The North American client is a pioneer in F&B, Resort management & Rental Home segments. They were using a wide array of applications (PMS, POS, analytics, inventory and more) to manage business data because of multiple business acquisitions. They wanted to create a data warehouse as the single version of the truth to enable stakeholders to derive valuable insights as per their needs.
Rishabh Software built a Cloud Data Warehouse (DWH) Solution after merging & collaborating data from internal & third-party applications. Key features of the solution include:
The data warehouse improves business intelligence by integrating & managing diverse, complex & large sets of data from disparate input data sources.
Helps scale analytic needs, without retooling while storing, processing & analyzing massive volumes of data with a minimal total cost of ownership (TCO) footprint.
Easy access to reliable, high-quality data to different business units to assess.
Centralized data repository to create customer profiles to drive focused sales & marketing initiatives with the right insights.
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.