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Business Analytics

What is business analytics (BA)?

  • A continuous and iterative exploration of past business performance.
  • Gain insight on the past performance
  • Get understanding of things that happened, improved or declined.
  • Help make data driven decision making.
  • Find patterns and reasons, understand customer behaviour.
  • Help make adjustments to business activities and improve business outcomes.

Business analytics compared

  • Data Engineering
    • Integrate Data Sources
    • Build Data Pipelines
    • Process and Transform
    • Store Data
  • Business Analytics / Intelligence
    • Dashboards/Reports
    • Exploratory Analytics
    • Statistical Modelling
    • Machine Learning
    • Business Actions

In Data Science, you do everything above.

Stages of business analytics

Descriptive - What happened? Exploratory - What is going on? Explanatory - Why did it happen? Predictive - What will happen? Prescriptive - How do I take advantage? Experimental - How well will it work?

Business analytics process

  • You move data from OLTP to OLAP. Build a data warehouse and data marts as required, then on top of it Analysis is done.

Use Cases

Heart Decease

For an individual, it has measures like blood pressure, cholesterol, and sugar.

  • Data
    • Age
    • Age Group - in increment of 20
    • Weight
    • Weight Group - in increment of 50
    • Sex - Male or Female
    • Chest Pain Type - 1/2/3/4
    • Resting BP
    • Cholesterol
    • High Sugar - 0/1

Email Campaign

Email campaigns and conversions

  • Computer business sends emails to customers about products
  • Offer different discount rates from time to time
  • Email readers click to view products and buy them
  • One year of emails are used for analysis
  • Captures details of the offers, customer types, and others
  • For ease of use, size of data set is small
  • Data
    • Offer Date - Date email was sent
    • Offer Weekday - Day email was sent
    • Offer Month - Month email was sent
    • Product - Name of product
    • Price - Price of product
    • Discount Offered - Discount % offered
    • Customer ID - Unique customer ID
    • Gender - Male or Female
    • Age - Age range
    • Earning - Range in 1,000s
    • Convert - 1/0

Descriptive Analytics (DEA)

  • Summarizes data to understand how business performed in a given time period
  • Compares different segments of data
  • Compares different time periods for trends and performance
  • Predefined and pre-canned reports
  • Bundled into software products or applications
  • Custom built by IT organizations
  • Schedule, run, export, and distribute reports
  • All users get the same data

DEA tools and techniques

DEA use case

DEA best practices

Exploratory Analytics (EDA)

The goal of exploratory data analytics is to deep dive into the data to understand patterns and confirm hypotheses.

  • Get familiar with the data itself
  • Deep dive into the data
  • Typically ad hoc reporting
  • Needs based

EDA tools and techniques

EDA use case

EDA best practices

Explanatory Analytics (EPA)

The goal of explanatory data analytics is to identify reasons and root causes for business results.

  • Storytelling with data
  • Answer questions
  • Present to an audience
  • Done by analysts or managers
  • Prelude to next actions
  • Start with a fact or statistic
  • Break down to interesting segments or profiles
  • Focus on interesting insights
  • Narrow down to possible causes

EPA tools and techniques

EPA use case

EPA best practices

2025-01-12 Aug 2024