Basics of Data Analytics using Spreadsheet Notes
Subject Overview
The first course in the Data Science elective stream, introducing data analytics concepts (structured/
Subject at a glance
2
Units
10
Topics
2
Credits
2
Infographics
Unit-wise Syllabus
2 units — open any unit for detailed topic-wise notes, diagrams and important exam questions
- Understanding data and its types
- what data analytics is
- types
- importance and applications of data analytics
- Prescriptive
What should we do?
- Predictive
What is likely to happen?
- Diagnostic
Why did it happen?
- Descriptive
What happened?
Study guide
Data analytics is the process of examining data to find useful patterns and support decisions. You learn what data is and its types, what analytics is, its types (descriptive, diagnostic, predictive, prescriptive), its importance and where it is applied. Be able to give an example of each analytics type from a business you know.
- Data collection methods
- data sources and formats
- data cleaning and transformation
- handling missing data and outliers
- ethical considerations in data analytics
- industry-specific applications (finance, marketing, operations) with case studies
- 1Collect
From surveys, systems and the web
- 2Clean
Fix errors, duplicates and formats
- 3Handle gaps
Missing values and outliers
- 4Transform
Create usable columns
- 5Analyse ethically
Respect privacy and avoid bias
Study guide
Good analysis depends on good data. You study data collection methods, sources and formats, cleaning and transformation, handling missing data and outliers, the ethical side of analytics (privacy, consent, bias), and how finance, marketing and operations use analytics, through case studies. Remember that data cleaning often takes most of an analyst's time.
Why Basics of Data Analytics using Spreadsheet Matters
Data analytics is one of the fastest-growing career areas, and spreadsheets are the first tool almost every analyst uses. This paper builds the thinking and habits behind data work before you move to Python and machine learning.
How to Prepare for Basics of Data Analytics using Spreadsheet
- Collect a small real data set, such as your own expenses, and analyse it from start to finish.
- Learn to explain each analytics type with a business example.
- Note the ethical issues in every case study you read.
Basics of Data Analytics using Spreadsheet: Frequently Asked Questions
What are the types of data analytics?
Descriptive (what happened), diagnostic (why it happened), predictive (what may happen) and prescriptive (what to do about it).
Why is data cleaning important?
Errors, missing values and outliers lead to wrong conclusions, so cleaning is a necessary step before any analysis.