How To Be A Data Analyst: Essence Of Data Analysis
Published 12/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 235.82 MB | Duration: 0h 56m
Published 12/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 235.82 MB | Duration: 0h 56m
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