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Are you planning a migrating of your data platform to Azure Synapse Analytics? Is it currently based on Azure Databricks, Azure Data Factory, and Azure Data Lake Storage? Make sure to grab these 10 tips! We'll talk about Spark compatibilities, orchestration pitfalls and solution deployment differences.
A guide to available services and solutions for timeseries data
In this demo-filled session we get an overview of Azure Data Explorer, which is a fast, fully managed data analytics service for real-time analysis on large volumes of data streaming from applications, websites, IoT devices, and more. We look at how to ingest data, as well as query in real-time against billions of rows with sub-second latency.
Using open source apache nifi to integrate and ingest data at scale
In this session we will introduce Azure Container Apps and understand how it can be used as a simple and cost-effective way to host applications in Azure
Data Engineer is an exciting and rewarding role. This session will describe a data engineer's responsibilities and give an overview of the skills needed to be an Azure Data Engineer.
Overview to some of the more popular Azure Data Engineering services used to analyze data
I will show a few challenges while deploying Azure Data Factory and solution for them.
This session will introduce you to "What and why you should care about", and discuss "how" to apply the Security and Privacy lens for Big Data on AWS.
Find out everything you need to know to get started with Azure Cosmos DB in 20 minutes or less.
I'll explain the current popular data architectures: Data Lakehouse, Data Mesh, and Data Fabric
Session covering table distributions, partitioning , RSC and materialised views.
Building a Data Quality implementation in Purview using the Glossary and Databricks
Hybrid Transactional Analytical Processing solve the age old problem of integrating operational processes with analytical capabilities within a single system. Find out what they're and how they deliver value
In this demo filled session we see how we use ksqlDB to gain real-time insights into streaming data. We look at push/pull queries, User Defined Functions, tables and streams.
What happens when you mix one rapidly-changing startup, one data analyst, one data engineer, and one hypothesis that Azure Synapse Analytics could be the right tool of choice?
This session will discuss a custom solution we have built to solve the problem of row level encryption in a highly complex data lake.
Join me to learn how to migrate a traditional DW transformation process to Spark/Scala based platform and reuse existed experience
Curious what Azure Synapse Analytics brings to the table? Bring your scuba gear, as we take a dive and explore everything it has to offer!
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