The cloud offers organizations access to (PaaS) platform-as-a-service components, pay-as-you-go cost models, flexibility and scalability... but most of all cloud gives us innovation and rapid access to new features and functionalities.
As a Data professional you want to stay up-to-date about how BI and Data Science is ran in the cloud, which features are new and which components can help overcome current challenges in your on-premise BI & Data Science environment. With that ambition, we host a 2-day fundamentals workshop aimed to share and show what a BI professional should know about building BI and Analytics platforms in the Azure Cloud. We'll run 1-day theory essentials and 1-day of technical training where participants get hands-on in Azure.
Course objective
The objective of this 2-day workshop is to learn the fundamentals on how to design, build and run a BI platform in the Azure Cloud. Building on the concepts that BI professionals know (e.g. ETL, slowly changing dimensions, SSIS) we'll be transparent on what's similar but different in Azure and which components and concepts are new but very relevant (e.g. DevOps, parallelization, infrastructure as code). We'll train you on the fundamentals and give you a full perspective on what you should know, how to get started and what skills to further grow.
Audience
- You are an IT or BI manager, developer or Data Scientist interested in the cloud for data & analytic workloads
- You are looking to know what's what in the Azure Cloud and get some practical tips (rather than reading online documentation)
- You are familiar with the concepts of ETL and data warehousing
Agenda
During the first theory-day, we'll get you up-to-speed about what you should know about the Azure Cloud. The training will handle underneath modules/topics
- Introduction into Azure & why Azure is leading in Belgium
- Core cloud services for BI, Data, AI & Analytics
- for ETL: Data Factory, Databricks, Dataflow
- for data warehousing: Synapse Analytics, SQL Database, type of SQL Databases
- for Modern Data Platform applications:
- Databricks Delta
- Azure Data Lake Storage
- Modern Data Platform concept
- Data Lake vs. Data Warehouse
- ETL vs. ELT
- DevOps in Azure
- Infrastructure as Code (using ARM templates or Terraform)
- Continuous Integration and Git
- Continuous Deployment
- MLOps in Azure
- Using Machine Learning Workspace
- Using Databricks & ML Workspace
- Security & governance
- Active directory
- Network security
- Cloud scalability & stability
- High availability, zone resiliency, geo-replication
- Costs in Azure
- Predicting costs
- Dedicated capacity
These technologies will be extensively covered in this course. From left to right: Databricks, Azure Data Factory, Azure Data Lake, Azure Devops
On the second-day, we'll run a full-day technical training where participants get hands-on in Azure. During the hands-on day we'll get you going on an Azure platform and help you:
- Write and deploy infrastructure through Infrastructure as Code
- Write and schedule data pipelines in Databricks
- Set-up various Data Factory pipelines
- running incremental and full copies from an on-premise database
- running ETL with transformations written in Dataflow
- Do continuous deployment of your code
- Run MLOps with Azure Machine Learning Workspace
Cost
- 1350 € per participant for 2 days (fundamentals + hands-on day)
Subscribe
For more information, contact academy@element61.be
- Write and schedule data pipelines in Databricks
Azure Training schedule can be found here.
For a complete overview of all courses, visit our academy page.