Course Introduction
This course has been designed to prepare you for meaningful opportunities in the future pertinent to Data Analytics. The course starts with the Introduction to Data Analytics and explains the phases of the Data Analytics project. It will further guide you to use different functions of excel with regard to Data Analytics like Sort and Filter, Lookup functions, conditional formatting, Pivot tables, and more. The final phase of this course will cover Data Visualization, in which you will be able to learn how to represent data using pictorial charts and tables. Using various examples,
This The Power of Data Analytics: Using Excel and SQL training course bridges these powerful tools, equipping participants to seamlessly integrate SQL`s data-handling strengths with Excel’s analytical capabilities. Through real-world examples and hands-on exercises, attendees will learn to transform raw data into meaningful insights, enhancing decision-making and driving impactful business results. Whether you are an aspiring data analyst or a professional looking to refine your skills, this course will unlock your potential to leverage data as a strategic asset.
Training Objectives
By the end of this training course, participants will be able to:
- Understand the principles and best practices of data analytics
- Display working knowledge of Excel for Data Analysis.
- Employ data quality techniques to import and clean data in Excel.
- Analyze data in spreadsheets by using filter, sort, look-up functions, as well as pivot tables.
- Query and manipulate data effectively using SQL
- Perform advanced data analysis and visualization in Excel
- Integrate SQL and Excel to enhance analytical efficiency
- Present data-driven findings to support strategic decisions
Training Methodology
This training course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension and retention of the information presented. This includes an interactive mixture of lecture-led learning & group discussions.
Who should Attend?
This training course is suitable to a wide range of professionals but will greatly benefit:
- Data analysts and business intelligence professionals
- Managers and team leaders looking to leverage data for decision-making
- Professionals in finance, marketing, operations, or any field involving data analysis
- Anyone interested in enhancing their data analytics skills with SQL and Excel
Course Outline
Day One: Introduction to Data Analytics
- Introduction to data analytics and its role in business success
- Overview of SQL and Excel in the analytics workflow
- Data types, structures, and the basics of database management
- Setting up and accessing data in SQL databases and Excel
Day Two: Retrieving Data
- SELECT Statement and Column Aliases
- Filtering Data with WHERE Clause
- Sorting Data with ORDER BY
- Limiting Results with LIMIT and OFFSET
Advanced Querying Techniques
- Working with NULL Values
- Pattern Matching with LIKE and Wildcards
- Grouping Data with GROUP BY
- Filtering Grouped Data with HAVING Clause
Day Three: Excel for Advanced Data Analysis
- Importing and cleaning data in Excel.
- Using formulas and functions for data transformation
- Creating PivotTables and PivotCharts for dynamic reporting
- Statistical analysis in Excel: Descriptive statistics, regression, and correlation
- Hands-on exercises: Analyzing real-world datasets in Excel
Day Four: Aggregating and Analyzing Data
- Window Functions and Ranking
- Using Aggregate Functions with GROUP BY
- Analytic Functions for Advanced Analysis
Managing Database Security
- Understanding Database Security Concepts
- Granting and Revoking Permissions
- Securing Sensitive Data
Day Five: Data Visualization and Reporting
- Principles of effective data visualization
- Creating compelling dashboards and reports in Excel
- Presenting SQL data in visual formats for stakeholders
- Case studies: Solving business challenges with SQL and Excel analytics
- Developing a personal action plan for applying learned skills
Real-world Applications and Case Studies
- Applying SQL in Data Science Projects
- Building Complex Queries for Business Analysis
- Working with Real-world Datasets