Synapse Analytics 1-day Workshop

pmOne AG

Synapse Analytics is Microsoft's big data-ready analytics solution for building the modern DWH in the cloud. In this 1-day WKS, we design together your individual architecture with Synapse Analytics

Azure Synapse Analytics is the new data analytics service from Microsoft that implements data consolidation for both the modern data warehouse and big data applications. Synapse Analytics combines a wide variety of tools and technologies under one interface for this purpose. Because of the multitude of building blocks that need to be linked together for creating a POC with Synapse, in this workshop we will jointly select the right components for your personal use case.
For example, we will look at your data sources, available Azure integration services and storage methods to integrate your data into Synapse Analytics in a targeted way. We will also give you a brief overview of the visualization and reporting capabilities with Power BI to perform ad-hoc evaluations, real-time reporting, or to integrate AI into your business processes.
This 1-day workshop will help you make an informed technology decision. In addition, the knowledge gained will enable business users to create better business concepts and specifications for modernizing their own system landscape.
Agenda: In this one-day workshop, we will jointly select the right components for your personal use case, which should be tested in a downstream POC. Based on your requirements and available data sources, we will create

  1. a first plan for data integration, e.g., using Azure Data Factory,
  2. an architecture blueprint for Synapse Analytics and
  3. a data security battle card to secure the Azure-based platform from unwanted access with Azure Security.
In times of limited contact, the session can also be conducted as a virtual whiteboard session. In this case, we recommend splitting into two half days.
Process of the service: The workshop has a dedicated focus on Azure Synapse Analytics. Therefore, no individual cost or runtime estimates can be made for the data loads. Similarly, predictions for user request response times are not possible.