Johan Ludvig Brattås
Suffers from chronic curiosity
Oslo, Norway
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Johan Ludvig Brattås is a director at Deloitte, and a dedicated community guy. He has worked with MS SQL server since late 1999, mostly with BI in one form or another. Since 2015, most of his work has been in the cloud working on data platform services such as Snowflake, Databricks and Synapse.
Combining his passion for MS SQL Server with his passion for sharing knowledge, he started speaking at various events in the SQL Community. This is also a way to give back to the community for all the things he has learned over the years. When not working, Johan Ludvig either spends his time with his kids, playing with new technology or teaching coeliacs how to bake glutenfree food.
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An introduction to Snowflake - the data cloud
Snowflake has grown to become a huge success worldwide and one of the main contenders for modern analytics solutions.
But why is it a data platform? And exactly how can it fit into your data landscape?
We will look at the different parts of the Snowflake offering and how they might fit into the data landscape.
What are Snowflakes strengths? And what are the weaknesses?
Azure Data Explorer - the new star in your data platform
Azure Data Explorer is a powerful timeseries database, but it is not the most well known analytical service in Azure.
But if you are using timeseries data at all - from IOT devices or otherwise - this service should be considered.
And with the powerful integrations built into it, it can quickly become your goto analytical service alltogether.
Join me in this session to learn more!
Don't cross the streams! A closer look at Stream Analytics
Azure is ready to recieve all your event- and devicedata for storage and analysis.
But which options in the Azure IoT portfolio should you use to recieve and manage your data?
In this session I will explain the different options in the Azure IoT portfolio, take a closer look at how they work and what this means for you.
Furthermore, I will take a closer look at the Azure Stream Analytics (ASA) language.
You will learn how to develop both simple and complex ASA queries, and how to debug.
We will look at the possibilities, limitations and pitfalls in the Azure Stream Analytics language.
And finally look at the different input and output choices and when to use which one. This includes a look at how to build a live stream dashboard with Stream Analytics data in PowerBI.
The session is based on real world project experiences and will use real world data in the demos.
Data Mesh - The emperor’s new clothes…
…or the best original idea since the invention of sliced bread?
In this session Johan and Rune will presents arguments from both sides and discuss why Data Mesh is the new way forward… or just the same old stuff in a different wrapping.
We will further discuss how the current cloud toolset can be used in a “Data Mesh-way”… or just how it should be used anyways using the terms, methods and practices we know from before.
Walking away from this session we hope we have clarified for you:
- What is Data Mesh?
- Why is Data Mesh a great idea… or not so great?
- How can we do modern data platforming the “Data Mesh-way”… or not?
Welcome to 60 minutes of enlightenment…?
Creating an modern data platform in the cloud
Planning on creating a new data platform? The term "Data Platform" is popular, but what exactly is it? And what do you need to think about when designing and creating your own data platform?
This session will take you through what a data platform is, and how to build one on Azure.
The Battle of Cloud Data Warehouses: Snowflake, Databricks, Synapse, and More
Gartner claimed the death of data warehousing a few years ago. They where wrong. But the cloud data warehouse (or should I say lakehouse?) have some twists to the traditional on-premises warehouses. One of them is the amount of data in play, another is the various new services you can choose to combine into your new data warehouse. Snowflake, Databricks, Synapse, Redshift AQUA and what about Big Query? Let's take a look on the role the data warehousing service plays in your modern cloud data platform.
Building your lakehouse on Synapse
No, not that kind of lakehouse...
The data lakehouse architecture launched launched by Databricks a few years ago has become a viable solution for modern data platforms, increasingly so with the string of new features released from Databricks lately. But the data lakehouse concept can also be fully implemented using Azure Synapse. So join me in this session to understand what the data lakehouse is, and how to make one using Databricks and Synapse!
Building trust in your data. Why data governance is the key to success.
Data governance is seen as boring and something you don't really need. But it is in fact the key to success for your data platform. As the amount of data sources, as well as the size of the data from the various sources increases - how can your users know what data is available? Or where to find it and what state it is in? When your users trust the data you deliver, they will use what you develop.
Another aspect to that trust is personal identifiable information - can citizens trust that you keep their data safe and respect their privacy?
This session will show you how to establish both kinds of trust, using Azure native tooling as well as third-party tools. But most importantly - tips on methodology, routines and people!
Azure Synapse + Power BI + Purview = True
Microsoft has launched a lot of servicess in the data and analytics space the last years. And it has become pretty clear that their vision for this space is encompassing and solid. Join me in this session to see why this combination of services and capabilities puts them ahead of the competition.
There is also a discussion on low code/no code vs full code...
An introduction to Azure Cloud Adoption Framework
The Azure Cloud Adoption Framework (CAF) is a set of guidance and best practices from Microsoft.
It comes with reccomendations as well as sample ARM templates on how to establish various sized Azure tenants, subscriptions and policies.
CAF can come across as a bit too much to handle for smaller organizations.
And as data professionals, we rarely deal with infrastructure as code or think too much about networking and so on.
But there is so much in CAF we as data professionals can use in our projects.
In september 2022, Microsoft even released the Data Management and Analytics scenario for CAF.
And while this is aimed at large organizations (Enterprise Scale), the guidance and the best practices contains loads of useful information for companies of all sizes.
Data Platform Next Step 2024 Sessionize Event
Data Point Prague Sessionize Event
Data Saturday Stockholm 2024 Sessionize Event
SQLBits 2024 - General Sessions Sessionize Event
Fabric February 2024 Sessionize Event
New Stars of Data Speaker Improvement Library Sessionize Event
Data Saturday Slovenia 2023 Sessionize Event
SQL Saturday Oregon/SW Washington 2023 Sessionize Event
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dataMinds Connect 2023 Sessionize Event
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dataMinds Connect 2022 Sessionize Event
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Data Toboggan - Cool Runnings 2022 Sessionize Event
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SQLDay 2022 Sessionize Event
Global Azure Norway 2022 Sessionize Event
MVPDagen 2021 Sessionize Event
dataMinds Connect 2021 Sessionize Event
DataMinutes #1 Sessionize Event
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TheCloudFirst Sessionize Event
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Data Architecture Day 2020 Sessionize Event
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DATA:Scotland 2019 Sessionize Event
DataGrillen 2019 Sessionize Event
Data in Devon 2019 Sessionize Event
Intelligent Cloud Conference 2018 Sessionize Event
Johan Ludvig Brattås
Suffers from chronic curiosity
Oslo, Norway
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