Become A Data Analyst - Tableau Python Power Bi Sql

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Become A Data Analyst - Tableau | Python | Power Bi | Sql
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.40 GB | Duration: 10h 22m​

Mastering Analytics: From Data Visualization to Business Intelligence

What you'll learn
Understand the role and responsibilities of a Data Analyst in various industries.
Gain a foundational understanding of key data analysis and visualization tools, including Tableau, Python, Google Data Studio, and Power BI.
Learn to set up Tableau Public Desktop and navigate its interface for data analysis and visualization projects.
Master the process of connecting to various data sources within Tableau and performing data joins on related datasets.
Acquire the skills to clean and preprocess data in Tableau to ensure accuracy and relevance in analysis.
Develop the ability to create compelling data visualizations and dashboards in Tableau that tell a story or reveal insights.
Install Anaconda and understand the differences between Anaconda and Miniconda for managing Python environments.
Get familiar with Jupyter Notebook as an interactive computational environment for Python programming.
Understand the basics of Python programming, including expressions, statements, data types, and variables.
Learn to work with Python data structures such as lists, tuples, dictionaries, and sets for efficient data manipulation.
Master Python's control structures, including conditional statements and loops, for complex data analysis tasks.
Explore the use of Python functions and modules to organize and reuse code effectively.
Dive into data analysis with Python using the Pandas library for data manipulation and analysis.
Practice data cleaning techniques in Python to prepare datasets for analysis.
Learn the fundamentals of data visualization in Python
Gain an introductory understanding of Google Data Studio for creating interactive reports and dashboards.
Explore the process of connecting Google Data Studio to different data sources and importing data.
Learn to create and customize various types of visualizations in Google Data Studio, including charts, tables, and geo maps.
Understand the basics of Power BI, including setting up Microsoft 365 and installing Power BI Desktop.
Master data transformation and modeling in Power BI to create compelling data visualizations.
Learn the process of publishing reports to Power BI Service and building interactive dashboards.
Acquire foundational knowledge in SQL for querying and analyzing data stored in relational databases.
Understand MySQL database concepts, installation, and the use of MySQL Workbench for database management.
Learn advanced SQL techniques for data analysis, including table joins, subqueries, and the use of aggregate functions to summarize data.

Requirements
No prior experience in data analysis or programming is required. This course starts with foundational concepts, making it accessible for beginners.
Basic Computer Literacy: Comfort with operating computers and navigating the internet will be beneficial.
Familiarity with Excel: While not mandatory, basic knowledge of Excel or any spreadsheet software can be helpful as it introduces concepts like data manipulation and simple formulas, which are foundational to data analysis.
A Computer: A laptop or desktop with internet connectivity is essential for accessing course materials, video lectures, and software used in the course.
Software Installation: You will need to install specific software such as Tableau Public (free version), Anaconda for Python, Google Data Studio (free web-based tool), and Microsoft Power BI Desktop (free version). Installation guides and resources will be provided in the course.
Web Browser: A modern web browser (like Chrome, Firefox, or Edge) will be required to access Google Data Studio and other online resources.

Description
Embark on a transformative journey to become a skilled Data Analyst with our comprehensive course: "Become a Data Analyst - Tableau | Python | Google Data Studio | BI | SQL." This meticulously designed course aims to equip you with the essential tools and techniques of data analysis, visualization, and business intelligence, ensuring you emerge as a proficient data analyst ready to tackle real-world challenges.Course Overview:Introduction to Data Analysis: Dive into the world of data analysis by understanding the pivotal role of a Data Analyst. Explore the responsibilities, tools, and the impact of data analysis in driving business decisions and strategies.Mastering Tableau for Data Visualization: Unlock the power of Tableau, the leading visualization tool, starting from setup to advanced data manipulation techniques. Learn through hands-on exercises on connecting data sources, cleaning data, and crafting compelling stories through visualizations.Python and Jupyter Notebook for Data Analysis: Venture into Python programming, a cornerstone for any Data Analyst. From basic syntax to complex functions, this section covers it all, including an in-depth exploration of Jupyter Notebook for executing Python code in an interactive environment.Exploring Google Data Studio: Navigate through Google Data Studio to create dynamic reports and dashboards. Gain proficiency in importing data, connecting to various data sources, and visualizing data to uncover insights.Analyzing Data with Power BI: Step into the world of Power BI, a premier business intelligence platform. Learn to install, connect to data, transform datasets, and visualize insights, culminating in the publication of reports and dashboards.SQL and MySQL for Data Management and Analysis: Build a strong foundation in SQL and MySQL, from database concepts to advanced data analysis techniques. Master table joins, aggregate functions, and the art of querying databases to extract meaningful information.Advanced Data Analysis Techniques: Elevate your skills with advanced SQL techniques, including inner, left, right, and self joins, subqueries, and the use of aggregate functions to perform complex data analysis.Throughout this course, you'll engage in practical exercises and projects, applying what you've learned in real-world scenarios. Whether you're new to data analysis or looking to enhance your skills, this course offers a path to mastery across the most powerful data analysis and visualization tools available today.Prepare to transform data into actionable insights and propel your career forward as a Data Analyst. Join us on this journey to mastering the art and science of data analysis.

