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Data Science and Analytics: Real-World Experience from Diverse voices in the field Jennifer Stirrup (She/Hers)
In this session, we will cut through the marketing buzzwords to share experiences, tips, and tricks on how to be successful with Data Science and Analytics in the real world. Tune in to hear the team share real-world experience and get takeaways from industry insiders on real projects with impact. We will also discuss the ethics and fairness of Data Science and Analytics projects and how we can be more inclusive from a technology, people, and process standpoint.
The video is not available to view online.
From Housekeeping to Data Engineer - My journey to find my passion Jean Joseph
Only the curious will learn and only the resolute overcome the obstacles to learning.
Implementing a Data Quality Framework in Purview Ust Oldfield
Building a Data Quality implementation in Purview using the Glossary and Databricks
Leveraging Apache Spark for Efficient Data Encryption at Scale Daniel Harrington
This session will discuss a custom solution we have built to solve the problem of row level encryption in a highly complex data lake.
Optimisation in Business Luke Menzies
The art of choosing the perfect set of actions to reach the ultimate value that can be achieved.
Overview of Azure Synapse Analytics Dave Ruijter
Curious what Azure Synapse Analytics brings to the table? Bring your scuba gear, as we take a dive and explore everything it has to offer!
So you want to be a Data Engineer? Michael Robson
An introduction to becoming a Data Engineer, Anna, Mikey and Ust will introduce the technology stack, tools and development skills needed for data engineering and show you how and where to go to learn them. We'll also show you how the skills you already have can kickstart your journey to becoming a Data Engineer.
What makes Databricks a powerful Machine Learning tool? Liam Doyle
This session is designed to explore some of the powerful features that made Databricks the leader in the Gartner 2021 Quadrant for Data Science and Machine Learning.
The video is not available to view online.
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