An honest, no-bs, non-salesy conversation about enterprise data management and analytics. This is your 30-minute elixir containing everything interesting about data and metadata management, data catalogs, knowledge graphs, and more. Join Juan Sequeda and Tim Gasper to explore emerging topics and hear from visionary leaders. Visit https://data.world/podcasts/ to watch and participate in the live program.
What do they teach at your Data Science U?
The data science discipline is in a constant state of evolution with new techniques and applications being introduced almost daily. And this journey often begins at institutions of higher learning around the world. Many universities offer bachelors and masters degrees in data science, but are these programs adequately preparing the data professionals of tomorrow?
In this episode, Juan, Tim, and Prof George Fletcher of Eindhoven University of Technology will discuss the state of data science education and explore how these programs can be extended to satisfy industry needs.
Other topics include:
What universities get right and wrong about data science education
What skills we should be teaching that we aren’t today
What should be the mascot at Data Science University?
Power to the Data!
Companies spend an obscene amount of money every year on data and analytics initiatives. And almost all of that spend goes toward applications that employ vastly different data models. Normalizing data structures is a painstaking process that most IT teams are used to by now. But should we normalize normalization?
In this episode, Juan, Tim, and Dave McComb, President of Semantic Arts and author of Software Wasteland and The Data-Centric Revolution, discuss what it takes to shift from an application-centric to a data-centric mindset.
Other topics include:
What it means to be data-centric
How to undo decades of questionable data management practices
Debate: French Revolution vs. American Revolution vs. Beatles Revolution
Building a great data team: Mission (Im)possible
Here’s your mission, should you choose to accept it: Your company is making poor decisions about how to bring its latest product to market. Time is running out, and the company risks missing a unique and lucrative opportunity. You must convince your exec team to stop using gut instinct and start trusting in data.
Step one is building a strong data and analytics team with the right mix of people, process, and technical know-how. In this episode, Juan, Tim, and Patrick Barry, VP of Data and Analytics at SPM Marketing and Communications, discuss what it takes to assemble a team from scratch.
Other topics include:
What roles and skills to prioritize
Why diversity is critical
What things do we wish would self-destruct
Does your data have a ‘born on’ date?
Where does this data come from? Who created it? How has it been used? Like the origins of the universe, there can be quite a mystery surrounding the genesis of your company’s datasets. Understanding data provenance is the first step in answering those critical questions.
Join Tim, Juan, and Professor Deborah McGuiness of Rensselaer Polytechnic Institute, renowned AI scientist and pioneer in provenance research to discuss data provenance and why it matters to you.
In this episode, we discuss:
The origin story and evolution of data provenance
Provenance standards every data person should know
Which fictional character has the best origin story
Identity graph: the new customer 360
What’s the best way to get to know your customers? For most companies the solution is creating a 360 profile using data integration, data warehouse, master data management, and a slew of marketing tools. But there is another option: the Identity Graph.
Join Tim, Juan, and guests Michael Murray and Bret Harper of Wunderman Thompson Data for a look at how and why Identity Graphs are disrupting the company-customer relationship.
In this episode, we’ll discuss what an identity graph is and why you need one, why graph technology is a game changer for understanding customers, and the true identity of St. Patrick and what he might buy if he were alive today.
A modern approach to data transformation
Data warehouses have been around for decades, and we’ve relied on data integration processes like ETL (Extract-Transform-Load) to get the data in. While data warehouses evolved to data lakes and data lakehouses, and ETL became ELT, little else has changed.
This week’s special guest is Drew Banin, co-founder of Fishtown Analytics. They’re the team behind the open source tool Data Build Tool (better known as dbt), and for disrupting the data transformation process (the T in ETL).
Discussion topics include how to build a modern tech stack for your data-driven business, what actually started the dbt revolution, and (of course, obviously) if you could transform into any animal on the planet, what would it be and why?