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This meetup is all about data. From small to big, SQL to NoSQL, BI, reports, development, design, and more. If you're a developer, DBA, BI expert, data analyst, data scientist, or data engineer, then this is a great place to meet and learn.

If you would like to present a session in one of our meetups, then please submit your session here: https://sessionize.com/israeli-data-platform-meetup/

Bevorstehende Events (2)

Explore Big Data with Serverless SQL Pool - Part 2

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Agenda (Israel Time)

  • 12:00-12:15 – Opening, Announcements, and More...
  • 12:15-13:15 – Explore Big Data with Serverless SQL Pool – Part 2
  • 13:15-13:30 – Q&A and Open Discussion

Session: Explore Big Data with Serverless SQL Pool – Part 2 – Guy Glantser (60 Minutes, Hebrew)

You are a data analyst or a DBA with strong SQL skills. You are used to querying data in SQL Server or Azure SQL. The next level in your career is to learn how to explore big data in other platforms and formats, such as parquet files in the data lake.

You don't have to learn new technologies, such as Spark and Python. You can leverage your existing SQL skills and advance your career in a short time. With the Serverless SQL Pool in Azure Synapse Analytics, you can query data stored in various file formats in the data lake as if it was a regular table in a relational database.

In this session, we will walk through a demo, from extracting data to parquet files in the data lake, through setting up Azure Synapse Analytics and all the required components, to exploring the data with the Serverless SQL Pool.

Architectural Decisions for a Successful Power BI Implementation

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Agenda (Israel Time)

  • 16:00-16:45 – Opening, Announcements, and More...
  • 16:45-17:45 – Architectural Decisions for a Successful Power BI Implementation
  • 17:45-18:00 – Q&A and Open Discussion

Session: Architectural Decisions for a Successful Power BI Implementation – Guy Glantser (60 Minutes, Hebrew)

Before implementing Power BI, you should ask some important questions, understand the requirements, and then take the right decisions accordingly.

Here are some important questions to ask:

  • What is the expected size of the data model?
  • How many users are expected to use it?
  • What is the data latency that you can afford?

Once you have the answers to these (and many other) questions, you will be able to take the right architectural decisions. Here are some examples:

  • Which licensing model is best appropriate?
  • Which connection type should we use? Import, DirectQuery, or Live?
  • Should we consider Power BI Embedded?

Taking the right decisions upfront will ensure a successful implementation, make your users happy, and save you money.

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