Cloud data engineering for business intelligence

A business intelligence environment required reliable data to be prepared and made available for Power BI reporting and analysis. The underlying data environment involved multiple cloud services and data-processing activities that needed to work together effectively to support the reporting layer.

The engagement required capability across both cloud infrastructure and data engineering. The objective was to configure the relevant cloud environment and prepare data so that it could flow effectively into downstream reporting and analytics.

Priscient Ideas provided data engineering and cloud architecture expertise, supporting the configuration of cloud services and preparation of data for Power BI reporting.

1. 01

   Analysed reporting and data requirements.

2. 02

   Reviewed the underlying data flow.

3. 03

   Configured relevant cloud services.

4. 04

   Supported data ingestion and processing.

5. 05

   Prepared and structured data for reporting.

6. 06

   Worked across the data and reporting layers.

7. 07

   Considered scalability, reliability and usability of the data pipeline.

8. 08

   Supported the connection between cloud-based data services and business intelligence.

• Technical work across the cloud data environment, configuring services and preparing data for consumption through Power BI.
• A connection between the underlying data-engineering layer and the business intelligence environment.

The engagement provided the technical data foundation required to support reliable Power BI reporting and analysis. It demonstrated an ability to operate across the data lifecycle, from cloud infrastructure and data engineering through to business intelligence.

• Amazon Web Services
• Cloud architecture
• Data engineering
• Data transformation
• Power BI
• Business intelligence
• Python
• Terraform