Total Revenue started trending down on Thursday, September 1, 2022, falling by 40.84% (10.16 million INR) in 273 days.

Total Revenue dropped from 34.75 million INR to 30.1 million INR during its steepest decline between Tuesday, June 1, 2021 and Wednesday, September 1, 2021.

Total Revenue experienced the longest period of decline (-10.16 million INR) between Thursday, September 1, 2022 and Thursday, June 1, 2023.

Profit Margin % started trending down on Thursday, December 1, 2022, falling by 26.23% (0.46%) in 182 days.

Profit Margin % dropped from 1.75% to 1.29% during its steepest decline between Thursday, December 1, 2022 and Thursday, June 1, 2023.

Profit Margin % experienced the longest period of decline (-0.46) between Thursday, December 1, 2022 and Thursday, June 1, 2023.

AtliQ Hardware is a company that supplies computer hardware and peripherals to many clients across India. AtliQ Hardware's head office is at situated in Delhi, India & they have many regional offices through out India.

The sales director is facing issues in terms of tracking the sales in this dynamically growing market & he is having issues with the growth of this business, as overall sales were declining. The company has a regional manager for North India, South, and Central India. Whenever he wants to get insights from any of these regions he would call these people & get some insights on the phone that this was the sales last quarter and we are growing by this much in the next quarter.

The problem is that all these things happen in verbal form & there is no proof with facts that how his business is affected. He wants to make data-driven decision to increase sales of his company.

He wants a simple data visualization tool that he can access daily. By using tools and technologies one can make data-driven decisions that help in increasing the sales of the company.

Ensuring data quality and integrity.

Verified all records in customer, date, markets, products, and transactions tables for completeness and accuracy.

Checked garbage values or outliers in the sales amount column of the transaction table and marked them.

Checked for blank or null values in any of the tables and marked them as missing.

Checked transactions that have a currency other than INR and converted them to INR using the exchange rate.

Performed data cleaning and transformation to prepare the data for analysis.

Removed all records with blank or null values in any of the columns.

Removed records with product codes greater than Prod279, as they are outliers or errors.

Standardized the sales amount column by adding another column with converted USD values to INR using the exchange rate.

Removed duplicate records based on the primary key or a combination of columns.

Performed analysis to extract insights from the transaction and date tables.

Joined the transaction and date tables using an inner join and applied filters by year, market, month, and currency to select the relevant data.

Calculated the total sales amount, number of transactions, and other metrics of interest using aggregation functions.

Performed data visualization using Power BI to create interactive and insightful reports and dashboards.

Created DAX measures to define custom calculations and metrics for the data.

Created various line, bar, and column charts to visualize the data and compare different categories and trends.

Create year and month slicers to filter the data and enable dynamic analysis.