A lap around Azure Data platform

Microsoft Azure cloud platform provides a number of options for storing all kinds of Data big or small, relational or NoSQL, and performing actions on Data. With so many available choices (IAAS and PAAS) it can be difficult to know the right Azure service to use for a given scenario. This session is about discovering the options of storing data in Azure and processing them. The talk will also touch on some associated services to build a streaming data pipeline. A reference architecture for big data analytics pipeline in Azure will be explained in the talk. The architecture will have data ingestion, preparation, real-time and batch analysis, publication and consumption stages. It is a whirlwind tour but I promise you will come out exhilarated at the end of the talk.

 
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Outline/structure of the Session

The content would be primarily through slides. There will a live view of some services in Azure management portal.

I will elaborate the various data related services in Azure their key features.

  • The following Azure services will be covered:
  • Azure Blob Storage
  • Azure Table Storage
  • Azure SQL DB
  • Azure SQL on VM (IAAS)
  • Azure Data Lake Store
  • Azure CosmosDB
  • Azure HDInsight
  • Azure Redis Cache
  • Azure Event Hub
  • Azure Stream Analytics
  • Azure Data Factory
  • Azure Machine Learning
  • Azure Cognitive Services
  • Power BI

Learning Outcome

  • Guidance provided for developers, architects and data analysts in choosing the right services and tools for data processing in Azure.
  • This is a session for all who wants to work with data small or big in Azure.
  • Azure data related services are perhaps not as well known as AWS or open source options to many and I hope they can understand what Azure has to offer in this space.

Target Audience

Architects, Developers, and Data Analysts

Prerequisite

I am expecting the participant to have some experience in data related technology. Knowledge of big data terms and prior exposure to AWS or Azure will be helpful.

schedule Submitted 5 months ago

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