Data Analytics Mastery

A Complete Data Analytics Course on Python, SQL, PowerBi, Tableau Advanced Excel and more..

What you'll learn

Gain a comprehensive understanding of data analytics concepts, including data collection, cleaning, and processing.

Learn how to use industry-standard tools like Python, R, SQL, and Excel for data analysis.

Master the art of visualizing data using tools like Tableau and Power BI to present insights effectively.

Develop a strong foundation in statistical methods and how they apply to data analytics.

Work on real-world projects that simulate industry challenges, giving you practical experience.

Understand the concepts of big data and learn how to work with large datasets using tools like Hadoop and Spark.

Learn various data mining techniques to discover patterns and relationships in large datasets.

Understand predictive modeling techniques to forecast future trends based on historical data.

Develop the ability to make informed business decisions using data-driven insights.

Learn about the ethical issues related to data privacy and security.

Enhance your Excel skills, including data manipulation, advanced formulas, and pivot tables.

Learn how to create interactive dashboards to monitor and present data in real-time.

Improve your ability to communicate data insights clearly to non-technical stakeholders.

Prepare for a career in data analytics with guidance on resume building, interview preparation, and job search strategies.

Requirements

No prior experience is required. We will start from the very basics

Description

The Importance of Data Analytics in Today’s WorldIn the modern era, data has become the lifeblood of decision-making, innovation, and competitive advantage. Data analytics, the practice of examining raw data to extract meaningful insights, is essential for businesses, governments, and organizations across the globe. By transforming vast amounts of data into actionable intelligence, data analytics enables informed decision-making that drives success. It empowers organizations to move beyond intuition, using factual analysis to identify opportunities, mitigate risks, and adapt to changing market conditions with greater precision.Data analytics also plays a crucial role in enhancing operational efficiency. By examining data from various sources—such as supply chains, customer interactions, and internal processes—businesses can identify inefficiencies and optimize their operations. This leads to cost savings, better resource management, and improved customer satisfaction, all of which contribute to a company’s bottom line. Moreover, the predictive power of data analytics allows organizations to anticipate future trends and behaviors, positioning them to be proactive rather than reactive in their strategies.Beyond the business world, data analytics is increasingly being used to address social and ethical challenges. Governments and non-profits leverage data to tackle issues like public health, climate change, and social inequality. As technology continues to evolve, the importance of data analytics will only grow, making it a vital skill for navigating the complexities of the future. In essence, data analytics is not just a tool for understanding the present but a powerful means to shape the future.Why Choose YodaafyAt Yodaafy, we believe in learning by doing. Our course is designed with a hands-on approach that ensures you not only understand theoretical concepts but also know how to apply them in real-world situations. With expert instructors, a supportive learning environment, and a curriculum aligned with industry needs, Yodaafy is your gateway to a successful career in data analytics.Course Includes 30+ Hours of on-Demand video 200+ Coding Exercises Downloadable resourcesCertificate of CompletionObjectivesDevelop Foundational KnowledgeEnhance Technical SkillsApply Data-Driven Decision MakingFoster Critical Thinking and Problem-SolvingWhat We Will Cover in the Yodaafy Data Analytics CourseThe Yodaafy Data Analytics course is designed to provide a comprehensive understanding of data analytics through a hands-on approach. Below is an overview of the key topics covered in the course:Microsoft Excel for Data AnalyticsExcel Fundamentals: Learn the basics of Excel, including navigating the interface, customizing toolbars, and understanding workbook structures.Data Entry and Formulas: Gain proficiency in entering and editing text, working with numeric data, and creating basic formulas with relative and absolute references.Excel Functions: Master key functions such as SUM, MIN, MAX, AVERAGE, and COUNT, and explore the use of AutoSum and AutoFill commands.Worksheet Management: Discover how to modify worksheets, including moving/copying data, inserting/deleting rows and columns, and formatting data with font, borders, and conditional formatting.SQL for Data ManagementMySQL Basics: Start with the fundamentals of MySQL, including database creation, table management, and basic data manipulation tasks like inserting, updating, and deleting records.Advanced SQL Functions: Delve into more complex SQL operations such as DISTINCT, ORDER BY, LIMIT, and GROUP BY, as well as working with subqueries.Joins and Relationships: Learn how to perform INNER, LEFT, RIGHT, and FULL OUTER joins, and understand how to manage one-to-many and many-to-many relationships in databases.Python for Data AnalyticsPython Basics: Begin with Python programming fundamentals, covering variables, data types, operators, lists, dictionaries, and control flow with if-else statements and loops.Data Manipulation with Python: Explore Python’s powerful data manipulation libraries like NumPy and Pandas, and learn how to visualize data using Matplotlib.Machine Learning Introduction: Get introduced to machine learning concepts, including regression analysis, decision trees, and data distribution techniques.Power BI for Data VisualizationPower BI Fundamentals: Understand the importance of data visualization, learn the basics of Power BI, and how it compares to other tools like Tableau.Data Import and Cleaning: Learn how to import datasets into Power BI, clean and format data, and use Power BI’s Query Editor to manipulate datasets.Advanced Power BI Techniques: Explore advanced Power BI features such as creating data models, merging/joining tables, and using DAX functions for deeper analysis.Tableau for Data VisualizationTransforming Data into Visualizations: Enable learners to transform raw data into meaningful visualizations that drive business decisions.Data Connection and Cleaning: Cover the basics of connecting to data sources and cleaning datasets.Creating Visual Representations: Teach learners to create complex visual representations, including heat maps, bar charts, and line graphs.Interactive Dashboards and Reports:By the end of the module, learners will be able to create interactive dashboards and reports.Effective Communication of Insights: Equip learners with the skills to effectively communicate data insights to stakeholders.This curriculum ensures that you gain a solid foundation in data analytics, with practical skills in the most widely used tools in the industry. Whether you're aiming to enhance your current role or pivot to a new career, this course equips you with the essential knowledge to succeed in the data-driven world.

