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TDWI Upside - Where Data Means Business

CEO Perspective: What's Ahead for Data and Analytics

From migration struggles to vendor lock-in, we look at some of the most challenging enterprise problems and changes ahead with Raj Verma of MemSQL.

Raj Verma is co-CEO at MemSQL. He brings more than 25 years of global experience in enterprise software and operating at scale. He was instrumental in growing TIBCO software and has served as CMO, EVP global sales, and COO.

For Further Reading:

Executive Perspective: Future Trends in BI and Analytics

Why Enterprises Are Turning to the Cloud for Global Data Management

Modernization Projects Will Dominate Data Management Through 2020

We asked Mr. Verma to tell us what lies ahead for enterprises in everything from data strategies to data architectures and management.

Upside: What technology or methodology must be part of an enterprise's data or analytics strategy if it wants to be competitive today? Why?

Raj Verma: Enterprises need to have the information to make decisions in the window of opportunity provided. Data is increasing by the second, and the useful life for data is diminishing. Any company that has postponed digitization is regretting it today. Having a strategy that is real time is what the current business environment requires. Some would say real time is not enough because you have to be predictive in understanding and determining how your customers or your resources are going to react to certain events that are likely to happen.

Data strategies that do not have vendor lock-in will do well. The multi-billion-dollar empires in enterprise software are built on holding enterprises for ransom. To stay competitive, enterprises must avoid being locked in and subservient to one vendor. There needs to be an exit button enabling enterprises to leave and take their data out at any time. Having a good technology that is also philosophically aligned with their own organization is a best practice I recommend.

What one emerging technology are you most excited about and think has the greatest potential? What's so special about this technology?

Amino therapy is going to be game-changing. It will be phenomenal for physical and mental diseases. Anything we can do to hasten those research projects will be extraordinary.

From a data perspective, I'm impressed with technology that has been built on first principles. First principles thinking means taking a fresh look at a problem and -- with the latest research and technologies at hand -- thinking through a better way to solve it, from the ground up.

First-principles thinking simplifies seemingly complex problems and unleashes a wide range of creative possibilities. Technologies that were built on first principles allow companies to avoid lock-in and give a real-time view of what is happening within their organizations. They are also inherently flexible, so they are easier to deploy in new environments, such as hybrid cloud and multi-cloud.

For databases and analytics, first principles thinking means determining what you want your database to do. Today, people want to work with the newest data, not just historical data, and they need to answer queries generated by AI programs and machine learning models quickly.

To meet these new requirements, you need the conceptually simple, inherently scalable architecture. That's why we call MemSQL the Database of Now! Our technology is being used by large telecommunications providers to develop heat maps for regions with large COVID-19 infection rates to see where people are congregating and point out areas to avoid. It's helping to get medical supplies to the hospitals and frontline workers that need these products most. This requires technology that is based on first principles.

What is the single biggest challenge enterprises face today? How do most enterprises respond (and is it working)?

The biggest challenge that large enterprises of today face is how to migrate off their legacy platforms in an efficient, economical, and agile manner and align to new business realities. Competition for larger enterprises is only a click away. No one is safe in today's economy.

The companies that do the hard and heavy lifting to respond to that will be surprised. Enterprises should be paranoid about how bulletproof their data architecture is. To standardize on a technology or a company is probably the worst decision you can make today. It is time for best-of-breed solutions that deliver the best of every world.

Is there a new technology in data or analytics that is creating more challenges than most people realize? How should enterprises adjust their approach to it?

The best way to kill an organization is to have bad data architecture and use that for decision making. The organizations that are rushing to buy analytics technology should pause to make sure their data strategy is right and confirm that they can make informed decisions with the data they have.

Enterprises need to look at today's challenging landscape, including the heavy lifting of understanding various data sets, curating them in the right manner, governing the data sets with the right attributes, and identifying the dependability of one source of data over another. A good analytics or BI tool will bubble up both the good and the bad information. Unless you have strong convictions that your data architecture is right, don't go into AI blindly right now.

What initiative is your organization spending the most time/resources on today? In other words, what internal project(s) is your enterprise focused on so that your company (not your customers) benefit from your own data or business analytics?

The number one initiative for MemSQL is to have a thriving hybrid platform that is easy to consume both in a self-deployed manner and in the public cloud while also offering companies the utmost ease of use.

Internally, we've added implementation of our customer data by adding support tickets with adoption and customer success. With our managed services, we've added to the number of users and queries that people can have on our trial in the cloud. Throughout all of this, we have always kept one initiative in mind: how do we help our customers get the most out of our own technology? We're drinking our own data. We've found it extremely useful to make investment decisions, to have interventions at customer sites to make them more successful, and to reach the outcomes that customers partnered with us for.

Where do you see analytics and data management headed in 2020 and beyond? What's just over the horizon that we haven't heard much about yet?

Data management will have to get a lot easier to perform and adopt. How do you make such a complex science easy to understand and consume? Analytics has already exploited the ease-of- use side. Analytics will have to get a lot wider in its ability to suck in data and provide a more holistic view of the organization. It must be nimbler to attract more sources of data inputs. Many AI tools are still extremely pricey. We can see a lot of those costs coming down as the user base expands.

Describe your product/solution and the problem it solves for enterprises.

The problem that MemSQL solves is how to marry real-time transactional data with historical data to make the best decision in the window of opportunity provided. MemSQL does it at scale, on commodity hardware, and with unprecedented speed and ease of use through a hybrid, multicloud environment.

[Editor's note: Raj Verma was formerly COO at Aptus Software and Hortonworks. He earned his bachelor's degree in computer science from BMS College of Engineering in Bangalore, India.]

About the Author

James E. Powell is the editorial director of TDWI, including research reports, the Business Intelligence Journal, and Upside newsletter. You can contact him via email here.

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