Data Analysis by Excel, SQL, Python and Power BI

Data Analysis by Excel, SQL, Python and Power BI, available at $64.99, has an average rating of 2.8, with 96 lectures, 9 quizzes, based on 59 reviews, and has 179 subscribers.

You will learn about You will able to analyze Raw Data patterns and uncover most of the hidden Information. Your research strategies will improve by using basics and Advanced functions of Excel, SQL, and Python. Confidently use the most crucial Excel functions and techniques for analysis You will get Hand-on Experience using Excel, SQL, Python, and Power BI. You will learn Data Wrangling, Data Cleaning, Data Analyzation and Data Manipulation. You will Identify Ideas and manage Business Decisions. Becomes an Expert in Data Storytelling and Optimize the overall output using Power BI. Able to provide your thought on crucial situations and solve them accordingly. You will be able to code on Python and SQL. You will merge different Datasets using Python, Excel and Power-BI. This course is ideal for individuals who are This course is particularly for those people who want to learn Data related things a student, a teacher, and Corporate sector people included. or Data curious guy who wanted to learn how to gather hidden information by using Excel, SQL, Python, and Power BI. or Students looking for a comprehensive, engaging, and highly interactive approach to learning Data Analysis. or A person who wants to improve the system and change the manual routine works into automatic work. or A Doctor, Teacher, Engineer, or even anyone who belongs to any particular domain can learn about Data Engineering. It is particularly useful for This course is particularly for those people who want to learn Data related things a student, a teacher, and Corporate sector people included. or Data curious guy who wanted to learn how to gather hidden information by using Excel, SQL, Python, and Power BI. or Students looking for a comprehensive, engaging, and highly interactive approach to learning Data Analysis. or A person who wants to improve the system and change the manual routine works into automatic work. or A Doctor, Teacher, Engineer, or even anyone who belongs to any particular domain can learn about Data Engineering.

Enroll now: Data Analysis by Excel, SQL, Python and Power BI

Summary

Title: Data Analysis by Excel, SQL, Python and Power BI

Price: $64.99

Average Rating: 2.8

Number of Lectures: 96

Number of Quizzes: 9

Number of Published Lectures: 96

Number of Published Quizzes: 9

Number of Curriculum Items: 105

Number of Published Curriculum Objects: 105

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

You will able to analyze Raw Data patterns and uncover most of the hidden Information.

Your research strategies will improve by using basics and Advanced functions of Excel, SQL, and Python.

Confidently use the most crucial Excel functions and techniques for analysis

You will get Hand-on Experience using Excel, SQL, Python, and Power BI.

You will learn Data Wrangling, Data Cleaning, Data Analyzation and Data Manipulation.

You will Identify Ideas and manage Business Decisions.

Becomes an Expert in Data Storytelling and Optimize the overall output using Power BI.

Able to provide your thought on crucial situations and solve them accordingly.

You will be able to code on Python and SQL.

You will merge different Datasets using Python, Excel and Power-BI.

Who Should Attend

This course is particularly for those people who want to learn Data related things a student, a teacher, and Corporate sector people included.

Data curious guy who wanted to learn how to gather hidden information by using Excel, SQL, Python, and Power BI.

Students looking for a comprehensive, engaging, and highly interactive approach to learning Data Analysis.

A person who wants to improve the system and change the manual routine works into automatic work.

A Doctor, Teacher, Engineer, or even anyone who belongs to any particular domain can learn about Data Engineering.

Target Audiences

This course is particularly for those people who want to learn Data related things a student, a teacher, and Corporate sector people included.

Data curious guy who wanted to learn how to gather hidden information by using Excel, SQL, Python, and Power BI.

Students looking for a comprehensive, engaging, and highly interactive approach to learning Data Analysis.

A person who wants to improve the system and change the manual routine works into automatic work.

A Doctor, Teacher, Engineer, or even anyone who belongs to any particular domain can learn about Data Engineering.

Data analytics has been one of the fastest-growing fields in the last five years. The use of major tools like Excel, SQL, and Python has elevated its importance, as these tools allow analysts to accurately and professionally uncover the story behind the data.

This course is structured to provide a step-by-step guide to you, starting from the basics of each tool and gradually building up to more advanced concepts. Through hands-on exercises and real-world examples, you will learn how to manipulate data, perform statistical analyses, and create compelling visualizations and dashboards.

In this course, we will cover :

In Excel Section:

Excel functions for data analysis.

Excel fundamental concepts such as Sorting, Filtering, Statistical, and text functions.

Create PivotTable slicers for interactive filtering.

Analyze time-based data with slicers.

Refresh and update data connections.

Combine data from multiple sources.

Perform data analysis on external datasets.

Construct various chart types (bar, line, pie, etc.).

Customize chart elements (titles, axes, data labels).

In SQL Section:

Working with SQL Queries to retrieve data from databases for Analysis.

Understand the concept of Sub-Queries or Inner Queries. Joining tables and combining data from multiple sources.

SQL- DDL, DML, and DQL commands.

Performing data manipulation.

Learn how to apply different conditions to datasets.

