What Makes Data Analytics Accessible:
Core Skills Are Tactile: Data cleaning, rudimentary statistics, and even the use of tools such as Excel, SQL, or Tableau are extremely tangible to learn, even for someone starting from scratch.
Tools Are Getting Easier: Tools like Power BI, Google Data Studio, and even Python libraries like Pandas make many things easier.
What Makes It Challenging:
Math & Stats: You don't have to be a mathematical genius, but a good understanding of statistics is crucial
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What is data analytics syllabus?
Data Analytics Syllabus
Module 1: Introduction to Data Analytics
What is data analytics?

Role of a data analyst
Types of analytics: Descriptive, Diagnostic, Predictive, Prescriptive
Data-driven decision making
Module 2: Data Collection & Data Sources
Types of data: Structured vs. unstructured
Data sources: Databases, APIs, web scraping, surveys
Data warehousing and data lakes
Introduction to ETL (Extract, Transform, Load) processes
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