Duration: 10 days – 70 hrs.
Overview.
The Data Analytics with Python, Azure Data Warehouse, and Power BI Training Course is an intensive program designed to equip participants with the skills and knowledge required to excel in the world of data analytics using the powerful combination of Python, Azure Data Warehouse, and Power BI. Through hands-on exercises and real-world projects, participants will learn how to harness the capabilities of these cutting-edge technologies to analyze vast datasets, build data pipelines, create interactive visualizations, and make data-driven decisions.
Objectives
- Gain proficiency in Python programming for data analysis and manipulation.
- Understand the fundamentals of Azure Data Warehouse and its role in big data processing.
- Learn how to use Python and Azure Data Warehouse to manage and process large-scale datasets.
- Discover the art of data visualization using Power BI to create dynamic and compelling reports.
- Acquire skills in building end-to-end data analytics solutions from data extraction to visualization.
- Understand best practices for data cleaning, transformation, and feature engineering.
- Explore advanced analytical techniques, including machine learning and predictive modeling.
- Learn how to integrate Python, Azure Data Warehouse, and Power BI to unleash the full potential of data analytics.
Audience
- Data Analysts: Professionals who work with data to extract insights, analyze trends, and make data-driven decisions.
- Data Scientists: Individuals responsible for advanced data analysis, predictive modeling, and machine learning.
- Business Intelligence (BI) Professionals: Those involved in creating dashboards, reports, and visualizations to support business decision-making.
- IT Professionals: Individuals interested in leveraging Python, Azure Data Warehouse, and Power BI for data analytics and reporting.
- Business Managers and Decision Makers: Executives and leaders who want to understand data analytics concepts and their applications in business.
- Database Administrators (DBAs): Professionals managing data storage and databases in organizations.
- Data Engineers: Those responsible for data pipeline development and data integration.
- Aspiring Data Analysts: Individuals looking to enter the field of data analytics and learn the essential tools and techniques.
- Statisticians: Professionals who want to explore data analytics tools and technologies for statistical analysis.
- Anyone with an interest in Data Analytics: Participants who have a keen interest in understanding data analytics, regardless of their current role.
Pre- requisites
- Basic understanding of data concepts and familiarity with programming fundamentals is recommended.
- No prior experience with Python, Azure Data Warehouse, or Power BI is required.
Course Content
Day 1: Introduction to Python Programming
- Overview of Python and its importance in data analysis and manipulation
- Setting up Python environment and IDE
- Basic data types, variables, and operators in Python
- Control flow statements: if-else, loops, and functions
Day 2: Data Manipulation with Python
- Working with lists, tuples, and dictionaries
- Understanding NumPy for numerical computations
- Introduction to Pandas for data manipulation and analysis
- Loading and exploring data with Pandas
Day 3: SQL Server Basics
- Introduction to SQL Server and relational databases
- Creating and managing databases, tables, and indexes
- Basic SQL queries: SELECT, INSERT, UPDATE, DELETE
- Querying data with filters, sorting, and aggregation
Day 4: Advanced SQL Server Queries
- Working with joins and subqueries
- Using SQL Server functions for data transformation
- Modifying and optimizing database structures
- Handling constraints and transactions in SQL Server
Day 5: Introduction to Azure Data Warehouse
- Understanding Azure Data Warehouse and its architecture
- Creating and configuring an Azure Data Warehouse
- Data loading options into Azure Data Warehouse
- Querying data in Azure Data Warehouse with T-SQL
Day 6: Data Modeling and Schema Design in Azure Data Warehouse
- Designing data models for Azure Data Warehouse
- Implementing data distribution and partitioning
- Managing data with PolyBase and external tables
- Performance optimization and tuning in Azure Data Warehouse
Day 7: Power BI Basics
- Introduction to Power BI for data visualization and reporting
- Connecting Power BI to various data sources, including SQL Server and Azure Data Warehouse
- Building basic visualizations: bar charts, line charts, and pie charts
- Applying filters and slicers for interactive reporting
Day 8: Advanced Power BI Techniques
- Utilizing DAX (Data Analysis Expressions) for complex calculations
- Building advanced visualizations: maps, scatter plots, and matrices
- Creating interactive dashboards with Power BI
- Sharing and collaborating on Power BI reports and dashboards
Day 9: Python and Power BI Integration
- Using Python scripts in Power BI for data transformation and analysis
- Leveraging Python libraries (e.g., Pandas, NumPy) in Power BI
- Building custom visuals with Python in Power BI
Day 10: Final Project and Wrap-up
- Participants work on a hands-on project combining Python, SQL Server, Azure Data Warehouse, and Power BI
- Project presentations and feedback
- Recap of key concepts from the training
- Final Q&A session to address any remaining questions and challenges
- Conclusion and certificate distribution
