Julia Førde
Datbricks lead - Managing consultant, Amesto Analytics
Oslo, Norway
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Experienced professional specializing in Business Intelligence and Data Warehousing within the Microsoft ecosystem with 5 years experience .
Passionate about leveraging technology to solve complex business challenges, particularly drawn to the capabilities of Azure Databricks. Throughout my journey, I've had the privilege of seamlessly transitioning between data engineering and architect roles in various projects. This experience has equipped me with a versatile skill set, allowing me to contribute effectively to crafting end-to-end solutions. With a background in collaborative consulting roles across sectors, I bring a pragmatic approach to solving problems and driving success.
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Implementing notebook templates in Azure Databricks
Join me for a technical session focused on improving the medallion architecture in Azure Databricks notebooks with template-based notebooks. This session shows how the use of templates can significantly improve data quality, productivity, and agility.
The session will include a practical demo of a template and a technical dive into the core components of the templates: parametrization, naming & predefined SQL statements
We will also take a look on how you can organize you unity catalog.
The templates in this session are focused on source data from the common data model in Dynamics365, but the strategies and methods presented in this session can be used with other sources as well.
Managing the Common Data Model in Azure Data Lake Through Azure Synapse Link
This presentation examines the structure of the Common Data Model (CDM) in Azure Data Lake when extracting data from Dynamics 365 (D365) using Azure Synapse Link, based on a real-life project.
Key topics will include:
CDM Organization in Azure Data Lake: Details on how files and folders are arranged in the Data Lake, including the use of change files for incremental data loads.
Technical Columns from Synapse Link: An overview of important technical columns generated during the export process and their role in ensuring data integrity.
Loading Strategies for Lakehouse Architectures: Effective methods for loading data into lakehouse environments such as Databricks and Microsoft Fabric.
Lessons Learned: Key insights and challenges faced during the project, providing practical takeaways for implementation.
This session will provide a clear understanding of the CDM's organization and practical strategies for using Azure Synapse Link in data management and analysis.
Databricks an introduction
Curious about Databricks and what it can do for you? In this session, we’ll break down the basics and get you up to speed. We’ll cover:
What Databricks Is: An overview of the platform and its core capabilities.
Key Features: A look at the tools and functionalities that make Databricks stand out.
How It Works: A simple explanation of how Databricks integrates with your existing data workflows.
Why Databricks: Understanding the benefits and why it might be the right choice for your needs.
Whether you're new to data engineering or just curious about the platform, this is the session for You!
Julia Førde
Datbricks lead - Managing consultant, Amesto Analytics
Oslo, Norway
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