implementation of digital strategies; adhere to new privacy and protection regulations, then maximize the value of existing data, through better visibility, quality and management of data. Machine learning and NLP empower organizations to accomplish the four cs: cataloging, classification, cluster analysis, and correlation. And those four Cs set the stage for the three Ps: confidentiality, protection and perspective.

The Roaring Twenties are back and businesses are gearing up for a boom. But before they can see any returns, they must first understand that in this century, data is the foundation of all financial advancement and business innovation. And if you don’t know what data you have, you’ll never know the benefits that data can bring.

About the Author

Dimitri Sirota is the CEO and co-founder of BigID, a modern data intelligence platform and an expert in privacy and identity. He is an established serial entrepreneur, investor, mentor and strategist, and previously founded two enterprise software companies focused on security (eTunnels) and API management (Layer 7 Technologies), which were sold to CA Technologies in 2013.

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