Introducing AI and Data Democratization Live: A Letter from the Editor

For years business gurus preached that “you can’t improve what you can’t measure.” Little did they know that by 2021, “measurement” would no longer be the problem. These days, companies are generating and collecting more data than ever, yet only a select few are using it in new, creative ways that truly drive strategic value and competitive advantage. 

The performance gap between those companies who are effectively using data as a strategic asset and those who are not is rapidly growing. In fact, according to a recent study by Accenture, data-driven organizations, on average, have an annual growth rate of over 30%, significantly outpacing the rest of the market. 

However, in order to become a data-driven or data-centric enterprise, whereby data is treated as a mission critical asset, organizations must first embrace data democratization.

The goal of data democratization is to ensure that everyone across an enterprise has unfettered access to data analytics and data-driven insights. In addition to the tools used to do so, such as self-service analytics and data lakes, “data democratization” also encompasses strategies for enhancing data literacy amongst non-technical employees. The ultimate goal is to unleash the power of so-called “citizen data scientists,” non-technical workers that are capable of understanding, actioning and, to a certain extent, developing their own data-driven insights. 

In other words, data democratization aims to ensure that all employees are equipped with the tools and knowledge necessary to use data strategically - in a way that enhances decision making and drives growth. 

One of the top benefits of data democratization is improved Artificial Intelligence (AI) and Machine Learning (ML). Not only does data democratization reduce the likelihood of AI bias, it paves the way for democratized AI whereby, with the help of low-code solutions, companies can build armies of “citizen developers” capable of producing their own AI-powered applications. 

This is why we’re so excited to be hosting the virtual event, AI & Data Democratization Live April 27-28. Over the course of two days, we’ll explore the end-to-end AI and data democratization process in its entirety, showcasing a constellation of key enabling strategies and technologies along the way. The goal is to endow participants with the foundational knowledge necessary to unleash wide-spread but secure access to enterprise intelligence and low-code AI development tools. 

For example, we have Adri Purkayastha, Global Head of AI and Digital Risk Analytics, BNP Paribas sharing how his organization built its Enterprise Data Nerve Center to fuel advanced analytics and AI innovation. From sharing a high-level overview of BNP Paribas’ state-of-the-art data architecture to discussing how they implemented self-service analytics, Mr. Purkayastha will provide a rare look into the full, end-to-end data democratization ecosystem. 

And that’s not all. We also have joining us as speakers:

• Catherine Lopes, Head of Data Strategy & Analytics, ME Bank presenting on Building An End-To-End Analytics Strategy
• Kate Carruthers, Chief Data & Analytics Officer, University of New South Wales presenting on Utilizing ML To Detect Historical Patterns To Then Detect Real Time Patterns
• Timo Etzold, Senior Data Consultant, Continental presenting on Mapping Out a Data Vision
• And more to come!

Our hope is that companies of all sizes and maturity levels walk away feeling inspired to jumpstart their own data democratization journey. Register now for AI & Data Democratization Live.

We look forward to seeing you there,

Managing Editor, AI, Data & Analytics Network