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Mega project

MNDA

Enterprise/Corporation
Company Type
Newport News, United States
Location
Project work
Engagement Model
6 - 10 people
Team Size
3 - 6 Months
Duration
$50K - $100K
Budget

About

This project focuses on the identification and analysis of mega projects by evaluating a large volume of associated invoices. The project's primary goal is to connect these mega projects to clients' invoices, offering insights into their overall performance and identifying potential opportunities for growth. To achieve these objectives, the project employs a comprehensive data analytics and machine learning approach.

Challenge, approach, and impact

Data Integration and Cross-Referencing

One of the major hurdles was integrating data from various third-party systems, including obtaining construction permits and location information. We needed to cross-reference this data with our internal records, which required careful validation to ensure accuracy.

Data Cleaning

The addresses in our databases were inconsistent and required significant cleaning. The process of standardizing and validating these addresses to accurately pinpoint coordinates was complex and time-consuming.

Geolocation Issues

Accurately converting cleaned addresses into geographic coordinates for proper cross-referencing was challenging, especially when dealing with incomplete or ambiguous location data.

Data Volume

The large volume of invoices and associated project data created processing challenges. Efficiently handling and analyzing such a vast dataset required advanced techniques and reliable infrastructure to ensure timely and accurate results.

Technology Integration

Using a combination of Azure, AWS, Python, SQL Server, and C# required ensuring smooth interoperability between these platforms, which added complexity to the project's technical execution.

How we built

Data Analytics and Visualization

Testimonials

Anonymous

Diligent Solutions DOO

Verified Testimonial

Working on this project has been a rewarding experience. By analyzing mega project invoices, we’ve gained valuable insights into performance and identified growth opportunities. Using technologies like Python, SQL Server, AWS, and Azure, we efficiently processed and analyzed large datasets, uncovering trends that drive key decisions. It’s been a great opportunity to work with cutting-edge tools and contribute to a project with a significant impact on future growth.

Team structure

Client team

Brandon L's avatar

Brandon L

Vice President - Enterprise Data

Project stakeholder

The client stakeholders were working closely with the team at Diligent Solutions

Agency team

1 x Project Manager's avatar

1 x Project Manager

Production

1 x Solution Architect's avatar

1 x Solution Architect

Production

3 x Data Scientist's avatar

3 x Data Scientist

Production

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