Oil & Gas

At our company, we are constantly striving to find ways to reduce our energy consumption and production costs. In order to do this, we rely on data that provides us with an understanding of our current energy situation. This data helps us to identify areas where we can make improvements. One of the most important things we have learned from our data is that our energy consumption is seasonal. This means that we can make the most significant reductions by making changes during the times of year when energy consumption is highest. We have also learned that our energy consumption is highest during the daytime. This is due to the fact that our production process is more energy-intensive during the daytime. 

Project Title

Energy Consumption and production

Project Objective

Project Description

Client needs to see their oil consumption and production according to country/date filters. They have provided the data JSON format.

Our Solution

We have used Power BI to visualise the data. Perform several EDA and statistics analysis to get desired output from raw data.

Why Power BI ?

Power BI is a new cloud-based Business Intelligence service from Microsoft that builds on the company’s years of experience with relational databases such as Access, SQL Server, and others. It is a business intelligence platform that enables organisations to clean and completely transform raw data into meaningful data. It thoroughly analyses data and provides insightful results.

Tools used

Databases , Power BI

Language/techniques used

Python , DAX

What are the technical Challenges Faced during Project Execution

How the Technical Challenges were Solved

Business Impact

In this visualisation they can see their Total Debt and Total Billing in line graph to check the trend.

Client can now visualise the Total property and Total Billing amount. They have flexibility to filter out the dashboard according to Account Category. They can see Bad debt according to account category so that they will change their policy toward that particular sector.

In this visualisation they can see their Total Debt and Total Billing in line graph to check the trend.

Client can visualise these two KPIs to check total insights according to category. They can see Property value ,Total Debt and Bad Debt in same pivot table where values are distinguished by heatmap. 

Project website url

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