Modernizing Legacy Reports

About the Client

The client is a recognized and trusted consultancy group focused on driving safety and sustainability in the oceanic and energy sectors. They offer a substantial range of end-to-end consultancy services and support the development of renewable technologies and resources globally.

  • Industry:Renewables, Maritime, Oil & Gas
  • Team Size:4 (BA/Project Manager, Data Engineer, AI Engineer, Power BI Developer)
  • Project Tenure:April 2025

Key Deliverables

  • Collecting legacy maritime reports from different surveyors, formats, and file types.
  • Identifying report types based on unique identifiers for organization/processing.
  • Collecting and structuring unstructured written data from legacy reports.
  • Addressing duplicate data issues for accurate and consistent reporting.
  • Presenting the data in an organized, visually pleasing format with intuitive UX.

Prime Challenges

  • This project involves a massive amount of legacy data that needs to be modernized in both structure and presentation.
  • Data collection also involves finding ways to identify, organize, and process different file formats, types of data, data duplicates, and sources.
  • Creating a new application that can receive and present the data in a quick and reliable way.
  • Creating functionalities that can organize the reports based on specific KPIs requested by the client.

Proposed Solution

  • Divide the entire process into three parts: AI processing, DE (Data Engineering) processing, and presentation layer.
  • Prepare a data flow using Logic Apps and Azure Functions (using Python/Pyspark as programming language/API) to identify, filter, and send documents to be processed with the appropriate prompts.
  • Azure Data engineering solutions are designed to clean, transform and store data in delta tables by implementing Medallion Architecture using Azure Synapse Analytics and Azure Storage Accounts.
  • Use Azure Data Lake Storage (ADLS) to manage unstructured data.
  • Implement Delta Lake to store and manage data effectively.
  • Remove duplicate records with defined filtration techniques, presenting only unique records at the Power BI layer.
  • Present different Power BI reports for internal and external users, highlighting key KPIs.

Tech Stack:

  • Open AI
    Open AI
  • Logic App
    Logic App
  • Azure Function
    Azure Function
  • Python
    Python
  • Azure Cloud resources
    Azure Cloud resources
  • Azure Synapse
    Azure Synapse
  • Azure Storage Account (ADLS Gen2, Delta Lake)
    Azure Storage Account (ADLS Gen2, Delta Lake)
  • Power BI Reporting
    Power BI Reporting
  • Microsoft Visual Studio Code
    Microsoft Visual Studio Code
  • Storage Explorer
    Storage Explorer
  • Microsoft Power BI Desktop
    Microsoft Power BI Desktop
  • Azure Virtual Desktop (AVD)
    Azure Virtual Desktop (AVD)

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