Become A Data Analyst: Excel, Sql & Tableau - 3-In-1 Bundle

Boost Your Career with Data Analytics: Learn Excel, SQL & Tableau for Advanced Business Insights & Competitive Advantage

What you'll learn
Discover the power of Excel and use it to manipulate and analyze data like a pro.
Master SQL queries to extract, filter, and aggregate data from relational databases.
Explore Tableau's interface and create stunning visualizations that communicate insights.
Develop the skills to integrate data from multiple sources and create interactive dashboards in Tableau.
Apply best practices for data cleaning, wrangling, and transformation in Excel and SQL
Create dynamic and automated reports in Tableau that update with new data.
Use Excel and Tableau to identify trends, patterns, and outliers in data.
Develop a data-driven mindset and use data to make informed business decisions.
Apply critical thinking and problem-solving skills to data analysis challenges.

Requirements
Only a PC with any version of Excel installed is needed for this course

Description
If you are interested in becoming a data analyst, but feel overwhelmed by the technical skills required, this "Become a Data Analyst: Excel, SQL & Tableau - 3-in-1 Bundle" course is designed for you. You'll learn Excel, SQL, and Tableau - the essential tools for data analysis - and develop the skills to turn raw data into insights that drive better business decisions.In this course, you will:Develop advanced Excel skills to manipulate and analyze dataMaster SQL queries to extract data from databasesCreate stunning data visualizations in Tableau to communicate insightsLearning these skills will allow you to excel as a data analyst, and open up new career opportunities. You'll practice real-world examples and complete hands-on exercises, so you can apply your new skills to real-world situations.This course is different because it offers a comprehensive, 3-in-1 bundle approach that covers all of the key skills required to become a successful data analyst. The course is also taught in an engaging and easy-to-understand format, so you can learn at your own pace and confidently apply your skills in the workplace.What makes us qualified to teach you?The course is taught by Abhishek (MBA - FMS Delhi, B. Tech - IIT Roorkee) and Pukhraj (MBA - IIM Ahmedabad, B. Tech - IIT Roorkee). As managers in the Global Analytics Consulting firm, we have helped businesses solve their business problems using Analytics and we have used our experience to include the practical aspects of business analytics in this course. We have in-hand experience in Business Analysis.We are also the creators of some of the most popular online courses - with over 1,200,000 enrollments and thousands of 5-star reviews like these ones:This is very good, i love the fact the all explanation given can be understood by a layman - JoshuaThank you Author for this wonderful course. You are the best and this course is worth any price. - DaisyWhat is covered in this course?The analysis of data is not the main crux of analytics. It is the interpretation that helps provide insights after the application of analytical techniques that makes analytics such an important discipline. We have used the most popular analytics software tools which are MS Excel, SQL, and Tableau. This will aid the students who have no prior coding background to learn and implement Analytics and Machine Learning concepts to actually solve real-world problems of Data Analysis.Let me give you a brief overview of the coursePart 1 - Excel for data analyticsIn the first section, i.e. Excel for data analytics, we will learn how to use excel for data-related operations such as calculating, transforming, matching, filtering, sorting, and aggregating data.We will also cover how to use different types of charts to visualize the data and discover hidden data patterns.Part 2 - SQL for data analyticsIN the second section, i.e. SQL for data analytics, we will be teaching you everything in SQL that you will need for Data analysis in businesses. We will start with basic data operations like creating a table, retrieving data from a table etc. Later on, we will learn advanced topics like subqueries, Joins, data aggregation, and pattern matching.Part 3 - Data visualization using TableauIn this section, you will learn how to develop stunning dashboards, visualizations and insights that will allow you to explore, analyze and communicate your data effectively. You will master key Tableau concepts such as data blending, calculations, and mapping. By the end of the course, you will be able to create engaging visualizations that will enable you to make data-driven decisions confidently.Our PromiseTeaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet, or anything related to any topic, you can always post a question in the course or send us a direct message.Don't let technical skills hold you back from pursuing a career in data analysis. Enroll now and start your journey towards becoming a data analyst.

Overview
Section 1: Introduction

Lecture 1 Introduction

Section 2: Excel Basics

Lecture 2 Getting started with Excel

Lecture 3 Course resources

Lecture 4 This is a milestone!

Lecture 5 Worksheet basics

Lecture 6 Entering values and Formulas

Lecture 7 Data Formats

Lecture 8 Data Handling Basics - Cut, Copy, Paste

Lecture 9 Saving and Printing in Excel

Section 3: Essential Excel functions

Lecture 10 Basic Formula Operations

Lecture 11 Mathematical Functions - Part 1

Lecture 12 Mathematical Functions - Part 2

Lecture 13 Difference between RANK, RANK.AVG and RANK.EQ

Lecture 14 Textual Functions - Part 1

Lecture 15 Textual Functions - Part 2

Lecture 16 Logical Functions

Lecture 17 Date-Time Functions

Lecture 18 Lookup Functions ( V Lookup, Hlookup, Index-Match )

