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Data Analysis Essentials – (Excel,SQL,Power BI,Python)

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Data Analysis Essentials – (Excel,SQL,Power BI,Python), available at $19.99, has an average rating of 4.13, with 99 lectures, based on 8 reviews, and has 83 subscribers.

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You will learn about Understand the foundational concepts of data analysis and its importance in decision-making processes. Gain proficiency in using Microsoft Excel for data manipulation, analysis, and visualization. Master SQL fundamentals for data retrieval, manipulation, and querying in relational databases. Learn to leverage Power BI for creating interactive dashboards and reports to visualize data insights. Develop essential programming skills in Python for data analysis, including data manipulation and visualization. Acquire techniques for data cleaning and preparation to ensure data quality and accuracy for analysis. Explore advanced Excel features for pivot tables, data validation, and conditional formatting to enhance data analysis workflows. Understand the principles of data visualization and create effective charts, graphs, and dashboards in Excel and Power BI. Learn to use Python libraries such as pandas for data manipulation, analysis, and visualization. This course is ideal for individuals who are Students: College or university students studying business, economics, mathematics, computer science, or related fields who want to complement their academic knowledge with practical skills in data analysis. or Professionals transitioning to data-related roles: Individuals looking to transition into data analysis, business analysis, or similar roles within their current organization or in a new industry. or Business professionals: Professionals working in marketing, finance, operations, healthcare, or any field where data plays a crucial role in decision-making and who want to improve their data analysis skills. or Entrepreneurs and business owners: Entrepreneurs and small business owners seeking to harness the power of data to drive business growth, optimize operations, and make informed strategic decisions. or Career changers: Individuals considering a career change into the field of data analysis who want to acquire the necessary skills and knowledge to pursue new opportunities in this rapidly growing field. or Anyone curious about data analysis: Individuals with a general interest in data analysis and a desire to learn how to extract insights from data to solve real-world problems and make better decisions. It is particularly useful for Students: College or university students studying business, economics, mathematics, computer science, or related fields who want to complement their academic knowledge with practical skills in data analysis. or Professionals transitioning to data-related roles: Individuals looking to transition into data analysis, business analysis, or similar roles within their current organization or in a new industry. or Business professionals: Professionals working in marketing, finance, operations, healthcare, or any field where data plays a crucial role in decision-making and who want to improve their data analysis skills. or Entrepreneurs and business owners: Entrepreneurs and small business owners seeking to harness the power of data to drive business growth, optimize operations, and make informed strategic decisions. or Career changers: Individuals considering a career change into the field of data analysis who want to acquire the necessary skills and knowledge to pursue new opportunities in this rapidly growing field. or Anyone curious about data analysis: Individuals with a general interest in data analysis and a desire to learn how to extract insights from data to solve real-world problems and make better decisions.

Enroll now: Data Analysis Essentials – (Excel,SQL,Power BI,Python)

Summary

Title: Data Analysis Essentials – (Excel,SQL,Power BI,Python)

Price: $19.99

Average Rating: 4.13

Number of Lectures: 99

Number of Published Lectures: 99

Number of Curriculum Items: 99

Number of Published Curriculum Objects: 99

Original Price: $49.99

Quality Status: approved

Status: Live

What You Will Learn

  • Understand the foundational concepts of data analysis and its importance in decision-making processes.
  • Gain proficiency in using Microsoft Excel for data manipulation, analysis, and visualization.
  • Master SQL fundamentals for data retrieval, manipulation, and querying in relational databases.
  • Learn to leverage Power BI for creating interactive dashboards and reports to visualize data insights.
  • Develop essential programming skills in Python for data analysis, including data manipulation and visualization.
  • Acquire techniques for data cleaning and preparation to ensure data quality and accuracy for analysis.
  • Explore advanced Excel features for pivot tables, data validation, and conditional formatting to enhance data analysis workflows.
  • Understand the principles of data visualization and create effective charts, graphs, and dashboards in Excel and Power BI.
  • Learn to use Python libraries such as pandas for data manipulation, analysis, and visualization.

