Types Of Business Analytics

Table of Contents

Introduction –

In this competitive world, if you want to run a business at the top level, you need skilled people and the right technology. Business analytics is one of the technologies that helps you stay competitive in this competitive market.

So basically, business analytics is a new way for businesses to understand and improve how they do things. It helps them make smart choices about what to do next. By looking at data, businesses can find problems early and make better decisions.

Additionally, they can track sales, how customers act, and even how well their marketing works. This helps them save money and do better overall.

There are many companies that use business analytics technology, such as Amazon, Flipkart, Google, etc.

As per smallbiztrends statistics, even small businesses are getting in on it, with almost 70% spending over $10,000 a year on analytics. From these statistics, it’s clear that analytics are crucial for business success.

In this blog will explain the types of business analytics, how they work, and how they can help your business succeed.

If you are a fresher or working professional who wants to start a career in business analytics, look no further than Technogeeks. Technogeeks is the best place to start.

Before exploring different types of Business Analytics let’s first understand what business analytics is.

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What is Business Analytics?

Business analytics helps people make good business decisions by using the power of data to change things. It includes –

Gathering
Analyzing
Interpreting
Showing data in order to find patterns, trends, and connections

So basically, when companies follow this process, they can use data to make better choices, work smarter, and become even better at what they do. Business analytics helps them reach new heights of success that have never been seen before.

Also Read: Business Analyst Roadmap: Steps to become a successful Business Analyst

Types Of Business Analytics

There are many types of Business analytics such as –

Descriptive Analytics
Diagnostic Analytics
Predictive Analytics
Prescriptive Analytics
Text Analytics
Web Analytics

Let’s explain one by one with examples.

1. Descriptive Analytics

Descriptive Analytics is a type of business analytics, which helps to summarize historical data to understand what has happened in the past.

It mainly focuses on providing insights into the present and past by analyzing historical data. This helps businesses get a clear picture of where they stand right now and also find any trends that might be hiding in the data. So, in a way, it’s like having a conversation with your data to understand the past and present.

For Example – Let’s take an example of clothing retailers who want to understand how their sales have been performing over the past few months.

So firstly he/she collect data from their sale systems, which includes information such as –

Daily sales revenue
Number of items sold
Average transaction value
Customer demographics

Using descriptive analytics, the retailer can analyze this data to generate reports that summarize their sales performance. Also to understand these data easily they create charts and graphs to understand data visually.

For example, they might notice that people tend to buy more summer clothes in March-April month.

Tools used for Descriptive Analytics –

You may have a question in mind: what tools do you use in descriptive analytics?

There are many tools & techniques used in Descriptive Analytics such as –

Spreadsheets
Database Management Systems (DBMS)
BI tools such as Tableau, Power BI,etc.
Data Visualization tools such as matplotlib, seaborn,etc.

2. Diagnostic Analytics –

Diagnostic Analytics helps you understand why something happened by thoroughly examining your data for valuable insights.

So basically descriptive analytics is the first step in analyzing data for many companies. It’s a basic process that just tells you what already happened and what happened next. And The second step is diagnostic analytics which helps to find out why certain things happened.

For Example – Let’s take the same example of clothing retailers who faced sudden drop in sales for a particular product category (Cord-Set) over the past month. To understand why this happened, they come to diagnostic analytics.

First, they collect information about different factors that might affect sales, such as –

Marketing Campaigns
Competitor Activity
Seasonality
Product Availability

These are some factors that might affect the sales or may be another reason. After finding the reason from diagnostic analytics, the company can take specific actions to fix why sales dropped.

Tools used for Diagnostic Analytics –

BI (Business Intelligence) tools such as Tableau, Power BI, and QlikView
Statistical Analysis Software tool such as Python with libraries like Pandas and NumPy
Knowledge of programming languages such as Python.

Also Read: Scope of Business Analytics

3. Predictive Analytics

The meaning of “Predictive Analytics” is that “predictive” refers to making predictions. In Predictive Analytics, we analyze future predictions based on historical data and statistical algorithms.

In predictive analytics we use many advanced techniques such as machine learning algorithms, regression analysis, time series forecasting, and data mining.

By using these techniques, businesses can predict trends, predict demand, and make decisions as per audience demand to succeed.

For Example – Let’s take an example of clothing retailers who can use Predictive Analytics to analyze what clothes people are likely to buy during the summer.

Using their past sales data, they can predict which items are likely to sell well in the future. This helps them stock up on popular items and avoid overstocking items that don’t sell as quickly.

By making these predictions, they can better manage their inventory and increase their chances of selling more products.

Tools used for Predictive Analytics –

Knowledge of Programming languages such as Python with libraries such as scikit-learn and TensorFlow.
BI Tools such as Tableau, Power BI, and QlikView, etc.
Predictive analytics platforms solutions such as SAS Enterprise Miner, IBM Watson Studio, and Microsoft Azure Machine Learning

4. Prescriptive Analytics

Prescriptive Analytics is a type of business analytics that comes after descriptive, diagnostic and predictive analytics.

So basically Prescriptive Analytics gives practical suggestions based on data insights, using advanced methods like optimization algorithms and machine learning.

For Example – Let’s take an example of a clothing retailer who uses prescriptive analytics to optimize their pricing strategy.

With prescriptive analytics, the retailer can use data to figure out the best prices for their products.

So basically they will consider many factors such as –

How much people are willing to pay
The time of year
What competitors are charging

These factors help them set prices that make the most profit.

Tools Used in Prescriptive Analytics –

Optimization algorithms
Simulation techniques
Machine learning models
Decision trees
Linear programming techniques

Also Read: Business Analytics vs Data Analytics

5. Text Analytics

Text Analytics involves extracting insights from unstructured textual data such as –

Customer Reviews
Social Media Posts
Emails
Documents

So basically text analytics uses NLP (Natural Language Processing) technique & machine learning techniques to analyze and interpret text, help businesses to gain valuable insights from large volumes of textual data.

Tools used in Text Analytics –

NLP (Natural Language Processing) technique
Machine Learning Frameworks such as Scikit-learn, TensorFlow, and PyTorch
Data Storage and Querying Tools like databases – SQL, NoSQL

6. Web Analytics

Web analytics focuses on analyzing website and online user data to understand user behavior, optimize digital experiences, and drive website performance.

It involves tracking metrics such as –

Website traffic
User engagement
Conversion rates
Click-through rates

To analyze the effectiveness of online campaigns and strategies.

Conclusion

I hope you get a better understanding of “Types Of Business Analytics”.

There is huge demand for Business Analytics in today’s digital world.
It helps understand “what happened” in the past (descriptive analytics)
It figures out “why things happened” (diagnostic analytics)
It predicts “what might happen” in the future (predictive analytics)
It tells you “what to do next” based on predictions (prescriptive analytics)
Helps businesses know what steps to take for success.
It’s about using data to improve processes and reach goals.