Building data assets to derive actionable insights has become an essential part of business planning. Having a huge amount of data oftentimes turns it into a liability for there is ample chance for data scientists to lose sight of a critical insight when the big data is organized haphazardly. On the other hand, a data catalog can help businesses discover data assets that were lying dormant. Data.world is a cloud-native enterprise data catalog company known for the best data practices in the industry, delivering result-centric insights. Analytics Insight has engaged in an exclusive interview with Brett Hurt, CEO, and Co-Founder at data.world.

1.  Kindly brief us about the company, its specialization, and the services that your company offers.

Enterprises are facing a trillion-dollar data problem. A recent study from NewVantage Partners found that 99% of Fortune 1000 companies planned to invest in big data and AI initiatives last year, but only 24% of respondents believe their companies are actually data-driven. My co-founders and I saw this first-hand in the market as well when we founded data.world in 2015 – for all the talk about data being critical for businesses, the most important data and analyses were typically buried in silos.

At data.world, we believe that business leaders need to view their data supply chain like their actual supply chain – incredibly valuable and essential to the operation of their business. Implementing this mindset across a business requires the right technologies. We offer a data catalog for the modern data stack, enabling both data producers and consumers to easily structure, govern, and analyze the data that powers their business. We're also unique in the space because we have been a Certified B Corporation ever since our launch and are committed to building the most meaningful, collaborative, and abundant data resource in the world to help maximize data's societal problem-solving utility. 

2. Tell us how your company is contributing to the IoT/AI/Big Data Analytics/Cloud Computing industry of the nation and how the company is benefiting clients.

More traditional data catalogs allow enterprises to centralize all their data into one place, creating a single point of reference for those using it. But for today's modern data stack – and the pace of innovation surrounding it – the traditional model doesn't go far enough. Many enterprises are wasting money on their data initiatives because they use outdated ways of thinking about data. Companies that utilize artificial intelligence and big data analytics – from those in the Fortune 500 to startups – require agile data governance, where data is easily accessible, understandable, and usable for everyone within a company. Our company data.world gives enterprises this edge. By providing fast data access, a clear context for the data, and a single platform to enhance data analysis, our customers can multiply the value of their data and use it to drive their products.

3. Kindly share your point of view on the current scenario of Big Data Analytics and its future.

We're at an interesting crossroads for data, both in terms of the current economic climate and its ability to create a whole new level of value for businesses. If past recessions have taught us anything, it's that data-driven decision-making is essential. Most companies understand theoretically that big data analytics can support their business and create value, but they don't know where to start. Plus, traditional approaches that silo data have forced IT teams into a "command and control" posture. This sets the stage for major issues for enterprise leaders, including overspending to try to centralize data and hurting the culture around data within the organization. No one intends this, of course, but it is the harsh reality in too many organizations. 

Recessions, while painful for businesses and the society at large, can be powerful engines for creating more efficient businesses. I have written recently about my belief that big data analytics will play a major part in that trend as we see increasing inflation and recession indicators.

4. How can C-suite executives leverage data to deliver business value to their organizations?

When thinking about the realities of leveraging data to deliver real value for your enterprise, looking to who I call the "knowledge superheroes" can help. Take, for example, Airbnb's founder and CEO Brian Chesky, who turned his company's pandemic challenges into a better business model, driven by data. He turned a company with revenues falling 80 percent overnight into one of 2020's biggest IPOs months later. 

Data catalogs and knowledge graphs can create the same type of transformative change for all companies, and every executive needs to start by getting their data house in order and equipping themselves with the right tools for their modern data stack to get that done. Doing so is critical for building a successful business model today both because of how fast technology is evolving and renewed economic uncertainty. In my recently published book, The Entrepreneur's Essentials, I outline the five critical ingredients for building startups into big companies, and their business model is #1. In today's market, that means investing in the modern data stack that helps your data producers and consumers in the short- and long-term.

5. The industry is seeing the rising importance of Big Data Analytics and AI. How do you see these emerging technologies impact the business sector?

Companies are rightly looking to big data analytics to drive a new wave of business efficiency and resilience by empowering teams to find, understand, trust, and use data needed to address critical business questions. This information can be used to answer questions like, "Where in my organization can I make cuts or reallocate?" and "What projects can I postpone for six months?" 

For example, over the next few months, you might need to put a critical program on hold or unfortunately let go of a percentage of your workforce. If you are leveraging a knowledge graph-powered data catalog, all information associated with the project, including team members, their skill sets, and their relationship to the project and respective data, can be cataloged and understood. Institutional knowledge is retained and connected to the business, so that it can be easily accessed when it's time to rehire, retrain, retrench, or shift back into growth mode. We saw this happen with one of our earliest customers a few years ago when many people turned over. They were easily able to keep their data and analysis work going due to how well it had already been centralized and documented.

6. Where are we going from here?

We're sitting in a much different economic environment than we were even a month or two ago, and businesses across industries need to be preparing proactively for the inflationary and recessionary pressures that are here now and lie ahead. Having led two prior businesses through the dot-com bubble and the Great Recession, I'm optimistic that this time will be different for two reasons: data literacy and agile governance. Since the last recession, the ability to confidently use data to inform problem-solving has improved dramatically. Now, when enterprises have the right tools and processes in place, they can have a much higher level of trust and confidence in the outcome of data-backed decision-making.

My main recommendation to enterprises is to think about data as simply the facts of your business – your customers, your partners, your staff, and your supply chain. Mastery of those facts and the analysis we can pull from them has the potential to shield companies from the worst of the bumpy economic landscape that may lie just around the corner. This time around, tech and business leaders alike have the opportunity to optimize our businesses in a way that was not even possible during the last recession.