Andy Cutler

AI is rewriting the rules for data professionals. Discover the gains, the challenges, and the emerging risks, and learn how to stay relevant and resilient as AI reshapes our industry.

In this session we'll be diving into 3 of the data storage formats that have emerged in recent years and understand how they work. 1. Delta Lake 2. Apache Iceberg 3. Apache Hudi

The Data Lakehouse is hotting up as the go-to cloud Data Warehouse and Analytics methodology. Combining the scale and flexibility of the data lake with the schema enforcement and transactional consistency of data warehouse database systems, the lakehouse pattern brings a huge advantage for organisations with both…

Microsoft Fabric makes developing an end-to-end analytics solution a rewarding experience, removing the hurdles of stitching together multiple cloud services to provide a holistic data platform. However, as easier as this has become we still need to be mindful of what happens when things go wrong...how do we ensure…

When Microsoft first introduced Fabric to the world, a pre-defined set of workloads became available for all types of organisations to use. These included Data Warehousing, Data Engineering using Spark, Realtime ingestion and analysis, Data Integration, and more.

Warehouses form part of the Fabric Data Platform and are a powerful method for processing and storing data ready for delivery to the business. In this 100 minute session we'll be taking a deep dive into Warehouses to understand the SQL Engine and how to build a Fabric Warehouse from the beginning.

The Data Lakehouse is hotting up as the go-to cloud Data Warehouse and Analytics methodology. Combining the scale and flexibility of the data lake with the schema enforcement and transactional consistency of data warehouse database systems, the lakehouse pattern brings a huge advantage for organisations with both complex and large amounts of data. But what underpins lakehouse technology?... In this session we'll be diving into 3 of the data storage formats that have emerged in recent years and understand how they work. 1. Delta Lake 2. Apache Iceberg 3. Apache Hudi We'll discuss the benefits and drawbacks of each format and look at technology platforms and vendors that support these formats. After this session you will have the power of knowledge to deal with the different formats in use with the Data Lakehouse and make an informed decision about the format(s) to use in a data solution.

The Serverless SQL Pools service within Azure Synapse Analytics allows querying CSV, JSON and Parquet data in Azure Storage, Data Lake Gen1/2 and Cosmos DB. With this functionality we are able to create a Logical Data Warehouse over data stored in these systems without moving and loading the data.

Synapse Analytics Serverless SQL Pools and Pipelines are the dream team when it comes to managing big data in Azure Data Lake, this session will take you through the process!