Who Should Attend

  • Students: College or university students studying business, economics, mathematics, computer science, or related fields who want to complement their academic knowledge with practical skills in data analysis.
  • Professionals transitioning to data-related roles: Individuals looking to transition into data analysis, business analysis, or similar roles within their current organization or in a new industry.
  • Business professionals: Professionals working in marketing, finance, operations, healthcare, or any field where data plays a crucial role in decision-making and who want to improve their data analysis skills.
  • Entrepreneurs and business owners: Entrepreneurs and small business owners seeking to harness the power of data to drive business growth, optimize operations, and make informed strategic decisions.
  • Career changers: Individuals considering a career change into the field of data analysis who want to acquire the necessary skills and knowledge to pursue new opportunities in this rapidly growing field.
  • Anyone curious about data analysis: Individuals with a general interest in data analysis and a desire to learn how to extract insights from data to solve real-world problems and make better decisions.

Target Audiences

  • Students: College or university students studying business, economics, mathematics, computer science, or related fields who want to complement their academic knowledge with practical skills in data analysis.
  • Professionals transitioning to data-related roles: Individuals looking to transition into data analysis, business analysis, or similar roles within their current organization or in a new industry.
  • Business professionals: Professionals working in marketing, finance, operations, healthcare, or any field where data plays a crucial role in decision-making and who want to improve their data analysis skills.
  • Entrepreneurs and business owners: Entrepreneurs and small business owners seeking to harness the power of data to drive business growth, optimize operations, and make informed strategic decisions.
  • Career changers: Individuals considering a career change into the field of data analysis who want to acquire the necessary skills and knowledge to pursue new opportunities in this rapidly growing field.
  • Anyone curious about data analysis: Individuals with a general interest in data analysis and a desire to learn how to extract insights from data to solve real-world problems and make better decisions.

In today’s data-driven world, the ability to analyze and interpret data is a valuable skill that opens doors to a wide range of career opportunities and empowers individuals to make informed decisions in both personal and professional contexts. Whether you’re a student eager to explore the field of data analysis, a seasoned professional looking to enhance your analytical capabilities, or an entrepreneur seeking to leverage data for business growth, this comprehensive course is designed to equip you with the knowledge and practical skills needed to excel in the exciting world of data analysis.

Spanning across multiple modules, this course covers everything you need to know to become proficient in data analysis, regardless of your prior experience or background. From understanding the fundamental concepts of data analysis to mastering popular tools and techniques used by data professionals, each module is carefully crafted to provide a structured learning path that caters to learners of all levels.

The journey begins with an introduction to the foundational concepts of data analysis, exploring its role in decision-making processes and its significance across various industries and domains. You’ll then dive into hands-on tutorials on using Microsoft Excel, SQL, Power BI, and Python – four essential tools in the data analyst’s toolkit. Through step-by-step guidance and practical exercises, you’ll learn how to manipulate, analyze, and visualize data efficiently, unlocking valuable insights that drive strategic decision-making.

Throughout the course, you’ll explore a wide range of topics, including statistical analysis, data cleaning and preparation, data visualization, regression analysis, and more. You’ll discover how to apply statistical techniques to analyze data distributions, measure central tendency, and assess variability, enabling you to derive meaningful insights from your data with confidence.

But this course is more than just theoretical knowledge – it’s about practical, real-world application. With hands-on projects and case studies inspired by real-world scenarios, you’ll have the opportunity to put your skills to the test and solve data analysis challenges commonly encountered in today’s professional landscape. Whether you’re analyzing sales trends, forecasting financial performance, or uncovering patterns in customer behavior, you’ll emerge from this course with the practical skills and confidence to tackle any data analysis task with ease.

By the end of this course, you’ll have the expertise and confidence to embark on a rewarding journey in the field of data analysis, equipped with the skills needed to excel in a variety of roles and industries. Whether you’re pursuing a career as a data analyst, business analyst, marketing analyst, or entrepreneur, this course will empower you to unlock the full potential of data and drive impactful decision-making in your personal and professional life.

