Data Analytics and Power BI Bootcamp

In the first week of the program, students will gain a comprehensive understanding of the Analytics Lifecycle, including the exploration of diverse data sources and databases. They will learn to navigate a typical data pipeline, generate valuable insights, and make recommendations based on end-to-end business case study demonstrations.

Practical skills will be honed through sessions, delving into Excel, working with Pivot Tables, sorting and filtering data, utilizing the Analyze Tab, exploring charts, and mastering descriptive statistics.

In this week, students will delve into the foundations of databases and gain a solid understanding of the SQL language. The week covers introductory concepts of relational databases, basic SQL syntax, and statements including SELECT, FROM, and WHERE. Students will learn the art of retrieving data using SELECT, explore SQL operators, and discover the power of in-built functions for numerical, string, and date-time manipulations. They will also learn essential skills such as filtering data using the WHERE clause, pattern matching with LIKE and wildcards, sorting query results, aliasing, and executing pagination queries.

This week, students will advance their skills in data manipulation and analysis. Beginning with the foundational concepts of aggregating and grouping data, the week extends to techniques such as aggregation-based filtering using HAVING, understanding SQL constraints, mapping, and joining tables. Students will explore the power of UNION and UNION ALL operations for combining datasets, delve into window functions for ranking, partitioning, and aggregating data, and master the intricacies of subqueries and nested subqueries. The week also covers the practical application of Common Table Expression (CTE) for query simplification and imparts an understanding of the crucial order of execution.

Students will start this week by configuring Google Colab and then delving into the fundamentals of Python. Covering variables, data types, and data structures, this week lays a solid foundation for understanding and applying essential concepts in Python programming.

This week, students dive into Numpy arrays and functions, mastering techniques such as indexing and accessing data. The week progresses to Pandas, covering series, dataframes, and essential operations like saving, loading, merging dataframes, and utilizing Pandas functions for comprehensive data manipulation and transformation.

This week, students gain expertise in data exploration through sanity checks, univariate, and bivariate analysis. The week also covers critical tasks such as missing value treatment and outlier detection, providing a holistic approach to uncovering insights and ensuring data integrity in the analysis process.

This week, students gain proficiency in Power BI essentials. Covering the interface, data visualization, and report creation, the week includes connecting to diverse data sources, basic data modeling, data preparation, cleaning, transformation using Power Query, establishing relationships between data tables, and exploring advanced modeling techniques for a comprehensive understanding of Power BI capabilities.

This week covers best practices for compelling visuals, customizing with formatting options, dashboard creation, and utilizing Power BI Developer Tools for custom visuals. The week also explores incorporating R and Python for advanced analytics and building interactive, drill-down visualizations to enhance the overall data storytelling experience.

Students get introduced to the Data Analysis Expressions (DAX) language. The week covers creating calculated columns and measures using DAX functions, understanding context in DAX calculations, leveraging advanced DAX functions for time intelligence, ranking, and more. Students explore working with tables and filters in DAX expressions and optimizing DAX performance.

This week, students learn the practical aspects of deploying and sharing Power BI reports. This includes deploying reports and dashboards to the Power BI Service, sharing with users and groups, and utilizing collaboration features. Students will learn how to implement best practices for optimized data models, understand query folding, and optimize queries for performance. The week also covers the use of DirectQuery and Live Connection for handling large datasets efficiently.

In the 'Power BI Administration and Security' module, participants gain expertise in managing Power BI workspaces, reports, and data sources. The curriculum covers configuring security settings, permissions, and delves into utilizing the Power BI API for automation and integration, empowering participants with skills for effective administration and robust security practices in Power BI.