Overview
Section 1: Introduction to Data Analysis

Lecture 1 Introduction

Lecture 2 What is a Data Analyst

Lecture 3 The role and responsibilities of a Data Analyst

Lecture 4 Overview of Data Analysis Tools

Section 2: Introduction to Tableau and Setup

Lecture 5 What is Tableau

Lecture 6 Tableau Public Desktop

Lecture 7 Tableau Public Desktop Overview: Part 1

Lecture 8 Tableau Public Desktop Overview: Part 2

Lecture 9 Tableau Online

Lecture 10 Tableau Data Sources

Lecture 11 Tableau File Types

Section 3: Data Analysis and Visualization with Tableau

Lecture 12 Connecting to a data source

Lecture 13 Join related data sources

Lecture 14 Join data sources with inconsistent fields

Lecture 15 Data Cleaning

Lecture 16 Exploring Tableau Interface

Lecture 17 Reordering Visualization

Lecture 18 Change Summary

Lecture 19 Split text into multiple columns

Lecture 20 Presenting data using stories

Section 4: Python and Jupyter Notebook Setup

Lecture 21 What is Jupyter Notebook

Lecture 22 Anaconda vs Miniconda

Lecture 23 Installing Anaconda on a Mac

Lecture 24 Verify Anaconda installation on mac

Lecture 25 Installing Anaconda on Windows

Lecture 26 Verify Anaconda on Windows

Lecture 27 What is Anaconda Navigator

Lecture 28 Introduction to Anaconda Navigator

Lecture 29 Anaconda Navigator Overview

Lecture 30 Installing Jupyter Notebook using Anaconda

Lecture 31 How to start Jupyter Notebook Server

Lecture 32 Creating a new notebook

Section 5: Python Fundamentals

Lecture 33 What is Python

Lecture 34 Python Expressions

Lecture 35 Python Statements

Lecture 36 Python Comments

Lecture 37 Python Data Types

Lecture 38 Casting Data Types

Lecture 39 Python Variables

Lecture 40 Python List

Lecture 41 Python Tuple

Lecture 42 Python Dictionaries

Lecture 43 Python Operators

Lecture 44 Python Conditional Statements

Lecture 45 Python Loops

Lecture 46 Python Functions

Section 6: Data Analysis with Python

Lecture 47 Kaggle Data Sets

Lecture 48 Tabular Data

Lecture 49 Exploring Pandas DataFrame

Lecture 50 Manipulating a Pandas DataFrame

Lecture 51 What is data cleaning

Lecture 52 Basic data cleaning

Lecture 53 What is data visualization

Lecture 54 Visualizing Qualitative Data

Lecture 55 Visualizing Quantitative Data

Section 7: Data Analysis and visualization with Google Data Studio

Lecture 56 What is Google Data Studio

Lecture 57 How to access Google Data Studio

Lecture 58 Exploring Google Data Studio Interface

Lecture 59 Data sources and connectors

Lecture 60 Importing data into data studio

Lecture 61 Connecting to sample data source

Lecture 62 Creating data visualization

Lecture 63 Importing data into Googlesheets

Lecture 64 Connecting to Googlesheets

Lecture 65 What are dimensions

Lecture 66 What are metrics

Lecture 67 Data refresh frequency

Lecture 68 Exploring edit and view modes in reports

Lecture 69 Creating a Pie Chart

Lecture 70 Creating a Bar Chart

Lecture 71 Adding a table to report

Lecture 72 Sorting data in columns

Lecture 73 Add bars to table metrics columns

Lecture 74 Creating a time series chart

Lecture 75 Customizing a time series chart

Lecture 76 Creating a Geo Chart

Lecture 77 Creating calculated fields

Lecture 78 Data cleaning using calculated fields

Lecture 79 Control Filters

Lecture 80 Adding a date range control

Lecture 81 Formatting your dashboard

Section 8: Analyzing Data and Visualization with Power BI

Lecture 82 What is Power BI

Lecture 83 Microsoft 365 Setup

Lecture 84 Exploring Microsoft 365

Lecture 85 Installing Power BI Desktop

