Identification of Pre-Packaged Business Solutions and Definition of Technical Architecture Scenarios

Objective

The main objective of this study:

• Identify Pre-Packaged Business Solutions: Search for solutions that offer pre-configured business functionalities, likely to accelerate project implementation.
• Define Technical Architecture Scenarios: Propose four technical architecture scenarios based on different integrated or Best Of Breed technical solutions.

Platform

The platform considered for this study is composed of the following technologies:

• Azure: Microsoft's cloud computing platform, offering a complete range of services for data processing and analysis.
• Databricks: A data analysis platform based on Apache Spark, providing a collaborative environment for the development and deployment of analysis workflows.
• Snowflake: A cloud-based data warehousing platform designed to provide high-performance management and analysis of large-scale data.
• Palantir: An analytics and artificial intelligence platform that enables organisations to visualise, analyse and make data-driven decisions efficiently.

Services

The main services considered in this study are as follows:

• Azure Synapse: An integrated data analysis service for extracting, transforming and loading large-scale data.
• Azure Analytic Services: A set of data analysis and visualisation services for creating interactive dashboards and customised reports.
• Azure Data Lake Storage: A scalable and secure data storage service designed to store large volumes of unstructured data.
• Power BI: A data visualisation tool for creating interactive reports and dynamic dashboards.

Conclusion

By comparing pre-packaged business solutions against four Best-of-Breed and integrated architecture scenarios built on Azure, Databricks, Snowflake and Palantir, this study gave the client a clear, technology-agnostic view of the trade-offs between speed of deployment and long-term flexibility.

The resulting scenarios provide a decision-ready foundation: each is scoped against the same set of core services — Synapse, Azure Analytic Services, Data Lake Storage and Power BI — so the client can select the architecture that best matches its budget, timeline and governance requirements before committing to full-scale implementation.