We started by creating a roadmap to build a data warehouse solution. Our experienced data analytics team included – Business Analyst, Data Architect & Solution Architect. The first step was to plot detailed requirement mapping of elements.
Listed below are essentials for Data Warehouse (DWH) development;
Performed data source identification (source, formats, entities & fields of interest), understanding data model for connected applications (SQL Server, Oracle Database, Salesforce & PMS). It was across over 20 disparate applications like email, API, flat files, RDBMS, customer CRM, etc.
Created rules for data validity, data deduplication & data sanity across all levels. Implement data pipelines to access data from transactional resources. Our team integrated data from multiple & diverse apps & IT systems.
Creation of ETL routines, packages, and schedules with SQL Server Integration Services (SSIS) along with monitoring tools (ASP.NET Core Microservices) for end-to-end activities. It included identification of API integration (Salesforce and others) needs and developing an API layer.
Developed an analytical layer while finalizing the data movement schedule and creating data marts for data ingestion and processing. Included mapping of integration needs from third-party applications.
Utilized Microsoft SQL Server Analysis Services (SSAS), and Power BI to map the various KPIs including expense management, demand forecasting & customer satisfaction.
Deployed the DWH on MS Azure after conducting a comparative analysis for the client.
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