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CEO Perspective: Future Trends in BI and Analytics

What technologies will help your enterprise become more data driven? Jérôme Lecat, the CEO at Scality, offers insights and updates on where analytics and data management are headed this year and beyond.

• By James E. Powell
• April 3, 2020

Jérôme Lecat, chief executive officer at Scality, describes himself as a business angel with 20 years of internet infrastructure start-up experience. From 2003 to 2010, he cofounded and led Bizanga, a leading email MTA for service providers. He spoke with TDWI's Upside about what's hot now, what's ahead, and key initiatives his company is focused on.

For Further Reading: How the Trust Gap Is Holding Back Data-Driven Decisions From Legacy to Hybrid Data Platforms: Managing Disparate Data in the Cloud Data Architects: Masters of the Soft Skills

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

Jérôme Lecat: The business world is transforming and is becoming even more data-driven. It is not new -- the shift started with modern accounting over a hundred years ago but it is accelerating fast. Practically, data and data methodologies have become part of the assets of every enterprise. Those who invest time, money, and effort to become truly data-driven will have a competitive advantage. It is not so much a question of technology. It is a question of mindset, and it has to start with the CEO. Unfortunately, many CEOs still think that data can be the role of a chief data officer. Although this role is important, it cannot replace the involvement of the CEO.

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

There is so much! I am excited about cloud, not just the public cloud but cloud as an IT architecture, whether private or public, because it decreases the cost of highly reliable computing service by an order of magnitude.

I am excited about UX improvement. At the end of the day, the most notable contributions of computing to our lives were some form of UX. Visicalc, the predecessor of Excel, was a new UX for numbers. WordPerfect, one of the first widely deployed word processing programs, was a UX for words.

I am obviously excited about AI, although I would say that the ultimate benefit of AI is better UX and better data visualization. I don't know how much humans will let AI make the big decisions.

As a result of these technologies, one of the industries that is going to change most in the next 20 years is healthcare. The amount of data we can have on each human is just mind boggling and will help us develop more personalized preventive care.

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

It is employee skills. The technologies and competitive forces are changing faster than natural employee turnover. As a result, enterprises need to re-skill employees who are not always motivated to learn new paradigms for just a few years left in a career.

It is a very complex challenge and I think that most enterprises pay too much attention to technologies and not enough to employee skills.

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?

AI is too broad a term. Many companies have invested huge amounts of money to put together Hadoop tools, data lakes, and AI teams with no results. This is the wrong approach.

Enterprises should not start with technologies but with the question "Why?" What is the goal? Where can AI or BI be useful? Start with impactful experiments rather than grand plans.

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?

Scality is a growing technology (software) company. Our data initiatives cover three very different scopes.

Our first initiative is quantitative analysis of the performance of our software. Performance depends on many variables, including the hardware, the OS configuration, and the workload. It is a multilayer problem. Having a good, fundamental understanding of how these variables interplay is critical for us to be able to advise our customers.

Our second initiative is deployed using SaaS tools, monitoring and getting real-time metrics on our customer platforms several times a minute. This allows us to build predictive models of what may fail and to proactively address these problems before the failure occurs. The ultimate goal is a self-driving system.

The third initiative is about the sales process itself. Enterprise sales is a costly process and we have very detailed quarterly analysis and trends on the sales process, customer growth and churn (very limited), and cross-product sales.

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?

I think that we are going to get better at knowing what data to keep and what not to keep, and we will trust AI systems to make the decisions for us (such as effectively deleting data). We are not there yet because neither the technologies nor the necessary trust in the technology are there.

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

Scality has developed software that allows organizations to deploy theirown private and hybrid cloud for storage of unstructured data. The software, deployed on industry-standard servers, makes a high-performance, highly reliable, and secure storage platform, which delivers cloud economics while staying in the control of our customers. Scality technology allows customers to leverage private or public cloud as appropriate. For example, Scality customers significantly decreased their IT cost by suppressing a whole data center, performing disaster recovery in the cloud. Scality software is designed for large-scale environments, as found in many industries, including some major public cloud services which rely on Scality technology to produce their service offering.