Information Technology

Data Analysis (Excel, SQL, Tableau)

Start: Oct 2019       Type: Evening / Weekend Classes       Duration (hr): 78


This course is perfect for business professionals, analysts, non-programmers, students and graduates who would like to improve their Data Analysis and Data Visualization skills. Students will learn how to work with data using advanced Microsoft Excel techniques, such as Functions, Lookups, Pivot Tables and Pivot Charts, Data Analysis Tools. Also, students will discover how to use VBA and Macros for more advanced analysis and automated procedures. Students will study fundamentals of SQL syntax and writing queries in SQL Server Databases. Finally, students will become skilled at Data Visualization in Tableau, including building Dashboards and using statistical techniques to analyze data. After completing this course, students will be able to perform work that requires intermediate knowledge of data analysis and data manipulation (in the Microsoft Excel environment) and data visualization.
1. 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.
2. Introduction to SQL Server Databases – this module provides students with the understanding of database concepts and the essentials of relational database with the SQL language.The module includses: data types, table structure, essential SQL commands, retrieving data, queries, group functions, data manipulation, control transactions etc.
3. 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.
*78 instructor-led in-class academic hours
Basics of Excel

Related Courses