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.
Client is already having a system and facing challenges with its existing architecture.
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.
API: On-premises applications have been replaced with SaaS-based applications which provide 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 purposes. We used the Azure data factory to execute Web API code (using CustomActivity), copy data from on-premise SQL DBs to Azure Data Lake Store & schedule processing at defined intervals.
Gateway: Gateway or Data Management Gateway is an intermediate bridge between on-premises systems and the 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 is stored as comma-separated values for smooth retrieval of data.
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)
Our detailed and accurate research , analysis, and refinement leads to a comprehensive study that describes the requirements, functions, and roles in a transparent manner.
We have a team of creative design experts who are apt at producing sleek designs of the system components with modernized layouts.
Our programmers are well versed with latest programming languages, tools, and techniques to effectively interpret the analysis and design into code.
Quality is at the helm of our projects. We leave no stone unturned in ensuring superior excellence and assurance in all our solutions and services.
We have a well-defined, robust, and secure launch criteria that offers us a successful implementation clubbed with detailed testing, customer acceptance and satisfaction.
Centralized data for reporting
Use of latest technologies & upgraded software
Less maintenance overhead due to adoption of SaaS-based applications
Easily accessible across the globe