How To Be A Data Analyst: Essence Of Data Analysis

Published 12/2023
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 56m | Size: 380 MB

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 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 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 this course is for
Every student curious about Data analysis

HomePage