DP-3011 Implementing a Data Analytics Solution with Azure Databricks
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Duration
1 day
Location
Course Language English
Training Solutions Online Live
The combination of cloud technology and modern data analysis is changing how information is processed and used. Powerful analysis platforms make it possible to intelligently connect data streams and efficiently answer complex questions.
Key topics
- Architecture and operation of scalable analytics solutions.
- Data processing with distributed analytics frameworks.
- Setting up pipelines for analysis and reporting.
- Security, governance, and cost management.
- Integration into existing data landscapes.
Prerequisites
Knowledge of data analysis, SQL, or Python, as well as a basic understanding of cloud architectures.
Target audience
Roles in data analytics, data engineering, business intelligence, cloud technology, and IT-related analysis functions.
Modern cloud analytics combines technical performance with strategic added value. Well-thought-out implementation supports sustainable data strategies and creates a stable basis for future analytical requirements.
- Getting started with Azure Databricks
- Identifying Workloads
- Understanding the concepts
- Discover Spark
- Create clusters
- Use notebooks
- Edit data files
- Visualization
- Set up Delta Lake
- Create Delta Lake tables
- Create and query catalog tables
- Using streaming data in Delta Lake
- Starting SQL Warehouses
- Create databases and tables
- Create queries and dashboards
- Understanding Azure Databricks Notebooks and Pipelines
- Create a linked Azure Databricks service
- Use notebook activity in pipeline
- Apply parameters in the notebook
