22-25 April 2026 
André Kamman
André is a Data Engineer and architect mostly in Azure. He has done a lot of DBA work on 1000’s of SQL Servers where he discovered his love for Powershell, architecting data solutions, building and tuning ETL processes (with BIML), and even implementing PDW. Having to wrangle a lot of data he's using Python, SparkSQL in Azure Databricks, Data Factory, dbt and Power BI as well these days. André is a Data Platform MPV since 2009, Dutch Microsoft Data Platform Meetup lead, organiser of Data Saturday Holland and Data & BI track volunteer for Techorama Holland
André Kamman's Sessions
FinOps, how data engineers get their cloud cost under controlSQLBits 2023
Managing cloud cost is no longer a "management approves the budget" type of thing. Cloud Engineers need to architecht their solutions in such a way that cost can be kept under control. This is not a one time thing. Monitoring, automatic downsizing, re-factoring are all parts of the yearly tasks of any cloud team. We'll discuss theory, techniques, best practices and lessons learned.
Generate test data quick, easy and lots of it with the Databricks Labs Data GeneratorSQLBits 2023
We're not supposed to use production in dev right! But generating proper test data is not easy, get's even harder when you need quite a lot of it. I generate Terabytes of it, and without much trouble. Let me show you how!
Keynote by The CommunitySQLBits 2023
Ben and Rob have found some wonderful folk to actually do the important parts of the community keynote. on the theme of
How to be a nonpassive member of the data community
D, E and I PanelSQLBits 2023
Come and meet the group working hard to make SQLBits as diverse and inclusive as it can be
Building your first Metadata Driven Azure Data FactorySQLBits 2022
Let's unleash the true power of ADF, it's ability to dynamically inject metadata almost anywhere. No complicated frameworks in this session, I'll show you some simple but very powerful examples.
Looking under the hood of the parquet formatSQLBits 2022
Understanding how the parquet format works helps with understanding why it can help you retreive your data fast, or perhaps why you struggle to get the desired performance out of your design.
FinOps, how data engineers get their cloud cost under controlSQLBits 2023
Managing cloud cost is no longer a "management approves the budget" type of thing. Cloud Engineers need to architecht their solutions in such a way that cost can be kept under control. This is not a one time thing. Monitoring, automatic downsizing, re-factoring are all parts of the yearly tasks of any cloud team. We'll discuss theory, techniques, best practices and lessons learned.
Generate test data quick, easy and lots of it with the Databricks Labs Data GeneratorSQLBits 2023
We're not supposed to use production in dev right! But generating proper test data is not easy, get's even harder when you need quite a lot of it. I generate Terabytes of it, and without much trouble. Let me show you how!
Keynote by The CommunitySQLBits 2023
Ben and Rob have found some wonderful folk to actually do the important parts of the community keynote. on the theme of
How to be a nonpassive member of the data community
D, E and I PanelSQLBits 2023
Come and meet the group working hard to make SQLBits as diverse and inclusive as it can be
Building your first Metadata Driven Azure Data FactorySQLBits 2022
Let's unleash the true power of ADF, it's ability to dynamically inject metadata almost anywhere. No complicated frameworks in this session, I'll show you some simple but very powerful examples.
Looking under the hood of the parquet formatSQLBits 2022
Understanding how the parquet format works helps with understanding why it can help you retreive your data fast, or perhaps why you struggle to get the desired performance out of your design.
My top tips for continuous learning without spending every minute of your free time on itSQLBits 2022
I'm a Data Engineer and work mostly in the cloud, the tech stack evolves so quickly that trying keeping up can seem scary, or even stressful. I'll share my top tips on how I try to handle continuous learning, while not hiding in my home office forever. Or even worse, burn out.
Schema Madness, handling (incompatible) schema changes in incoming json files with DatabricksSQLBits 2022
Databricks has a schema evolution feature which can automatically handle schema changes. This seems amazing in theory, but there are quite a bit of practical gotcha's I've run into. This is a notes-from-the-field demo rich session where I show you what problems I ran into and how to fix them.
The stress of many options, which ETL and DWH engines do you combine and why?SQLBits 2022
Do you use Data Factory, Databricks, Synapse, (serverless, or dedicated?), Snowflake, SQLDB, DBT, Debezium, Fivetran, Python, Functions? The list seems endless and continuously evolving. Join us for an open discussion where we debate, amongst ourselves and with you, about what worked for us and what we perhaps would have done differently knowing what we know now.
Why would I use DBT?SQLBits 2022
DBT, or Data Build Tool seems to get a lot of traction lately. Let's look at this thing together. How does it work, where would it fit in a data warehouse stack and of course, is this something you or I would use?