Power BI #5: Power BI and Synapse for data Engineering & analytics at scale [Webinar]
Azure synapse - your Datawarehouse, data lake, data pipelines, analytics and much more in one service. It integrates seamlessly with Power BI - at this webinar you will learn how.
About the webinar
Azure synapse - your Datawarehouse, data lake, data pipelines, analytics and much more in one service. It integrates seamlessly with Power BI, AI from cognitive services and of course azure machine learning service, and it has similar data connectors. On top of this, you can work with telemetry data (IOT) and use Apache spark and SQL engines, while having all the data languages of the data department; T-SQL, KQL, Python, Spark SQL, Scala, .Net, ect.
Wow, that's a lot, it really is the entire data department.
So how do you get started on this journey of a unified experience to ingest, explore, prepare, transform, manage, and serve data for immediate BI and machine learning needs?
We start by taking a look at a synapse workspace, then dive into the SQL pool and the data explorer pool, so now we are ready for the data lake, before we get back up on the dry again with some Apache spark, so we can orchestrate some pipelines, before we finally visualize all this amazing data in Power BI.
We will be covering a lot in a short time, only dipping our toes on many subjects, therefore we will of course include plenty of links to learning resources for longer deep dives.
Contents with agenda
- Create and setup a Synapse workspace
- Analyze using a serverless SQL pool
- Analyze using a dedicated SQL pool
- Analyze using a Data Explorer pool
- Analyze data in a storage account (data lake)
- Analyze using Apache Spark
- Orchestrate with pipelines
- Visualize data with Power BI
Speaker
Emilie Lundblad,
Managing Director of Data & AI at Amesto Nextbridge
Speaker at Make Data Smart & Genesis Conference
12 Microsoft Data & AI certifications
Minor in Machine learning & AI from MIT (Guest lecturer fall 2022)
Writing master thesis in AI on Executive master of IT Management at ITU (Guest lecturer fall 2022)
Candidate in quantitative finance & econometrics
12+ years' experience with data & analytics, 6 of them in Data & AI consulting.
Startup entrepreneur & data nerd.
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