Overview
The client is a global professional services provider in the energy, chemicals, and resources sector with over 25,000 projects in 46 countries. They face the challenge of handling a large volume of data from various sources that come in different formats. The client has multiple projects for Finance, Project Management, and other departments, and their reporting is in Power BI. The client also fetches data from appropriate source systems and builds SQL data marts using SSIS in cases where data is not available in the Enterprise Data warehouse. To overcome these challenges, the client has engaged STL Digital for consulting services.
Business Challenge
The client’s Data Engineering pipelines, built on Azure Data Factory, Azure Synapse, and Azure Databricks, face difficulties in handling the diverse formats of data that they ingest from various sources. The client needs a solution that can help ingest, clean, transform, and suitably prepare the data to generate different reports for the business. Additionally, the client requires a high level of skilled professional expertise in Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, SSIS, DAX, and Power BI to address these challenges.
Solution
To solve these challenges, STL Digital co-created different dashboards with the stakeholders and collaborated with the Data Architects and Data Engineering team to ingest, clean, transform, and prepare the data suitably for generating reports for different departments. The team leveraged Azure Data Factory, Azure Synapse, and Azure Databricks for building Data Engineering pipelines, Azure Data Lake for storage, and SSIS for building SQL data marts. The team utilized DAX and Power BI for reporting purposes.
Results
STL Digital provided a high level of skilled professional expertise in Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, SSIS, DAX, and Power BI, delivering advantages to the client. The client leveraged the team’s expertise in developing Data Engineering pipelines, ingesting data from various sources, and building SQL data marts. Additionally, the team assisted in preparing suitable reports for different departments using Power BI. The result was efficient processing and transformation of data that led to better decision-making and increased productivity for the client.
