About the Customer
Industry: Industry Specific
The USA based client, allied with product designing company providing exceptional services to its clients by blending technology and design. For more than 20 years they are at the forefront of bringing change in their client’s identity with design and delivering measurable value for their business.
The organization is providing the most consistent and reliable designing services and solutions to its customers across the USA, China, London, Europe, and many other countries.
As per the client’s business requirement, we need to build a centralized data storage for all SaaS-based & on-premise applications accessible over the internet.
- Bunch of on-premises applications built with some specific purpose, a few third-party systems like Dynamics GP for Finance & Data warehouse for reporting
- Most of the backend data reside in Microsoft SQL Server DBs & flow internally through real-time replications
Challenges with Existing Architecture
- Difficult to maintain different data servers & databases
- Needs to constantly monitor real-time replications & keep them running
- Reporting was quite difficult due to decentralized data storages
To fulfill the client’s business requirement and deal with the challenges there is a need to change the working model and folder structure of centralized data storage.
- Replace on-premise applications with SaaS-based applications to reduce development & maintenance overhead
- Migrate existing on-premise databases to the cloud (Microsoft Azure)
- Centralized data from all applications into Azure Data Lake Store
- Incremental load of data using Azure Data Factory
- Generalized formats for storing all systems data – storing data in text files as a comma-separated resulting best utilization of data storages and saving data spaces
- Implement raw level & folder level security using Azure Active Directory (following best security policy & standards)
Implemented BI Architecture
Explanation of Diagram Components
API: On-premises applications have been replaced with SaaS-based applications which provides data in JSON format through Web API calls. This raw data is further processed into meaning form for reporting & analytics purposes.
Azure Data Factory: An ETL tool mainly used for EXTRACT, TRANSFORM & LOAD purpose. We used Azure data factory to execute Web API code (using CustomActivity), copy data from on-premise SQL DBs to Azure Data Lake Store & schedule processing on defined intervals.
Gateway: Gateway or Data Management Gateway is an intermediate bridge between on-premises systems and Azure cloud. We configured this to migrate on-premise SQL data to Azure cloud.
Azure Data Lake Store: This is a centralized storage account to store all application data in a generalized format. All the data stored as comma-separated values for smooth retrieval of data.
Tools and Technologies
- Centralized data for reporting
- Use of latest technologies & upgraded software
- Higher performance
- Less maintenance overhead due to adoption of SaaS based applications
- Cost-effective solutions
- Easily accessible across the globe