How To Be A Data Analyst: Essence Of Data Analysis

This is a Beginner's Guide On How To Be A Data Analyst

What you'll learn

Master data cleaning, transformation and processing in order to glean insights from it

Know in depth Data analysis best practises which include Data Requirement Gathering, Data collection, Data Analysis, Data Interpretation, Data Visualisation

Master Data Analysis techniques like Text Analysis, Statistical Analysis, Diagnostic Analysis, Predictive Analysis and Prescriptive Analysis

Learn statistical analysis methods such as Mean, Standard deviation, Regression and Hypothesis testing

Learn the essential chart types needed for Data Visualisation such as bar chart, line chart, bubble plots, Heat maps, Pie charts, Funnel Charts and more

Requirements

No programming experience needed, you'll learn everything you need to know in this course

Description

A Data analyst is someone who is an expert in cleaning, changing, and processing raw data in order to extract actionable, relevant information that helps businesses make more informed decisionsAccording to Glassdoor labor statistics, the average salary for data analyst is around 80,000 dollars per yearGiven the demand for highly skilled data analysts, there has been a corresponding increase in salaries too.And the demand for data analysts and data science professionals has been growing these past few years and especially so since the Covid-19 pandemic.Data analysis is a process of cleaning, transforming and modelling data to discover useful information for business decision-making. For you to be a Data Analyst you need to be an expert in Data AnalysisThis well-curated online course covers important topics in Data Analysis, as well how companies are making use of these popular tools and techniques to make key decisions in their organisation. Topics covered here include: Data Requirement Gathering, Data Collection, Data Cleaning, Data Analysis, Data Interpretation and  Data VisualisationAlso covered are common statistical analysis methods such as Mean, Standard deviation, Regression, Hypothesis testingAfter taking this Data Analysis online course, you should be able to:Know in depth Data analysis best practises which include Data Requirement Gathering, Data collection, Data Analysis, Data Interpretation, Data VisualisationMaster Data Analysis techniques like Text Analysis, Statistical Analysis, Diagnostic Analysis, Predictive Analysis and Prescriptive AnalysisKnow in details Data Analysis Tools and Techniques, Common Statistical Analysis Methods, Essential Chart Types for Data Visualisation, Data Analysis Myths That Can Hamper Your Business, Companies That Use Big Data Analytics and How Companies Make Use Of  Data Analysis

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Definition and role of Data analysis in the society

Lecture 3 Why Organisations and individuals need data analysis

Lecture 4 Definition of Data Analysis

Lecture 5 What is Data Analysis?

Lecture 6 Importance of data analysis for businesses

Lecture 7 How to use data analysis in your business

Lecture 8 Another reason Data Analysis is important

Lecture 9 How accurate data improves data analysis

Lecture 10 Data Analysis Steps

Lecture 11 Data Requirement Gathering

Lecture 12 Data Collection

Lecture 13 Data cleaning

Lecture 14 Data Analysis tools

Lecture 15 Data Interpretation

Lecture 16 Data Visualisation

Lecture 17 Types Of Data Analysis

Lecture 18 Diagnostic Analysis

Lecture 19 Predictive Analysis

Lecture 20 Prescriptive Analysis

Lecture 21 Statistical Analysis

Lecture 22 Text Analysis

Lecture 23 Data Analysis Methods

Lecture 24 Qualitative Data Analysis

Lecture 25 Quantitative Analysis

Lecture 26 Artificial Intelligence and Machine Learning

Lecture 27 Maths and Stats

Lecture 28 Graphs and Visualisation

Section 2: Data Analysis: Tools and Techniques

Lecture 29 Purpose of Data Analysis

Lecture 30 Example of Data Analysis

Lecture 31 Data Analysis Tools

Lecture 32 Types Of Data Analysis

Lecture 33 Text Analysis

Lecture 34 Statistical Analysis

Lecture 35 Descriptive Analysis

Lecture 36 Inferential Analysis

Lecture 37 Diagnostic Analysis

Lecture 38 Predictive Analysis

Lecture 39 Prescriptive Analysis

Lecture 40 Data Analysis Process

Lecture 41 Data Requirement Gathering

Lecture 42 Data Collection

Lecture 43 Data Cleaning

Lecture 44 Data Analysis

Lecture 45 Data Interpretation

Lecture 46 Data Visualisation

Lecture 47 Summary

Section 3: Common Statistical Analysis Methods

Lecture 48 The Four Common Methods Used For Statistical Analysis

Lecture 49 Mean

Lecture 50 How To Calculate Mean

Lecture 51 Standard Deviation

Lecture 52 How To Calculate Standard Deviation

Lecture 53 Variance

Lecture 54 Regression

Lecture 55 How To Calculate Regression

Lecture 56 Hypothesis Testing

Section 4: Essential Chart Types for Data Visualisation

Lecture 57 Introduction

Lecture 58 How To Choose A Chart Type

Lecture 59 The Foundational Four

Lecture 60 Bar Chart

Lecture 61 Line Charts

Lecture 62 Example Of A Line Chart

Lecture 63 Scatterplot

Lecture 64 Data Analysis Steps

Lecture 65 Example Of A Scatterplot

Lecture 66 Common Variations

Lecture 67 Histogram

Lecture 68 Example Of A Histogram

Lecture 69 Stacked Bar Chart

Lecture 70 Example Of A Stacked Bar Chart

Lecture 71 Bubble Plots

Lecture 72 Example Of A Bubble Plot

Lecture 73 Heatmaps

Lecture 74 Example Of A Heatmap

Lecture 75 More On Heatmaps

Lecture 76 Pie Charts

Lecture 77 More On Pie Charts

Lecture 78 Funnel Charts

Lecture 79 Adwords Conversion Funnel

Lecture 80 Map-Based Plots

Lecture 81 Choropleth

Section 5: Data Analysis Myths That Can Hamper Your Business

Lecture 82 Data Analysis Myths That Can Hamper Businesses

Lecture 83 Data Analysis Leads To New Discoveries

Lecture 84 Data Analysis Is To Expensive

Lecture 85 Data Analysis Is Too Time-Intensive

Lecture 86 You Need To Be An Analyst To Get Value From Data

Lecture 87 All Businesses Are Driven By Data

Lecture 88 There's No Reason To Track Bounce Rate

Lecture 89 Machine-made Decisions Eliminates Bias

Lecture 90 Data Analytics Leads To Job Loss

Lecture 91 The More Data You Gather, The Better

Lecture 92 Analysis Can Drive Your Business

Section 6: Companies That Use Big Data Analytics

Lecture 93 Top Data Analytics Companies Should Follow

Lecture 94 Reonomy

Lecture 95 SAP

Lecture 96 Sedin Technologies

Lecture 97 Sisense

Lecture 98 Sigma Data Systems

Lecture 99 Snowflake

Lecture 100 Salesforce

Section 7: How Companies Use Data Analysis

Lecture 101 How Companies Use Data Analytics

Lecture 102 Benefits Of Data Analysis

Lecture 103 Amazon

Lecture 104 Apple

Lecture 105 How Apple Uses Big Data

Lecture 106 Google

Lecture 107 Spotify

Lecture 108 Facebook

Lecture 109 Instagram

Lecture 110 Starbucks

Lecture 111 Netflix

Every student curious about Data analysis