Cloud-Based Data Warehouse System
For a US-based hospitality giant manage disparate data from 20+ sources
About
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.
Capability
Data Analytics
Industry
Travel & Hospitality
Country
US
Key Features
Rishabh Software built a Cloud Data Warehouse (DWH) Solution after merging & collaborating data from internal & third-party applications. Key features of the solution include:
Integrated consistent data
The data warehouse improves business intelligence by integrating & managing diverse, complex & large sets of data from disparate input data sources.
Scalable data reporting
Helps scale analytic needs, without retooling while storing, processing & analyzing massive volumes of data with a minimal total cost of ownership (TCO) footprint.
Intuitive dashboards
Easy access to reliable, high-quality data to different business units to assess.
Campaign support
Centralized data repository to create customer profiles to drive focused sales & marketing initiatives with the right insights.
Challenges
- Lack of central source to store & manage data, leading to data stored in silos & increasing data redundancy
- No visibility of the performance data for different business units
- No customization of BI reports for changing business needs
Solution
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;
Understanding data
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.
Operational Data Store (ODS) creation
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.
ETL
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.
Creation of DWH
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.
Technologies Used
Project Snapshots
50%
increase in workflow efficiency
40%
reduction in data quality issues
99%
accuracy of business understanding available on-the-go
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