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Data Analysts Toolbox

Data Analysts Toolbox

Free Practice Test

  • TypeExam Format
  • No. of Questions10
  • AccessImmediate
  • Access DurationLife Long Access
  • Exam DeliveryOnline
  • Test ModesPractice

Practice Exam

  • TypeExam Format
  • No. of Questions100
  • AccessImmediate
  • Access DurationLife Long Access
  • Exam DeliveryOnline
  • Test ModesPractice, Exam

Online Course

  • Content TypeVideo
  • DeliveryOnline
  • AccessImmediate
  • Access DurationLife Long Access
  • No. of Videos203
  • No. of hours21+ hrs

Data Analysts Toolbox

Data Analysts Toolbox consists of tools such as Excel, Python, and Power BI.These tools are useful and strong. These tools help to perform complex data analysis. This Data Analysts Toolbox group is focused on halfway Excel users who are new to Python and Power BI.

Table of Contents

  • Advanced Pivot Tables: Introduction
  • Importing Data
  • Preparing Data for Analysis
  • Creating and Manipulating Pivot Tables
  • Formatting a Pivot Table
  • Value Field Settings
  • Sorting and Filtering
  • Interacting with a Pivot Table
  • Calculations
  • Pivot Charts
  • Conditional Formatting
  • Dashboards
  • Summary
  • Introduction to Power Pivot and Power Query
  • Getting Started with Power Query
  • Useful Power Query Features
  • Creating a Data Model
  • Data Analysis Expressions (DAX)
  • Data Analysis Expressions (DAX) Measures
  • Pivot Tables and Slicers
  • Introduction to Power BI
  • Power BI: Getting and Transforming Data
  • Power BI: Data Modelling
  • Introduction to Data Analysis Expressions (DAX) Measures
  • Power BI: Report Design
  • Power BI: Editing Interactions and Filters
  • Power BI Service
  • Python: The Workplace Tech Divide
  • Introduction to Python
  • Basic Data Types
  • Python Built-in Functions
  • Variables and Functions
  • Errors and Debugging
  • Python Keywords
  • If-Else Statements
  • Storing Complex Data
  • Python Modules
  • Installing Python and Modules

Data Analysts Toolbox FAQs

Most data science positions expect you to have a post-advanced education in a quantitative field. Nonetheless, most data analysts I know come from totally irrelevant backgrounds and don't possess specialized degrees. Data scientific skills can easily be acquired by taking internet-based courses and doing training camps.

A data analyst uses several data analysis tools, such as Excel, SQL, and Tableau to assist them with their day-by-day data duties.

The skills required to turn into a data analyst (which will be clarified underneath), are easy to gain.  There is also an exceptional appeal for data analysts, and it is easy to make the transition into the field without going through years of rigorous studying.


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