Introduction

Assume you have a lot of data, scattered like puzzle pieces all over the place. It can be exhausting trying to make sense of it all. But business intelligence platforms make the process easier. They collect all of your data, clean it up, and help you uncover useful insights. It’s like having your own team of data specialists to assist you in making better business decisions.

The term’ Business Intelligence (BI) provides the user with data and tools to answer any decision-making important question of an organization; it can be related to running or part of a business.

• BI is used to determine whether a business is running as per plan.
• BI is used to identify which things are going wrong.
• BI is used to take and monitor corrective actions.
• BI is used to identify the current trends of their business.

STAGES OF BUSINESS INTELLIGENCE

1. Data collection

Identify and gather data from multiple sources either internal or external, such as spreadsheets, files, cloud storage platforms, and databases. This will help you develop a business objective and identify the data needed to achieve it.

2. Data preparation

Once gathered, the data must be prepared for analysis which refers to cleaning the data and ensuring there are no inconsistencies, duplicates, or errors. Unstructured data must be organized and transformed before analysis.

Now, let’s talk about how cleaning up your data can do wonders for your online clothing store. You have a large inventory with many products, but the data contains inconsistencies, duplicates, and inaccuracies. Before you can analyze the data and make sound decisions, you must first clean it up. This will ensure your inventory is accurate and your product suggestions are relevant.

3. Data storage

This stage of business intelligence entails storing all the data you’ve obtained. Typically, data is stored in a central location known as a data warehouse. Data encryption methods are used to safeguard the confidentiality and integrity of the stored information.

In an online clothing store, you’ll be handling customers’ personal information and payment data. During the data storage step, you can encrypt and securely save all the collected data in a centralized data warehouse.

4. Data analysis

The data that has been collected and stored must ultimately be processed and analyzed to reveal patterns, trends, and insights. To extract useful information from data, many analytical approaches and algorithms are used. 

By analyzing the sales data of your online clothing store, you’ll obtain insights into your customers’ preferences, popular products, and sales trends. From there, you will be able to refine your marketing techniques and improve the entire consumer experience.

5. Data visualization

After the data has been analyzed, it should be presented in the form of charts, graphs, dashboards, or other visual representations. It helps you to efficiently present the insights gained from the data to a broader audience, including decision-makers and stakeholders.

In order to present your online clothing store’s sales performance information, you’ll want to use BI software to diplay your sales and revenue data, product performance data, and more with aesthetically appealing charts, graphs, and dashboards.

6. Decision making

Collaboration is essential for insight-driven decision making. Decision-makers and stakeholders must work together to discuss and determine the best course of action for the business.

Using all the insights you have gained about your online clothing store, you can make decisions by collaborating with decision-makers and stakeholders to optimize your marketing campaigns.