CEO Perspective: Future Trends in BI and Analytics
From AI and machine learning to logical data models and data-driven decision making, we explore what enterprises are (or should be) working on with Sisense CEO Amir Orad.
- By James E. Powell
- September 20, 2019
Is your data accessible? Is it coming too fast? Are your tackling AI and machine learning now or do you expect them in your future? Upside spoke with Sisense CEO Amir Orad to explore what's hot now, what BI and analytics trends are on the horizon, and what tech offers a bigger opportunity to your enterprise than you may know.
Upside: What technology or methodology must be part of an enterprise's data strategy if it wants to be competitive today? Why?
Amir Orad: To be competitive, you need to make data accessible to as many decision makers and operators in the organization as possible. Too many organizations have data locked down underground in data silos, making it inaccessible and difficult to use. That frustrates people, reduces innovation, and affects the ability to make decisions.
Second, the velocity of data today is such that any data strategy needs to assume that your data inputs, outputs, and requirements are going to change every month. As a result, you need to build a very agile system for data analysis. A waterfall method that takes time and effort to make small adjustments just won't work. A typical approach is to balance the two extremes and have some data technologies that are more rigid and planned and some that enable more ad hoc and agile development. But you cannot function with just the former.
What one emerging technology are you most excited about and think has the greatest potential? What's so special about this technology?
First, as much as it's overhyped, machine learning and AI are also under appreciated. Today, models are able to detect everything from cancer to your insurance risk to the chance you have a car accident better than any human-built algorithm. ML and AI are going to transform our lives and put any organization that's not leveraging them at a total disadvantage to the point of irrelevance.
ML and AI are also enabling a whole new industry of robotic process automation. We won't be replacing artists or songwriters tomorrow, but we can replace a lot of other mundane tasks and free up people and businesses to spend time on things that just matter more. For example, I'm proud to say, through our work with GE Healthcare, we have seen them build over a dozen analytics applications taking advantage of modern machine learning and analytics in Sisense to better predict and automate processes that had been manual and less accurate before.
What is the single biggest challenge enterprises face today? How do most enterprises respond (and is it working)?
There's two areas where enterprises used to have clear strengths that have now become weaknesses. First, most enterprises are proud, robust organizations with very strong culture, but in a majority of them, dynamic deployment of modern technology is not a part of the culture. Specifically, when it comes to analytics and data-driven decision making, many of these organizations don't have the right DNA to take advantage of the latest technologies.
Second, these organizations have had the luxury of building gigantic IT systems, the strongest and the fastest on the planet. However, these IT systems were built historically with rigid controls and very limited access to data, so when you want to quickly and nimbly deploy analytics and data products in an enterprise, you'll find that legacy to be limiting, not enabling. Those two things were advantages and are now becoming disadvantages and slowing enterprises down.
I view our role at Sisense as providing these organizations a bridge to let them leverage their amazing people and assets by getting them more quickly and easily into AI, ML, and other technologies and bypassing some of those historical limitations.
Is there a technology in data and analytics that creates a bigger opportunity for enterprises than they realize?
Logical data models, or what we call our semantic data layer, which is somewhat similar in concept to what was once thought of as logical data warehouse. That's something we strongly believe in and we think there is an amazing opportunity to decouple the physics of data with the logical representation to business people. By decoupling it, you accelerate your ability to access and use data and ignore historical limitations.
What initiative is your organization spending the most time/resources on today? In other words, what internal projects is your enterprise focused on related so that you (not your customers) benefit from your own data or business analytics?
As you know, we've recently gone through a merger with Periscope Data. Right now, our goal is to build a unified product that will bring the best value from Sisense and Periscope Data to our combined and future customer base.
We've begun implementing a process to develop a quantitative approach as well as a qualitative one. The quantitative approach looks at customer usage data of each feature and involves a per-feature deep dive to determine the value each feature offers. This is highly customized to each feature, as each has different benefits to customers, and the KPIs that we study for each are very nuanced. We're supporting this with high-level qualitative customer interviews to better understand workflows; together that approach paints a full and rich picture of customer needs and customer value from each product. Analyzing that data helps inform our priorities, and tradeoffs on the path to a unified product.
This is just one example. Staying data-driven throughout the company is critical for helping us improve our sales process, enhancing our product offerings and building the best analytic tools for our customers.
Where do you see analytics and data management headed in rest of 2019 and beyond? What's just over the horizon that we haven't heard much about yet?
Every business must be data-driven or it will die. As an extension of that, it's imperative that every enterprise has technologies that allow it to put data at the forefront of every business decision. If a business is making decisions on gut instinct alone, it will fail. You must have technology that can help you derive insights from data so decision makers at every level of the business can make real, actionable choices.
Every occupation, every decision, every business, every process will be data-driven and analytics-driven, and it's our job as professionals to make sure we're on the right side of history and not become irrelevant. Some will take a decade, some will take five more years. Some will take just a year and some are already here, such as IoT devices that provide you personal sleep recommendations.
It's really the beginning of gigantic data-driven revolution that could make an impact as big as the internet did 15 years ago. Data-driven technologies are leveraging all the cloud-computing and connectivity power of the internet together with data mining capabilities to change everything for the better, and individuals and businesses will be better off as a result.
Describe your product/solution and the problem it solves for enterprises.
The Sisense analytics platform dramatically accelerates the time it takes to build, embed, and deploy intelligent analytic apps that unleash user creativity and engagement. Whether it's interactive dashboards, self-service analytics, or white-labeled BI apps, Sisense delivers the industry's lowest TCO at scale, all on a hybrid-cloud platform designed to leverage all of your data together no matter where it is.
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.