Lecture 86 Exploring Power BI Desktop Interface

Lecture 87 Connecting to data

Lecture 88 Transforming Data

Lecture 89 Data Modelling

Lecture 90 Visualizing Data

Lecture 91 Publishing reports to Power BI Service

Lecture 92 Building a dashboard

Lecture 93 Collaborating and sharing

Section 9: Introduction to MySQL and Setup

Lecture 94 What is SQL

Lecture 95 What is MySQL

Lecture 96 Database Concepts

Lecture 97 Installing MySQL (Windows)

Lecture 98 Installing MySQL (Mac )

Lecture 99 What is MySQL Workbench

Lecture 100 Installing MySQL Workbench (Mac)

Lecture 101 MySQL Data Types

Lecture 102 Overview of using MySQL and SQL for Data Analysis

Lecture 103 Introduction to Databases

Section 10: Data Analysis with SQL

Lecture 104 Introduction to Table Joins

Lecture 105 Analysing data using SQL INNER Join

Lecture 106 Analysing data using SQL LEFT Join

Lecture 107 Analysing data using SQL RIGHT Join

Lecture 108 Analysing data using SQL SELF Join

Lecture 109 Analysing data using Sub Query

Lecture 110 Analysing data using SQL Nested Sub Query

Lecture 111 Introduction to Aggregate functions

Lecture 112 Analysing data using SQL AVG Aggregate Function

Lecture 113 Analysing data using SQL COUNT Aggregate Function

Lecture 114 Analysing data using SQL SUM Aggregate Function

Lecture 115 Analysing data using SQL MIN Aggregate Function

Lecture 116 Analysing data using SQL MAX Aggregate Function

Lecture 117 Aggregate functions in SQL GROUPBY Clause

Lecture 118 Aggregate functions in SQL HAVING Clause

Lecture 119 Filtering data with the WHERE Clause

Lecture 120 Sorting data with ORDER BY Clause

Individuals looking to pivot into a data-driven career will find this course an invaluable stepping stone. Whether you're transitioning from a non-technical role or seeking to enter the tech industry, our comprehensive curriculum will guide you through the essentials of data analysis, visualization, and business intelligence tools.,Aspiring data analysts with little to no prior experience in the field are prime candidates for this course. We start with the basics, ensuring that learners gain a solid foundation in data analysis concepts and tools, making the course ideal for those who are starting their journey in data analytics.,College students or recent graduates in fields such as business, economics, computer science, or any other discipline who wish to enhance their data analysis skills will benefit significantly. This course can complement your academic knowledge, providing practical, hands-on experience with tools and techniques used in the industry.,Working professionals in roles that involve data handling, reporting, or decision-making, such as business analysts, marketing professionals, and project managers, will find the course content directly applicable to their work. Enhancing your data analysis skills can lead to improved job performance, opportunities for advancement, or even a specialisation shift within your career.,Entrepreneurs who need to make data-driven decisions to grow their business will benefit from learning how to analyze data effectively. This course will empower you to understand your business data better, identify trends, and make informed decisions.,Individuals with a keen interest in data, technology, and analytics, looking to explore new skills or understand the world of data analysis better, will find the course engaging and enlightening. It's an excellent opportunity for personal growth and intellectual stimulation.

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