Nate Goethel

Technical Writer
April 25, 2022 DataChat Insider

The Future of Analytics: A Q&A with Danny Thompson, EVP of Sales

With the explosion in data access and collection, companies are moving beyond traditional business reporting and towards tailored analytics. Teams across all industries and aspects of business can enhance competitive outcomes with new technologies – such as artificial intelligence techniques like machine learning. In this post, we’ll ask a 20+ year industry veteran about his perspective on the tectonic shifts in business analytics. Danny Thompson joined DataChat in December 2021 as the EVP of Sales.

What were you doing before you came to DataChat? 

I’ve been in sales for more than twenty years in a variety of organizations, including Oracle, Andersen Consulting, JD Edwards, Peoplesoft, and most recently Tableau. The reason I got into technology sales was to help people become more effective in their jobs and help companies become more successful in building shareholder value. I joined Tableau in 2012 when it was still a private company with about 350 employees. Tableau created an innovative approach to visual discovery and analytics. This new software category grew into a successful IPO and eventually Tableau was acquired by Salesforce. I’ve watched the technology landscape transform throughout my career, and I’m excited to see how the analytics market evolves.

What market trends have caught your eye?

Over the last few years, there has been a lot of buzz in the market about artificial intelligence and machine learning. There were interviews of CXOs by the big consulting firms about how these technologies would take businesses to the next level. As consumers, we already see AI in our everyday lives, such as Google Maps and Apple’s FaceID.

How do these trends influence business intelligence?

Traditional business intelligence can only take businesses so far. They really need these advanced technologies to survive, let alone to thrive. In addition, traditional tools are often a patchwork of best-in-breed solutions that are difficult to deploy and even more difficult to integrate with each other. Many business users simply use these platforms as a dashboarding tool to track key performance indicators: good or bad, up or down. 

This is the “what,” as in, “This is what happened.” The “what” is the bare minimum for business intelligence, but companies need to understand the “why,” as in, “Why did that happen?” to be able to take action and change outcomes.

What does the transition to “why” look like to you?

Advanced analytics like machine learning help get us to the “why.” Getting to the “why” requires software but is also a team sport. A company needs people who can handle and analyze the data, build machine learning models, and understand the business enough to ask the right questions. Those people need the machine to help them find patterns and trends in data and feed it back to them so they can use their human intuition—their gut—to make decisions. I see the need for humans and computers to speak the same language so that we can all understand the data journey. DataChat’s Guided English Language is that common language. Talking the same way will empower people to ask more questions – and get more answers.

What are some of the hurdles you see to get to the “why”?

One big hurdle—particularly for large organizations—is the sunk cost invested in tools, training, processes, and organizational structures. They don’t want more tools and extra training – they want to consolidate with existing knowledge. For these organizations, this best-in-breed approach hinders investment in innovative technologies like AI and machine learning – technologies that can reveal the ‘why’ and empower decisions that drive outcomes. For example, past outreach trends can drive marketing campaigns. Or another example, historical equipment performance can negotiate better lease terms.

Another hurdle is the inherent complexity of machine learning techniques. This creates a convoluted journey – navigating a business question through the data assessment, ingestion, manipulation, analysis, and forecasting, across different departments with different data sources and different approaches. The situation needs an all-in-one solution that simplifies the complex and fills the gaps.

What do you think is the ‘secret sauce’ of DataChat?

This question brings me back to my days at Oracle. At that time, the company was on an acquisition track, which meant it was always integrating companies and technologies into the organization. It made the user experience challenging but also meant that the company wasn’t innovating. I had an aha moment when I realized that you’re either integrating or innovating. That idea has stuck with me, and as I thought about the “why” I saw a void in the marketplace. No software vendor offers a single, cohesive analytics and data science platform that can be deployed across an organization. This was a key driver for my decision to join DataChat as I see it filling this void. 

Have you already started thinking about what’s after “why”?

We have a lot of work to do to get to “why”, but I’m always thinking about how to allow knowledge workers to connect with their data and ask questions. Can we make it so simple that it’s automatic? In the consumer space, we’ve grown accustomed to Siri and Alexa on our phones. I think the pinnacle of analytics would be allowing any person to answer business questions in real-time from anywhere, at any time, and on any device without having to locate and wrangle data.

What else do you want people to know?

DataChat is an innovative software company looking to change how people use data in their daily lives. We want to enable a data empowerment mindset. People have great ideas, great questions, and just need a platform to test and execute them.

DataChat is a cohesive analytics platform that uses natural language to make a broad range of data science tools, including data wrangling, preparation, exploration, visualization, and predictive modeling, accessible to everyone to improve business outcomes. Contact us or schedule a demo to learn more about how DataChat can help you improve your business outcomes.

Related Articles

a blue question mark on a pink background
DataChat Insider
Introduction to DataChat: A Q&A with Co-Founder Rogers Jeffrey Leo John

We asked DataChat’s co-founder, Rogers Jeffrey Leo John, to tell us about the origins of the company. What was missing from the marketplace? How has...