How To Be A Data Analyst: Essence Of Data Analysis

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Ugonna Alinnor

56:02

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1. Introduction

1. Introduction.mp4

01:16

2. Definition and role of Data analysis in the society.mp4

00:47

3. Why Organisations and individuals need data analysis.mp4

00:48

4. Definition of Data Analysis.mp4

00:48

5. What is Data Analysis.mp4

00:38

6. Importance of data analysis for businesses.mp4

00:34

7. How to use data analysis in your business.mp4

00:20

8. Another reason Data Analysis is important.mp4

00:27

9. How accurate data improves data analysis.mp4

00:33

10. Data Analysis Steps.mp4

00:26

11. Data Requirement Gathering.mp4

00:17

12. Data Collection.mp4

00:25

13. Data cleaning.mp4

00:19

14. Data Analysis tools.mp4

00:29

15. Data Interpretation.mp4

00:14

16. Data Visualisation.mp4

00:29

17. Types Of Data Analysis.mp4

00:22

18. Diagnostic Analysis.mp4

00:27

19. Predictive Analysis.mp4

00:26

20. Prescriptive Analysis.mp4

00:22

21. Statistical Analysis.mp4

00:26

22. Text Analysis.mp4

00:29

23. Data Analysis Methods.mp4

00:43

24. Qualitative Data Analysis.mp4

00:40

25. Quantitative Analysis.mp4

00:57

26. Artificial Intelligence and Machine Learning.mp4

00:27

27. Maths and Stats.mp4

00:25

28. Graphs and Visualisation.mp4

01:01

2. Data Analysis Tools and Techniques

1. Purpose of Data Analysis.mp4

00:17

2. Example of Data Analysis.mp4

00:43

3. Data Analysis Tools.mp4

00:28

4. Types Of Data Analysis.mp4

00:30

5. Text Analysis.mp4

00:31

6. Statistical Analysis.mp4

00:30

7. Descriptive Analysis.mp4

00:16

8. Inferential Analysis.mp4

00:15

9. Diagnostic Analysis.mp4

00:20

10. Predictive Analysis.mp4

00:34

11. Prescriptive Analysis.mp4

00:27

12. Data Analysis Process.mp4

00:40

13. Data Requirement Gathering.mp4

00:19

14. Data Collection.mp4

00:30

15. Data Cleaning.mp4

00:26

16. Data Analysis.mp4

00:32

17. Data Interpretation.mp4

00:19

18. Data Visualisation.mp4

00:28

19. Summary.mp4

00:37

3. Common Statistical Analysis Methods

1. The Four Common Methods Used For Statistical Analysis.mp4

00:23

2. Mean.mp4

00:35

3. How To Calculate Mean.mp4

00:21

4. Standard Deviation.mp4

00:26

5. How To Calculate Standard Deviation.mp4

00:23

6. Variance.mp4

00:31

7. Regression.mp4

00:31

8. How To Calculate Regression.mp4

00:32

9. Hypothesis Testing.mp4

00:30

4. Essential Chart Types for Data Visualisation

1. Introduction.mp4

00:44

2. How To Choose A Chart Type.mp4

00:55

3. The Foundational Four.mp4

00:22

4. Bar Chart.mp4

00:37

5. Line Charts.mp4

00:36

6. Example Of A Line Chart.mp4

00:16

7. Scatterplot.mp4

00:31

8. Data Analysis Steps.mp4

00:31

9. Example Of A Scatterplot.mp4

00:09

10. Common Variations.mp4

00:25

11. Histogram.mp4

00:14

12. Example Of A Histogram.mp4

00:08

13. Stacked Bar Chart.mp4

00:17

14. Example Of A Stacked Bar Chart.mp4

00:08

15. Bubble Plots.mp4

00:43

16. Example Of A Bubble Plot.mp4

00:06

17. Heatmaps.mp4

00:09

18. Example Of A Heatmap.mp4

00:07

19. More On Heatmaps.mp4

00:30

20. Pie Charts.mp4

00:08

21. More On Pie Charts.mp4

00:16

22. Funnel Charts.mp4

00:13

23. Adwords Conversion Funnel.mp4

00:16

24. Map-Based Plots.mp4

00:28

25. Choropleth.mp4

00:09

5. Data Analysis Myths That Can Hamper Your Business

1. Data Analysis Myths That Can Hamper Businesses.mp4

00:47

2. Data Analysis Leads To New Discoveries.mp4

00:55

3. Data Analysis Is To Expensive.mp4

00:29

4. Data Analysis Is Too Time-Intensive.mp4

00:31

5. You Need To Be An Analyst To Get Value From Data.mp4

00:25

6. All Businesses Are Driven By Data.mp4

00:33

7. Theres No Reason To Track Bounce Rate.mp4

00:32

8. Machine-made Decisions Eliminates Bias.mp4

00:40

9. Data Analytics Leads To Job Loss.mp4

00:33

10. The More Data You Gather, The Better.mp4

00:31

11. Analysis Can Drive Your Business.mp4

00:25

6. Companies That Use Big Data Analytics

1. Top Data Analytics Companies Should Follow.mp4

00:42

2. Reonomy.mp4

00:40

3. SAP.mp4

00:54

4. Sedin Technologies.mp4

00:36

5. Sisense.mp4

00:39

6. Sigma Data Systems.mp4

01:06

7. Snowflake.mp4

00:50

8. Salesforce.mp4

00:45

7. How Companies Use Data Analysis

1. How Companies Use Data Analytics.mp4

00:25

2. Benefits Of Data Analysis.mp4

00:38

3. Amazon.mp4

00:38

4. Apple.mp4

00:35

5. How Apple Uses Big Data.mp4

00:22

6. Google.mp4

00:36

7. Spotify.mp4

00:30

8. Facebook.mp4

00:28

9. Instagram.mp4

00:47

10. Starbucks.mp4

00:32

11. Netflix.mp4

00:31

Description

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

What You'll Learn?

Data cleaning, Data transformation and how to process data in order to glean insights from it
In-depth Data analysis best practises which include Data Requirement Gathering, Data collection, Data Analysis, Data Interpretation, Data Visualisation
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
Essential chart types needed for Data Visualisation such as bar chart, line chart, bubble plots, Heat maps, Pie charts, Funnel Charts and more

Who is this for?

Every student curious about Data analysis

What You Need to Know?

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

More details

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 decisions

According to Glassdoor labor statistics, the average salary for data analyst is around 80,000 dollars per year

Given 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 Analysis

This 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 andÂ Data Visualisation

Also covered are common statistical analysis methods such as Mean, Standard deviation, Regression, Hypothesis testing

After 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 Visualisation

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

Know 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 OfÂ Data Analysis

Who this course is for:
Every student curious about Data analysis

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Ugonna Alinnor is founder of Cartwheel LLC.He is a professional and sophisticated writer, author, scientist, editor, and content creator with over 15 years of experience in creating quality content for businessesAs an experienced English medical freelance writer, I believe I possess the skills and knowledge required to meet and even exceed your project requirements.With my understanding of clinical trial documentation, medical writing, technical writing and general content writing, I can create engaging and informative product guides or blog posts tailored to your specific requirements.I'm also technology and social media savvy and I have access to Chat GPT as well as Chat GPT UniversityI'm the author of the online course "Deep learning with R" I have also authored several e-books and articles on Artificial Intelligence and other related topics

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