5 Minutes with a Data Scientist and CEO: Ben Tai of DrivenBI
Before launching DrivenBI, Ben Tai was most recently vice president of global services at Business Objects, now an SAP company. At Business Objects, he led the worldwide XI migration program office to drive R2 product adoption. Prior to Business Objects, Ben was vice president leading worldwide professional services at Vitria, a provider of enterprise application integration (EAI) and business process management (BPM) software.
Before Vitria, Ben developed his career for 13 years at Oracle, the enterprise and database provider. His last position at Oracle was group vice president leading managed services business unit. Ben holds a Master of Science degree in electrical engineering from NYU Tandon School of Engineering. He studied American culture at Columbia University and business administration at USC Marshall Business School.
Tai spoke to Upside about his current job and his outlook on the analytics and BI industries.
UPSIDE: What’s the one thing you wish people knew about your job?
Ben Tai: I have worked with some of the world’s largest companies in helping them analyze their data. In doing so, I’ve come to understand that the tools and methods we use for data analytics are overly complex, expensive, and generally ineffective.
Are you working on anything interesting right now? If not, what’s your dream project?
We have created the first cloud-native self-service business intelligence solution that doesn’t require any on-premises equipment nor data warehouse or programming of any kind. It is something that allows business professionals who need the analysis to organize, customize, and view the data they need on their own. It even allows them to prepare and import data with no help from IT.
What’s your favorite part about being an analyst/data scientist? Your least favorite part?
My favorite part is the customization of how data is analyzed by each company. How each analyst creates meaningful analysis to fit their specific business need is remarkable. Whether it’s a manufacturing company that analyzes data that helps them reduce energy costs or a retailer that analyzes fashion trends to streamline inventory, everyone gets something different — and something really valuable.
My least favorite part is the complexity of the tools that most business users have to deal with (which my company is fixing). The data analysis tools used by the large corporations I was involved with were so complex that they went underused or unused completely. Despite pouring millions into these big brand names, analysis was done reviewing spreadsheets.
If you could go back in time, what’s the one thing you would tell yourself as a new analyst/data scientist?
You don’t need to learn to program or struggle with the technical aspects of importing and manipulating data. Focus on how to view data in ways that will create real profits and savings.
What’s a personality trait you think people need to succeed at your job?
Most people view data analysis as a technical function, but that is changing as analysis tools become less complex. The traits that make a good analyst today are more creative and visionary. The next generation of successful analysts will be the creatives, not the programmers and number crunchers.
What’s a typical day like for you? Do you work mostly with a team or mostly alone? Which do you prefer?
There are lots of things that I have to deal with every day as a both a data scientist and a CEO. A typical day would have me spend most of my energy and attention driving strategies for business development and team building which includes organizing and mobilizing the team by providing them vision and guidance to execute mission-critical tasks including sales, marketing, engineering and consulting. Having said that, I deem it crucial for the success of my company to have a good team, and I would definitely like to be part of the team.
What’s your biggest pet peeve (abused buzzword, overhyped idea, etc.) and why?
Big data. I’m in the BI business so I hear it a lot. The reason I think it’s abused and overhyped is because more and more people are talking about it without truly understanding it. Some say big data is just lots of data, and most people simply think it is a silver bullet to solve all problems out there without the fundamental understanding of the data itself. The data does not give you the answer until you know how and what to do with it. However, as Fred Brooks has said, in the world of software engineering, there is no “silver bullet.”
Is there a tool or technique that isn’t popular today but has a lot of potential? Why?
Real-time collaboration. It might be a surprise to hear that because surely there are already a lot of collaboration tools out there. I’m saying this within the context of the business I’m in. BI should not be just about producing the result without a systematic way to collaborate. A BI tool can offer even greater value if it facilitates the users to take immediate action upon the analysis results when the collaboration also has to be proactive other than reactive.
This is exactly one of the great aspects of my company’s product. Other BI vendors will start to realize the importance of making collaboration and action-taking as part of the BI cycle, but we are already ahead of the game.
Whether it’s the latest Python build or a 50-gallon drum of espresso, what’s the one thing you can’t do your job without?
Teamwork. I mostly work with my team including sales, engineering, marketing, and product specialists and I enjoy it. Walk into my office and my teams will update the latest status with me. We are all focused on achieving our KPIs for the business, and yes, we all use our own BI technology to analyze and improve our decision-making and grow our bottom line — just like our customers. Most important, my office is usually open for my team. I prefer a clear, direct way of communication.
What’s the most common roadblock you hit in your work? How do you deal with it?
It is always difficult to pitch new ideas that defy the common understanding of most of the people in the respective area, so it is especially challenging to sell a new product with a startup company. We deal with it by actively working with our prospects and clients to provide them with the benefits of a valuable and differentiable solution to their problem. For example, we believe data and analysis belong to the business, not IT. Therefore, we design our BI product for business professionals and remove IT complexity. We aren’t just trying to convince them to buy another BI product in addition to the many they already have.
Where is data analytics/data science headed in the next few years?
Cloud-native, self-service BI tools will allow business professionals to develop analysis on their own without burdening IT. As a result, analytical thinkers and marketing decision makers will be empowered to bring the data forward by themselves within the decision-making window and disseminate insights across all lines of business in a timely manner.
True cloud-native solutions are inherently without the complexities that IT-centric BI tools have always encountered. No programming, data warehouse, or OLAP component is needed. In fact, very little IT support is ever required at all. The business professional learns it in days and uses it effectively immediately. Cloud-native also means that there is no on premises-based equipment to buy or to configure and therefore no ongoing maintenance cost, which is why new clients are up and running so quickly. There is also no capital investment for an initial software license which can be prohibitive.
Cloud-native, self-service BI tools can do more than just receive, store, and analyze data or build and share reports and dashboards. They can easily offer features that make the analysis results actionable in a centralized and well-organized manner.