Client: India Based Client
Vertical: Hospitality
Client Overview
The Client has a chain of hotels at multiple locations. The client wanted to have location wise, user wise, category wise reports that can help them make decisions to increase business. Their data was stored in CSV format and wanted data visualization to figure out important parameters and critical factors of their business.
Problem Areas
- Huge amount of data and lot of manual process involved in verification, cleansing and formatting the raw data.
- Traditional approach for data processing. Scattered, redundant and inconsistent data.
Our Solution
- Application of Data cleansing and integration techniques.
- Integrated data sources provide access to massive amounts of real time and historic data for analysis.
- Successful implementation of High charts for data visualization.
- Ease of reporting through OLAP and advanced analytical tool for data forecasting.
Implementation Highlights
- Backend BI System: Used for collection, integration and consolidation of data from various sources.
- Intermediate BI Tools: Allows users to create forecasts and identify trends from the data.
- Frontend BI Tools: Provides interactive user interface to view details generated by the system.
Our Key Challenges
- Multiple data sources
- Data Forecasting & Data mining
- Integrated data warehouse implementation
- Legacy operational data environment
What did we achieve?
- Improved reporting performance & user experience.
- Rate optimization through data mining.
- Hotels were able to use their past data to make better, more efficient decisions for the future.
- It helped in understanding their guests’ expenditure in terms of how and where they spend their money and time.
Technology Stack
- Tableau
- Cube
- Talend ETL
- High Charts
- Hadoop