How data collection strategy design would involve which type of business analytics (Common types of business analytics)


  • Introduction
  • Types of Business analytics
  • Data Collection in Business Analytics, Helps Make Better Business Decisions
  • Key takeaways on Data Collection in Business Analytics
  • Takeaway



Data is vital for any business, but raw data doesn’t have any meaning.

Data plays an integral role in any company’s success because so much boils down to numbers without meaning if there isn’t knowledge behind them. Data needs structure and understanding before businesses could even begin using its insights properly to their benefit.

There are many types of analytics that businesses can use. Today, we will explore the common types of business analytics under which data collection is used to derive insights and benefit organisations.


Types of Business analytics

The first is descriptive analytics; the second focuses on forecasting and predictive modelling; the third type evaluates past performance to improve current decision making by identifying patterns in data that can be used for future analysis (examples include what products sold well after a new marketing campaign).

Then we have prescriptive analytics, which examines available information and helps determine how decisions should be made with regard to allocating limited resources efficiently or best aligning goals. 

Finally, it is adaptive where it provides guidance continuously based on emerging trends resulting from changing conditions in order to anticipate change before they happen. Hence, you stay ahead of your competition.

The importance each stage plays becomes clear when looking at them as an interrelated set rather than just individually.


Descriptive Analytics

  • Assess what happened?
  • Rooted in the past and is anchored by a set of rules


  • Techniques used:
  • Metrics report
  • Data mining and aggregation
  • Summary statistics


Diagnostic Analytics

  • Why did a certain event happen?
  • Rooted in the past and is based on probability


  • Techniques used:
  • Principal components analysis
  • Sensitivity analysis
  • Regression analysis


Predictive Analytics

  • What might happen if specific conditions occur?
  • Rooted on the future and is based on probability


  • Techniques used:
  • Quantitative analysis
  • Predictive modelling
  • Machine learning algorithms


Prescriptive Analytics

  • Which actions will be best based on desired results or outcomes
  • Rooted on the future and is anchored by a set of rules


  • Techniques used:
  • Simulation analysis
  • Recommendation engines
  • Artificial Intelligence
  • Neural networks


Cognitive Analytics

  • Analyse large data sets
  • Give structure to unstructured data
  • Rooted on predicting future outcomes
  • Techniques used
    • Semantics
    • Artificial Intelligence Algorithms
    • Machine Learning
    • Deep Learning


Data Collection in Business Analytics, Helps Make Better Business Decisions

Data is the new oil. We live in a data-driven world, and possessing hard evidence to persuade stakeholders can be an enormous advantage for any business, big or small. 

Both collecting data through interactions on social media platforms as well as gathering monthly reports are simple ways your company could make better decisions that will-

  • Use predictive analysis to forecast sales trends
  • Keep customers satisfied
  • Improve customer retention rates
  • Create more loyal clients by streamlining marketing and advertising efforts
  • Provide excellent service, which then leads to increased revenue opportunities


Solves Complex Problems

Data can help business owners find inefficiencies and problem areas that need to be improved. They take the data collected from each department and track how well they meet their goals and objectives using a specific key performance indicator or quantifiable measure.

Gain Comprehensive Performance Overview

Businesses can select specific key performance indicators or quantifiable measures for their company’s goals. A data collecting tool then takes collected data and sifts through it all to show which departments need improvement on meeting those KPIs.

Management can make informed decisions to adjust processes, manage spends, or employ new marketing techniques to improve each department’s performance further.

Helps Improve Business Processes

Data collection/gathering offers a better understanding of business processes and how they should operate across various departments or business locations.

Helps Understand Customer Behaviour

Businesses can use qualitative and quantitative data collection to gain insights into their customers and if they would want to purchase the product or service offered by the company.


Key takeaways on Data Collection in Business Analytics

  • Data collection is a complex process involving the utilisation of various business analytics tools to collect data from different sources.
  • It helps businesses learn about inefficiencies and improves processes to enable stakeholders to make better business decisions.
  • Collection and management of data enable businesses to solve complex problems, gain a comprehensive insight into business performance, improve workflow processes, and help understand the behaviour of customers.



In today’s world, organisations face an overload of data. They need to find a way to turn this unstructured information into something that can be used in the decision-making process. Business Analytics helps solve these problems by providing insight through various patterns and relationships within all of this raw data.

To succeed, they must take advantage of big data analytics tools which will help them sort through their massive amounts of available, which is often incomprehensible, so that they may use it as part of their daily operations. Irrespective of which profession you are in, you will be surrounded by and driven by data.

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