Section 4: Data Tools

Lecture 19 Sorting, Filtering and Data Validation

Lecture 20 Text-to-columns and remove duplicates

Lecture 21 Advanced Filter option

Section 5: Formatting data and tables

Lecture 22 Formatting data and tables

Section 6: Pivot Tables

Lecture 23 Pivot Tables

Section 7: Excel Charts

Lecture 24 Excel Charts - Categories of messages that can be conveyed

Lecture 25 Elements of charts

Lecture 26 The Easy way of creating charts

Lecture 27 Bar and column charts

Lecture 28 Formatting charts Part -1

Lecture 29 Formatting charts Part -2

Lecture 30 Line Charts

Lecture 31 Area Charts

Lecture 32 Pie and Doughnut Charts

Lecture 33 Why we should avoid Pie charts

Lecture 34 Scatter plot or XY chart

Lecture 35 Frequency Distribution and Histograms

Lecture 36 Waterfall Charts

Lecture 37 Hierarchy Charts: Sunburst and Treemap

Lecture 38 Combination charts

Lecture 39 Sparklines

Section 8: Pivot Charts

Lecture 40 Pivot Charts

Section 9: Special purpose charts

Lecture 41 Stock charts

Lecture 42 Radar charts

Lecture 43 Surface charts

Lecture 44 Heatmaps

Section 10: Named Ranges

Lecture 45 Named Ranges

Lecture 46 Indirect Functions

Section 11: Excel Shortcuts

Lecture 47 Shortcuts

Section 12: Macros

Lecture 48 Macros

Section 13: Advanced Excel

Lecture 49 Advanced Excel: Analytics in Excel

Section 14: Creative Infographics

Lecture 50 Infographic Example 1

Lecture 51 Infographic Example 2

Section 15: SQL

Lecture 52 Introduction

Section 16: Installation and getting started

Lecture 53 Installing PostgreSQL and pgAdmin in your PC

Lecture 54 If pgAdmin is not opening...

Section 17: Case Study : Demo

Lecture 55 Case Study Part 1 - Business problems

Lecture 56 Case Study Part 2 - How SQL is Used

Section 18: Fundamental SQL statements

Lecture 57 CREATE

Lecture 58 INSERT

Lecture 59 Import data from File

Lecture 60 SELECT statement

Lecture 61 SELECT DISTINCT

Lecture 62 WHERE

Lecture 63 Logical Operators

Lecture 64 UPDATE

Lecture 65 DELETE

Lecture 66 ALTER part -1

Lecture 67 ALTER part - 2

Section 19: Restore and Back-up

Lecture 68 Restore and Back-up

Lecture 69 Debugging restoration issues

Lecture 70 Creating DB using CSV files

Lecture 71 Debugging summary and Code for CSV files

Section 20: Selection commands: Filtering

Lecture 72 IN

Lecture 73 BETWEEN

Lecture 74 LIKE

Section 21: Selection commands: Ordering

Lecture 75 Side Lecture: Commenting in SQL

Lecture 76 ORDER BY

Lecture 77 LIMIT

Section 22: Alias

Lecture 78 AS

Section 23: Aggregate Commands

Lecture 79 COUNT

Lecture 80 SUM

Lecture 81 AVERAGE

Lecture 82 MIN & MAX

Section 24: Group By Commands

Lecture 83 GROUP BY

Lecture 84 HAVING

Section 25: Conditional Statement

Lecture 85 CASE WHEN

Section 26: JOINS

Lecture 86 Introductions to Joins

Lecture 87 Concepts of Joining and Combining Data

Lecture 88 Preparing the data

Lecture 89 Inner Join

Lecture 90 Left Join

Lecture 91 Right Join

Lecture 92 Full Outer Join

Lecture 93 Cross Join

Lecture 94 Intersect and Intersect ALL

Lecture 95 Except

Lecture 96 Union

Section 27: Subqueries

Lecture 97 Part-1 Subquery in WHERE clause

Lecture 98 Part-2 Subquery in FROM clause

Lecture 99 Part-3 Subquery in SELECT clause

Section 28: Views and Indexes

Lecture 100 VIEWS

Lecture 101 INDEX

Section 29: String Functions

Lecture 102 LENGTH

Lecture 103 UPPER LOWER

Lecture 104 REPLACE

Lecture 105 TRIM, LTRIM, RTRIM

Lecture 106 CONCATENATION

Lecture 107 SUBSTRING

Lecture 108 LIST AGGREGATION

Section 30: Mathematical Functions

Lecture 109 CEIL & FLOOR

Lecture 110 RANDOM

Lecture 111 SETSEED

Lecture 112 ROUND

Lecture 113 POWER

Section 31: Date-Time Functions

Lecture 114 CURRENT DATE & TIME

Lecture 115 AGE

Lecture 116 EXTRACT

Section 32: PATTERN (STRING) MATCHING

Lecture 117 PATTERN MATCHING BASICS

Lecture 118 ADVANCE PATTERN MATCHING (REGULAR EXPRESSIONS) Part -1

Lecture 119 ADVANCE PATTERN MATCHING (REGULAR EXPRESSIONS) Part 2

Section 33: Windows Functions

Lecture 120 Introduction to Window functions

Lecture 121 Introduction to Row number

Lecture 122 Implementing Row number in SQL

Lecture 123 RANK and DENSERANK

Lecture 124 NTILE function

Lecture 125 AVERAGE function

Lecture 126 COUNT

Lecture 127 SUM TOTAL

Lecture 128 RUNNING TOTAL

Lecture 129 LAG and LEAD

Section 34: COALESCE function

Lecture 130 COALESCE function

Section 35: Data Type conversion functions

Lecture 131 Converting Numbers/ Date to String

Lecture 132 Converting String to Numbers/ Date

Section 36: User Access Control functions

Lecture 133 User Access Control -1 Grant and Revoke

Lecture 134 User Access Control -2 Drop, Alter users

Section 37: Nail that Interview!

