Sales insights data analysis project involves analyzing sales data to identify trends, patterns, and insights that can be used to improve sales performance and make data-driven business decisions. The goal of this project is to provide sales managers and executives with actionable insights that can be used to increase revenue, improve customer retention, and optimize sales processes.
The project typically involves the following steps:
Data Collection: Collecting data from various sources, such as sales databases, CRM systems, social media, and other customer engagement platforms.
Data Preparation: Cleaning and transforming the data to ensure it is accurate, complete, and ready for analysis.
Data Analysis: Analyzing the data using statistical methods, machine learning algorithms, and data visualization techniques to identify trends, patterns, and insights.
Insights Generation: Generating insights based on the analysis, such as identifying the most profitable products or services, determining the most effective sales channels, and identifying customer segments with the highest potential for growth.
Presentation: Presenting the insights to sales managers and executives in a way that is easy to understand and actionable, such as through reports, dashboards, or presentations.
sales insights data analysis project using power BI. This project will give you a feel of how data analysis projects are executed in big companies. This would be perfect for anyone Our case study is based on a computer hardware business which is facing challenges in dynamically changing market. Sales director decides to invest in data analysis project and he would like to build power BI dashboard that can give him real time sales insights.
Once sales directory of atliQ hardware has decided to invest in data analysis project he will do a meeting with IT director, data analytics team to come up with a plan. They will use AIMS grid to define purpose and success criteria of this project.
AIMS grid simple explanation: Once AIMS grid is defined, next step is data discovery. In this step, data analyst team approaches IT team within an organization who owns software system that keep track of sales records. These records are stored in mysql database. Power BI can be plugged to this database to pull necessary information required for data analysis. I also discuss ETL, OLTP, OLAP and data warehouse concepts. Many times we need separate data warehouse or OLAP system to run our data analytics queries but in our project we will directly use mysql database.
This database has all sales transactions, customers, products, and market information. We will analyse this database and then hook it up with power BI. In power BI we will perform ETL and data cleaning operations to make it ready so that we can build our dashboard.
we will plug mysql database with Power BI. In power BI we will do data cleaning and ETL (Extract, transform, load). This process is also known as data munging or data wrangling. We will do currency normalization, handle invalid values, etc.
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