Azure Synapse Analytics Boot Camp

Instructor-Led Training / Boot camp / Data & AI

Azure Synapse is an end-to-end data analytics platform that combines SQL data warehousing, big data analytics, ML, and data integration into a single integrated environment. Synapse empowers users to gain quick access and insights across all of their data, enabling a whole new level of performance and scale that is simply unmatched in the industry.

Solliance is at the forefront of Azure Synapse expertise. Since months before its release, we have been working with Synapse, collaborating with the Microsoft engineering team to test and document new functionality and train internal Microsoft FTEs and external partners in an in-depth, technical boot camp-style format.

We can bring this same training experience to your organization with our Azure Synapse Technical Boot Camp.

Throughout an intensive two to four-day live experience, your learners will hear presentations, participate in discussions and group activities, and complete hands-on labs. We also offer a level-400 hackathon-style challenge day. Our world-class coaches are focused on helping your team build and implement critical skills needed to deliver engagements with customers.

  • Identify the major Synapse Analytics components
  • Design, optimize, and secure a file system within ADLS Gen2
  • Load and transform data using Apache Spark, serverless SQL pools, dedicated SQL pools, mapping dataflows, and integration pipelines
  • Discern which Azure Synapse Analytics component to use for specific data engineering scenarios
  • Implement optimization strategizes for the data warehouse using a SQL-based approach in Azure Synapse Analytics
  • Apply security concepts including row-level security, object-level security, column-level security, sensitive data discovery and classification, and access controls to a customer scenario
  • Use Synapse notebooks with Apache Spark to train and serialize machine learning models for SQL-based predictions
  • Train and operationalize models with an integrated Azure Machine Learning workspace
  • Monitor activities within Synapse Studio

Bootcamp modules

Pick and choose the modules that are most important to your organization. Each module equates to a single 7-hour live training day.

1. Synapse Overview & Data Engineering

This module is foundational. As such, we recommend that you start with this in any configuration.

This module starts with a high-level overview of Azure Synapse Analytics, builds upon the attendees’ existing skill set, and teaches the importance of proper data loading for cloud analytics solutions. These skills are critical foundations for all data engineering tasks that follow.

By the end of the day, learners will be able to:

  • Identify the major Synapse Analytics components
  • Design, optimize, and secure a file system within ADLS Gen2
  • Load and transform data using Apache Spark, serverless SQL pools, dedicated SQL pools, mapping dataflows, and integration pipelines
  • Discern which Azure Synapse Analytics component to use for specific data engineering scenarios

Learning these foundations allows us to transition into:

  • Identifying methods on how to optimize the data warehouse
  • Address security of data through a Synapse Analytics architecture
2. Optimization & Security

This module teaches the most critical operational skills, either determining the success or failure of data warehouse-based projects. Proper Data Warehouse optimization and security configurations are vital opportunities for you to showcase your differentiation against your competition.
 
 By the end of the day, learners will be able to:

  • Implement optimization strategies for the data warehouse using a SQL-based approach in Azure Synapse Analytics
  • Apply security concepts including row-level security, object-level security, column-level security, sensitive data discovery and classification, and access controls to a customer scenario
3. Machine Learning & Monitoring

This module dives into the data science workloads and integrations within Synapse Analytics then covers monitoring capabilities built into the Synapse workspace. Attendees learn Apache Spark and Machine Learning fundamentals and perform data modeling and operationalization within Synapse Notebooks and integrations with Azure Machine Learning. Finally, learners experience monitoring methods through practical examples and demonstrations.

By the end of the day, learners will be able to:

  • Use Synapse notebooks with Apache Spark to train and serialize machine learning models for SQL-based predictions
  • Train and operationalize models with an integrated Azure Machine Learning workspace
  • Monitor activities within Synapse Studio
4. Challenge Day

Level: Expert

In this hackathon-style module, students team up to solve a series of real-world challenges by applying what they learned in the other modules or by drawing from their Synapse Analytics experience. The challenges test the team’s ability to overcome complex data engineering and analytics-related problems, from malformed or incomplete data sets to slow-running queries and advanced data exploration and reporting requirements. There are no step-by-step instructions, just a series of requirements derived from a customer scenario, artifacts, and a list of outcomes for each challenge.

Challenge Day will test the extent of your learners’ knowledge, as well as their ability to work as a team effectively.

Ready to Get Started?

Our Training Team is ready to help you get started on your training journey. Reach out and let us know your training needs so we can discuss how best we can help.

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Course Benefits

Trained by experts

Our instructors are expert practitioners who share their real-world experience and insights into the topics covered by this course in a pragmatic way.

We offer a safe environment where you can experiment with realistic data and ask questions throughout the boot camp.

Hands-on experience

This course includes lab environments that use realistic data, allowing you to tackle common data issues and challenges encountered “in the wild.” All you need to access the lab environments is a modern web browser.