In a recent conversation with data warehousing legend Bill Inmon, I learned about a new way to structure your data warehouse and self-service BI environment called the Unified Star Schema. The Unified Star Schema is potentially a small revolution for data analysts and business users as it allows them to easily join tables in a data warehouse or BI platform through a bridge. This gives users the ability to spend time and effort on discovering insights rather than dealing with data connectivity challenges and joining pitfalls. Behind this deceptively simple and ingenious invention is author and data modelling innovator Francesco Puppini. Francesco and Bill have co-written the book ‘The Unified Star Schema: An Agile and Resilient Approach to Data Warehouse and Analytics Design’ to allow data modellers around the world to take advantage of the Unified Star Schema and its possibilities. Listen to this episode of Leaders of Analytics, where we explore: What the Unified Star Schema is and why we need itHow Francesco came up with the concept of the USSReal-life examples of how to use the USSThe benefits of a USS over a traditional star schema galaxyHow Francesco sees the USS and data warehousing evolving in the next 5-10 years to keep up with new demands in data science and AI, and much more.Connect with Francesco Francesco on Linkedin: https://www.linkedin.com/in/francescopuppini/ Francesco's book on the USS: https://www.goodreads.com/author/show/20792240.Francesco_Puppini

An estimated 80 to 90 percent of the data in an enterprise is text. Sadly, this rich information is mostly neglected for analytical purposes. Textual data is typically full of information, but also very complex to interpret computationally and statistically. Why? Because textual data is both content and context. The same words and sentences can have very different meanings depending on the context. Textual data is truly a goldmine, but how can we mine it without being digital superpowers like Google, Microsoft or Facebook? To answer this question and many more relating to interpretation of textual data, I recently spoke to Bill Inmon. Bill is the Founder, Chairman and CEO of Forest Rim Technology and author of more than 60 books on data warehousing. He is often described as the Father of Data Warehousing due to his pioneering efforts in making data and data technologies available to organisations across all industries and sizes. In this episode of Leaders of Analytics, we discuss: How Bill became the Father of Data WarehousingThe history of data warehousing and the most exciting developments in this space todayThe typical challenges holding us back from extracting value from textual dataThe concept of the “Textual ETL” and it’s benefits over other text data storage and analytics approachesWhy NLP is not the best approach for textual data analyticsThe biggest opportunities for textual analytics today and in the future, and much more.Connect with Bill: Forest Rim Technnology: https://www.forestrimtech.com/ Bill on LinkedIn: https://www.linkedin.com/in/billinmon/