Course Curriculum

Chapter 1: Introduction to Data Analysis

Lecture 1: Introduction

Lecture 2: Understanding the role of data analysis in decision-making

Lecture 3: Overview of tools and technologies used in data analysis

Lecture 4: Introduction to Excel, SQL, Power BI, and Python for data analysis

Chapter 2: Excel Essentials for Data Analysis

Lecture 1: Introduction to Excel for data manipulation and analysis

Lecture 2: Data cleaning and preparation techniques in Excel

Lecture 3: Basic statistical analysis using Excel functions

Lecture 4: Data visualization with charts and graphs in Excel

Lecture 5: What is Power Pivot

Lecture 6: Enabling Power Pivot in Excel

Lecture 7: What is Power query

Lecture 8: Connecting to data source

Lecture 9: Preparing your query

Lecture 10: Cleansing data

Lecture 11: Enhancing your query

Lecture 12: Creating a data model

Lecture 13: Build data relationships

Lecture 14: Analyse data using Pivot tables

Lecture 15: Create lookups as new fields with DAX

Lecture 16: Analyse data with Pivot charts

Lecture 17: Refreshing source data

Lecture 18: Updating queries

Lecture 19: Creating new reports

Chapter 3: Data Analysis with SQL

Lecture 1: What is SQL

Lecture 2: What are relational databases

Lecture 3: MySQL

Lecture 4: Basic database concepts

Lecture 5: MySQL Installation for Windows

Lecture 6: MySQL Installation for Macs

Lecture 7: MySQL Workbench

Lecture 8: Installing MySQL Workbench for Macs

Lecture 9: Data export and import methods

Lecture 10: Data export and import using table wizard

Lecture 11: SQL data export and import wizard

Lecture 12: Using result data export and import

Lecture 13: SQL Statement and query

Lecture 14: Analyzing data using SQL Joins

Lecture 15: Analyzing data with INNER Join

Lecture 16: Analyzing data with LEFT Join

Lecture 17: Analyzing data with RIGHT Join

Lecture 18: Analyzing data with SELF Join

Lecture 19: Analyzing data with Sub queries

Lecture 20: Analyzing data with nested sub query

Lecture 21: Analyzing data with derived tables

Lecture 22: Analyzing data with Between operator

Lecture 23: Analyzing data with IN Operator

Lecture 24: Analyzing data with LIKE Operator

Lecture 25: Analyzing data with UNION Operator

Lecture 26: Analyzing data with aggregate functions

Lecture 27: Analyzing data with AVG aggregate functions

Lecture 28: Analyzing data with COUNT aggregate functions

Lecture 29: Analyzing data with SUM aggregate functions

Lecture 30: Analyzing data with MIN aggregate functions

Lecture 31: Analyzing data with MAX aggregate functions

Lecture 32: Analyzing data with character lenght function

Lecture 33: Analyzing data with concat function

Lecture 34: Analyzing distinct data

Lecture 35: Analyzing data by grouping

Lecture 36: Analyzing data using having clause

Lecture 37: Sorting data with order by clause

Lecture 38: Filtering data with where clause

Chapter 4: Data Analysis with Power BI

Lecture 1: What is Power BI

Lecture 2: What is Power BI Desktop

Lecture 3: Setup Microsoft 365

Lecture 4: Getting started with Microsoft 365

Lecture 5: Adding user to Microsoft 365

Lecture 6: Installing Power BI Desktop

Lecture 7: Exploring Power BI Interface

Lecture 8: Power BI Overview – Part 1

Lecture 9: Power BI Overview – Part 2

Lecture 10: Power BI Overview – Part 3

Lecture 11: Components of Power BI

Lecture 12: Exploring Power BI Service

Lecture 13: Connect to web based data

Lecture 14: Clean and transform data – Part 1

Lecture 15: Clean and transform data – Part 2

Lecture 16: Combining data sources

Lecture 17: Creating Visualizations: Part 1

Lecture 18: Creating Visualizations: Part 2

Lecture 19: Publishing Reports to Power BI Service

Chapter 5: Data Analysis with Python

Lecture 1: What is Python

Lecture 2: What is Jupyter Notebook

Lecture 3: Install Python on Windows

Lecture 4: Install Python on Mac

Lecture 5: Install Jupyter Notebook with Anaconda

Lecture 6: Jupyter Notebook components

Lecture 7: Jupyter Notebook dashboard

Lecture 8: Jupyter Notebook Interface

Lecture 9: Creating a new Notebook

Lecture 10: The dataset

Lecture 11: Tabular Data

Lecture 12: Exploring Pandas DataFrame

Lecture 13: Manipulating Pandas DataFrame

Lecture 14: What is data cleaning

Lecture 15: Perform Data cleaning

Instructors

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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!

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