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The Six Most Common Objectives of Enterprise Big Data Analytics

If you intend to develop analytical work for a company but don’t know the ultimate goal to be achieved with analytics, here are six common objectives for companies to pursue.

The Six Most Common Objectives of Enterprise Big Data Analytics


A descriptive objective aims to summarize a characteristic of a data set. For example:

  1. What are the characteristics of our customers?
  2. The demography of our website visitor; how many visitors and where do they from?
  3. How many shipments of our products get returned every day?


Exploratory objective aims to find patterns like trends or relationships among variables. For example:

  1. Patterns of products selling: Which products have increased sales in the last five years? Which products are likely sold together?
  2. Relationship between marketing campaign & products sales: Which marketing campaigns are most effective?
  3. Trends: Does our social media indicate missing popular topics?


Inferential objective aims to find generalizations about a population by examining a subset sample of the population. For example:

  1. What type of marketing campaign should we launch?
  2. Which product should we launch in a new region at the first?


Predictive objective aims to predict future outcome. For example:

  1. How many products will we sell next period?
  2. Will the prices go up? Or down?
  3. Should we procure more raw materials?


Causal objective aims to understand why a certain phenomenon happened. For example:

  1. As the sales increase; because of our marketing campaign better and more effective?
  2. As the customer satisfaction survey results are higher in Area X, because of our team delivered the products on time?


Mechanistic business objectives provide answers to business in questions which explain phenomena in purely physical or deterministic terms. For example:

  1. Why did we sell more last quarter compared to the previous one?
  2. Why is this product our most successful product?


Given the infinite amount of data that is available and the thousands of potential algorithms that can potentially solve a problem, it is vital to scope a business problem right from the start. A well-defined scope will help to set expectations towards business stakeholders and executives and will guide in the selection of the appropriate analysis techniques and algorithms.


Hendrix Yapputro M.Sc., Certified IT Architect – General Manager PT Equine Global


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