Managers, Developers and Data Scientists who are contemplating the future of Azure Data Analytics
Technology changes quickly – patterns and approaches less so. As people move towards the cloud, there are clear benefits of adopting a distributed cloud architecture employing a range of disparate tools. As this evolves, the patterns that were designed for single box solutions should be challenged.
This session will take you through the pattern known as the Lambda architecture, a reference pattern for building data analytics systems that can handle any combination of data velocity, variety and volume. The session will outline the set of tools and integration points that can underpin the approach. Do you need to build out real-time reporting systems? Or crunch through petabytes of data? Or perhaps you are adopting a cloud architecture and simply want to make sure it can handle anything the future throws at it? Whether you’re dealing with Gigabytes or Petabyes, Daily Loads or Data Streaming – This session is for you.
We will follow the movement of data through batch and speed layers via Azure Data Lake Store & Analytics, Data Factory, SQL Datawarehouse and Streaming Analytics, before looking briefly at Azure Analysis Services with PowerBI. This is a largely theory-based session to prime you for the future.
Why I Want to Present This Session:
It’s an architecture session – which isn’t really the norm for these conferences – but the way Azure is going, there are hundreds of options, different ways of achieving the same goal. For those who are confused by the myriad options around, I want to cut through the hype and clearly lay out a simple approach that works for loads of different scenarios!
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