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Data Analysis with Business Intelligence (SQL, Excel, Tableau, Power BI)


Mar 2024


Data Analysis and Data Visualization*

Type of Training: Remote (Online) / In-Person; Time: Evenings & Weekends

This unique course provides solid knowledge in Data Analysis and Business Intelligence. Students will learn the fundamentals of Data Analysis with Microsoft Excel, SQL Databases and Business Intelligence, Data Visualization with Tableau, and Data Visualization with Power BI and Data Analysis Expressions (DAX). After completing this course, students will be able to work as a Data Analyst or perform related work that requires knowledge of data analysis, data manipulation and data visualization. This training is available in-class and remotly (online).


1. Statistics Basics – students will review basic concepts and terminology in Statistics.

2. SQL Databases Fundamentals – this module provides solid fundamentals of SQL databases, with emphasis on querying data. Students will learn how to filter, group and sort data, retrieve data from multiple tables using joins and unions, built-in functions to manipulate dates and strings, primary and foreign key table relationships, understand indexes for performance gains. The following topics will be covered: select queries, filtering, grouping, sorting data, combining tables with joins and union, understanding primary and foreign key relationship, views, built in system functions for querying data, conditional testing with If and Case statements, looping, inserting, updating and deleting data basics.

3. Foundations of Business Intelligence with SQL – in this module students will learn key components of the Microsoft Business Intelligence stack, including SSIS / ETL, SSRS for reporting and SSAS for multidimensional data analysis. SSIS provides knowledge in creating connection managers to various data sources, use and configure data flow and control flow tasks, work with container objects, create variables and parameters, deploy packages, work with the Integration Services Catalog. SSRS concentrates in configuring the tablix controls (table, matrix and list), creating data sources and data set, using subqueries, grouping rows and columns, dynamic and cascading parameters, conditional formatting, creating expressions, publish reports. SSAS teaches creating multidimensional cubes, building dimension and fact tables, data mining, datawarehouse concepts, star and snowflake schema, .

4. Data Analysis with Excel – in this module students will learn Excel advanced techniques, including Math Functions, Logical Functions, Statistical Functions, Lookup, Sort/Filter Data, Pivot Tables and Pivot Charts, Power Pivot Tables, Data Analysis Tools etc. Also, this module provides introduction to VBA scripting and using Macros.

5. Data Visualization with Tableau – the module includes: using the Tableau interface/paradigm to create data visualizations, creating calculations, building Dashboards, advanced chart types and visualization, complex calculations to manipulate data, use statistical techniques to analyze data, implement advanced geographic mapping techniques and visualizations of non-geographic data, prep data for analysis, combine data sources using data blending.

6. Data Visualization with Power BI and DAX – Power BI Desktop lets you connect to, transform, and visualize your data. With Power BI Desktop, you can connect to multiple different sources of data, and combine them (often called modeling) into a data model. This data model lets you build visuals, and collections of visuals you can share as reports, with other people inside your organization. Most users who work on business intelligence projects use Power BI Desktop to create reports, and then use the Power BI service to share their reports with others in a cloud.

150 instructor-led in-class academic hours

Basics of Statistics and Excel

Bonus for our students enrolled in DA course:
Special discount price for SAS Programming, R Programming (valid 24 months)

Note: Statistics Basics module can be waived for students with recent similar college credits (Statistics) or people with extensive experience in Statistics.

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