SQLBits encompasses everything from in-depth technical immersions to the enhancement of valuable soft skills. The full agenda will be announced in the spring; in the meantime check out the timetable and content we cover below.
2024 Training Days
Presenting 2024’s selection of training days, encompassing a deep dive into a range of subjects with some of the best data trainers in the world.
- 08:00 Registration opens and breakfast served.
- All training days run simultaneously across the venue from 09:00 – 17:00 with co-ordinated breaks.
- All training days include regular refreshment breaks and a lunch stop to rest, recharge, and chat to fellow delegates.
- No evening events planned, but if you’re staying over the night beforehand, why not join us in the Aviator on Monday night to meet the training day speakers for an informal drinks reception.
Data Transformation and Integration
Data Engineering with Databricks
Description
So you’ve heard of Databricks, but after setting up a notebook and writing some code you’re still not sure what the fuss is all about.
Yes you’ve heard it’s Spark, but then there’s this Delta thing that’s both a data lake and a data warehouse (isn’t that what Iceberg is?). And then Unity Catalog, which does more than just catalog data, it does access management but even surprising things like optimise your data and programmatic access to lineage and billing?
But then serverless came out and now you don’t even have to learn Spark? And of course there’s a bunch of AI stuff to use or create yourself.
So why not spend a single day learning the details of what Databricks does, and how it could make you look like a rockstar Data Engineer.
Overview
This hands on course will give you the building blocks to become a skilled Data Engineer in Databricks, allowing you to build real time pipelines, optimised workloads from the getgo and scalable architectures.
The instructor is Holly Smith, who spent half a decade delivering formidable projects for Databricks’ own consulting team.
Outline
ETL with Spark SQL and Delta
Incremental Data Processing with Structured Streaming
Medallion Architecture
Task Orchestration with Databricks Workflows
Unity Catalog and System Tables
AMA with Databricks experts
Yes you’ve heard it’s Spark, but then there’s this Delta thing that’s both a data lake and a data warehouse (isn’t that what Iceberg is?). And then Unity Catalog, which does more than just catalog data, it does access management but even surprising things like optimise your data and programmatic access to lineage and billing?
But then serverless came out and now you don’t even have to learn Spark? And of course there’s a bunch of AI stuff to use or create yourself.
So why not spend a single day learning the details of what Databricks does, and how it could make you look like a rockstar Data Engineer.
Overview
This hands on course will give you the building blocks to become a skilled Data Engineer in Databricks, allowing you to build real time pipelines, optimised workloads from the getgo and scalable architectures.
The instructor is Holly Smith, who spent half a decade delivering formidable projects for Databricks’ own consulting team.
Outline
ETL with Spark SQL and Delta
Incremental Data Processing with Structured Streaming
Medallion Architecture
Task Orchestration with Databricks Workflows
Unity Catalog and System Tables
AMA with Databricks experts
Learning Objectives
You will leave with the Databricks notebooks used in the class, the slides used for theory sections, $400 of compute to try in your own Databricks Express account.
Things I will need
A laptop that can run Google Chrome and access to the internet. It’s probably best to use your personal laptop if your work laptop is locked down.
You will need basic knowledge of SQL up to and including joins, DML statements like Merge. Basic python variables, functions and control flow is preferred.
Experience with cloud Data Engineering practices using virtual machines, object storage, identity management and metastores.
You will need basic knowledge of SQL up to and including joins, DML statements like Merge. Basic python variables, functions and control flow is preferred.
Experience with cloud Data Engineering practices using virtual machines, object storage, identity management and metastores.
Tech Covered
Python, Spark, Data Bricks, Data Transformation and Integration, Grounded in Reality, Inspirational