Overview

Section 1: Microsoft Excel Advanced

Lecture 1 Introduction to Excel

Lecture 2 Functions and Formulas

Lecture 3 Understanding the Count Functions

Lecture 4 Exploring Countif and Sumif functions

Lecture 5 Understanding Countifs and Sumifs functions

Lecture 6 Logical Functions

Lecture 7 Sorting and Filtering

Lecture 8 Protecting workbook & worksheet

Lecture 9 Data Validation

Lecture 10 Conditional Formatting

Lecture 11 Index Match Function

Lecture 12 Exploring Charts

Lecture 13 Pivot Tables

Lecture 14 Power Pivot

Lecture 15 Financial Functions

Lecture 16 Excel Scenario Manager and Goal Seek

Lecture 17 Understanding VLOOKUP & HLOOKUP

Lecture 18 Macro Explained

Lecture 19 Excel Templates

Section 2: MS SQL Server

Lecture 20 Introduction to Data & Databases

Lecture 21 Understanding Database Structures

Lecture 22 Introduction to SQL

Lecture 23 Basic Data Operations

Lecture 24 Advanced SQL Features

Lecture 25 Data Filtering & Grouping

Lecture 26 Constraints & SETO Operations

Lecture 27 Subquery, CTE's & Joins

Lecture 28 Advance Database Objects

Section 3: Python

Lecture 29 Introduction to Python

Lecture 30 Python Installation

Lecture 31 Getting Started With Python

Lecture 32 Syntax

Lecture 33 Comments

Lecture 34 Variables

Lecture 35 Data Types

Lecture 36 Casting

Lecture 37 Strings

Lecture 38 Boolean

Lecture 39 Operators

Lecture 40 Sets

Lecture 41 Tuples

Lecture 42 Lists

Lecture 43 Dictionaries

Lecture 44 If-Else

Lecture 45 While Loop

Lecture 46 For Loop

Lecture 47 File Handling

Lecture 48 Read Files

Lecture 49 Write / Create Files

Lecture 50 Delete Files

Section 4: Microsoft PowerBI

Lecture 51 Introduction to PowerBI

Lecture 52 PowerBI Components

Lecture 53 Download and Install PowerBI Desktop

Lecture 54 Explore the PowerBI Desktop

Lecture 55 Loading CSV & EXCEL file in PowerBI

Lecture 56 Power Query in PowerBI - Data Transformation

Lecture 57 Cleaning Data with Query Editor

Lecture 58 Adding new column in Power Query

Lecture 59 Merge Query in PowerBI

Lecture 60 Pivoting & Unpivoting

Lecture 61 Append Query in PowerBI

Lecture 62 Fact & Dimension Table

Lecture 63 Managing Relationship in PowerBI

Lecture 64 One to One & One to Many Relationship

Lecture 65 Many to Many Relationships

Lecture 66 Cross Filter Direction

Lecture 67 Basic Charts in PowerBI - Table & Matrix

Lecture 68 Formatting the PowerBI Visual

Lecture 69 Filter Pane

Lecture 70 Slicer and Sync Slicer

Lecture 71 Edit Interaction

Lecture 72 Drill Down and Drill Through

Lecture 73 Buttons

Lecture 74 Selection Pane

Section 5: Tableau

Lecture 75 Introduction to Tableau

Lecture 76 Download and Install Tableau Desktop (Part 1)

Lecture 77 Download and Install Tableau Desktop (Part 2)

Lecture 78 Connecting with diffrent database

Lecture 79 Live vs Extract

Lecture 80 Data Types in Tableau

Lecture 81 View Data

Lecture 82 Drill down & Hierarchies in Tableau

Lecture 83 Sorting in Tableau

Lecture 84 Grouping in Tableau

Lecture 85 Measure Names and Values

Lecture 86 Discrete Vs Continuous

Lecture 87 Tableau Parameter

Lecture 88 Combining in Tableau

Lecture 89 Sets

Lecture 90 Tableau Filters

Lecture 91 Context Filters

Lecture 92 Action Filters

Lecture 93 Colour

Lecture 94 Size

Lecture 95 Label

Lecture 96 Tooltips

Lecture 97 Shapes

Lecture 98 Details

Lecture 99 Font

Lecture 100 Alignment

Lecture 101 Shading

Lecture 102 Dashboard Function

Lecture 103 Publishing to Tableau Public

Lecture 104 Exporting Data

Lecture 105 Introduction to Charts

Lecture 106 Bar Charts and Stacked Bar Charts

Lecture 107 Line Charts

Lecture 108 Introduction to Maps

Lecture 109 Map Options

Lecture 110 World Maps

Lecture 111 Tree Maps

Lecture 112 Funnel Charts

Lecture 113 Waterfall Charts

Lecture 114 Pie Charts

Aspiring Data Analysts: If you're new to data analytics, this course will provide you with the foundational skills to start your career.,Working Professionals: Enhance your existing skills and stay ahead in your field by learning the latest data analytics techniques.,Business Professionals: Learn how to incorporate data-driven decision-making into your strategic planning processes.