Understand the concept of Sub-Queries or Inner Queries.

Discovering these concepts with a Case Study.

In Python Section:

Python’s fundamental concepts include Object-oriented programming.

Work with Jupyter Notebooks.

Introduction to the NumPy and the Pandas Library.

Data Cleaning and Handling Missing Values.

Descriptive Statistics.

Correlation Analysis.

Learn about Data Story Telling with Matplotlib and Seaborn.

Hands-on Projects.

In Power BI Section:

Understand the Power BI ecosystem

Install and set up Power BI Desktop

Navigate the Power BI interface

Transforming and cleaning data

Data modeling basics

Creating simple visualizations (tables, charts)

Using filters and slicers

Creating interactive reports and dashboards

Combining multiple data sources

Hands-on projects and real-world applications

So,

You will get to practice the exercises and work on some exciting projects.

Enroll now and make the best use of this course.

Course Curriculum

Chapter 1: Data Analytics Foundation, and Connection with other Fields, and Future Trends.

Lecture 1: Introduction to Data Analytics? Is it worth it ?

Lecture 2: Why Data Analytics?

Lecture 3: Types of Data Analysis

Lecture 4: Framework of Data Analytics Course

Lecture 5: The Course Content

Lecture 6: The Services you will provide.

Lecture 7: Future Trends

Chapter 2: Case Study of Real Life

Lecture 1: Case Study

Lecture 2: Learning Resources

Lecture 3: You have Achieved .

Chapter 3: Data Analysis with EXCEL

Lecture 1: Overview of Excel Section

Lecture 2: Introduction to Excel

Lecture 3: Data Connections

Lecture 4: Data Formatting

Lecture 5: Data Cleaning

Lecture 6: Detailed Descriptive Analysis

Lecture 7: Where is the Option of Data Analysis?

Lecture 8: Descriptive Statistics

Lecture 9: VLookup

Lecture 10: Pivot Table Part 1

Lecture 11: Pivot Table Part 2

Lecture 12: Pivot Table Formatting

Lecture 13: Correlation

Lecture 14: How to Merge multiple data tables?

Lecture 15: What is Insert Slicer?

Lecture 16: Random Number Generation

Lecture 17: Charts and Graphs

Lecture 18: What have you achieved from this Excel Section?

Chapter 4: Data Analysis with SQL

Lecture 1: Overview of SQL Section

Lecture 2: Installation of SQL SERVER

Lecture 3: Discover the Interface

Lecture 4: How to Import Data?

Lecture 5: SELECT and FROM Clause

Lecture 6: SELECT DISTINCT

Lecture 7: Logical Operators

Lecture 8: Comparison Operators

Lecture 9: Aggregate Functions

Lecture 10: Where with Logical Operators ( AND & OR )

Lecture 11: WHERE Clause with Logical Operators Part 1

Lecture 12: WHERE Clause with Logical Operators Part 2

Lecture 13: Group By Part 1 with Aggregate Function

Lecture 14: Group By Part 2 with Data Type Change

Lecture 15: ORDER BY

Lecture 16: HAVING

Lecture 17: WHERE AND HAVING

Lecture 18: Primary Vs Foreign Key

Lecture 19: JOIN

Lecture 20: UNION

Lecture 21: SUBQURIES

Lecture 22: Introduction to Case Study

Lecture 23: Case Study Part 1

Lecture 24: Case Study Part 2

Lecture 25: What have you achieved from this SQL Section ?

Chapter 5: Data Analysis with PYTHON

Lecture 1: Overview of Python Section

Lecture 2: Installation of Anaconda ( For PYTHON )

Lecture 3: Opening Layout Introduction

Lecture 4: What are Data Types in Python?

Lecture 5: Variable, Value and Print

Lecture 6: Casting and Case Sensitive

Lecture 7: What is Module?

Lecture 8: Module Vs Library

Lecture 9: Numpy Library

Lecture 10: PANDAS Library

Lecture 11: Matplotlib Package

Lecture 12: Seaborn Library

Lecture 13: How to Import Data in Jupyter Notebook?

Lecture 14: What is Data Wrangling?

Lecture 15: Data Cleaning Part 1

Lecture 16: Missing Data

Lecture 17: Outliers

Lecture 18: Inconsistent Data

Lecture 19: Data Cleaning Part 2

Lecture 20: Invalid Data

Lecture 21: Duplicate Data

Lecture 22: Data Types Issues

Lecture 23: GroupBy

Lecture 24: Merge

Lecture 25: Cross-Tab

Lecture 26: Cut

Lecture 27: Analysis Methods Part 1 (a)

Lecture 28: Analysis Methods Part 1 (b)

Lecture 29: Analysis Methods Part 2

Lecture 30: Analysis Methods Part 3

Lecture 31: Unique Methods

Lecture 32: Graphs and Charts

Lecture 33: Case Study Part 1

Lecture 34: Case Study Part 2

Instructors

Sparky Academy
Data Science

Rating Distribution

1 stars: 6 votes

2 stars: 8 votes

3 stars: 14 votes

4 stars: 10 votes

5 stars: 21 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!