How To Be A Data Analyst: Essence Of Data Analysis
This is a Beginner's Guide On How To Be A Data Analyst
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What You Will 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
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
Data analysis is a process of cleaning, transforming and modelling data to discover useful information for business decision-making.
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.
In this course, I tried to explain data analysis and analytics in a way someone without a background in maths will understand as well as showing you the tools in which you can perform production level data analysis
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 and 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 Of Data Analysis
Who Should Attend!
- Every student curious about Data analysis