Lecture 135 Showcasing SQL Skills with HackerRank Stars

Lecture 136 Tablespace

Lecture 137 PRIMARY KEY & FOREIGN KEY

Lecture 138 ACID compliance

Lecture 139 Truncate

Section 38: Performance tuning tips

Lecture 140 TIP 1 (EXPLAIN)

Lecture 141 TIP 2

Lecture 142 TIP 3

Lecture 143 TIP 4 (VACCUM)

Lecture 144 TIP 5

Lecture 145 TIP 6 ( STRING FUNCTIONS)

Lecture 146 TIP 7 (JOINS)

Lecture 147 TIP 8 (SCHEMAS)

Section 39: Database Basics

Lecture 148 What is SQL?

Lecture 149 Tables and DBMS

Lecture 150 Types of SQL commands

Lecture 151 PostgreSQL

Section 40: TABLEAU

Lecture 152 Introduction

Lecture 153 Tableau Products

Section 41: Installation and getting started

Lecture 154 Installing Tableau desktop and Public

Lecture 155 About the data

Lecture 156 Connecting to data

Lecture 157 Live vs Extract

Section 42: Combining data to create Data model

Lecture 158 Combining data from multiple tables

Lecture 159 Relationships in Tableau

Lecture 160 Joins in Tableau

Lecture 161 Types of Joins in Tableau

Lecture 162 Union in Tableau

Lecture 163 Physical Logical layer and Data models

Lecture 164 The visualization screen - Sheet

Section 43: Data categorization in Tableau

Lecture 165 Types of Data - Dimensions and Measures

Lecture 166 Types of Data - Discreet and Continuous

Lecture 167 Changing Data type in Tableau

Section 44: Most used charts

Lecture 168 Bar charts

Lecture 169 Line charts

Lecture 170 Scatterplots

Section 45: Customizing charts using Marks shelf

Lecture 171 Marks cards

Lecture 172 Dropping Dimensions and Measures on marks card

Lecture 173 Dropping Dimensions on Line chart

Lecture 174 Adding marks in scatterplot

Section 46: Other important charts

Lecture 175 Text tables, heat map and highlight tables

Lecture 176 Pie charts

Lecture 177 Area charts

Lecture 178 Creating custom hierarchy

Lecture 179 Tree map

Lecture 180 Dual combination charts

Lecture 181 Creating Bins

Lecture 182 Histogram

Section 47: Grouping and Filtering data

Lecture 183 Grouping Data

Lecture 184 Filtering data

Lecture 185 Dimension filters

Lecture 186 Measure filters

Lecture 187 Date-Time filters

Lecture 188 Filter options

Lecture 189 Types of filters and order of operation

Lecture 190 Customizing visual filters

Lecture 191 Sorting options

Section 48: Map chart in Tableau

Lecture 192 How to make a map chart

Lecture 193 Considerations before making a Map chart

Lecture 194 Marks card for customizing maps

Lecture 195 Customizing maps using map menu

Lecture 196 Layers in a Map

Lecture 197 Visual toolbar on a map

Lecture 198 Custom background images

Lecture 199 Territories in maps

Lecture 200 Data blending for missing geocoding

Section 49: Calculations and Analytics

Lecture 201 Calculated fields in Tableau

Lecture 202 Functions in Tableau

Lecture 203 Table calculations theory

Lecture 204 Table calculations in Tableau

Lecture 205 Understanding LOD expressions

Lecture 206 LOD expressions examples

Lecture 207 Analytics pane

Section 50: Sets and Parameters

Lecture 208 Understanding sets in Tableau

Lecture 209 Creating Sets in Tableau

Lecture 210 Parameters

Section 51: Dashboard and Story

Lecture 211 Dashboard part -1

Lecture 212 Dashboard part - 2

Lecture 213 Story

Section 52: Appendix

Lecture 214 Connecting to SQL data source

Lecture 215 Connecting to cloud storage services

Section 53: Congratulations and about your certificate

Lecture 216 The final milestone!

Lecture 217 Bonus lecture

Anyone curious to master Data Analysis in a short span of time,Individuals who want to pursue a career in data analysis, business intelligence, or data visualization,Professionals who want to upskill and add value to their existing roles by learning data analysis,Aspiring data analysts who want to develop the skills to turn raw data into actionable insights,Small business owners who want to use data to drive better decision-making in their companies

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