Client:
One of the largest amusement park operators in India with parks in Kochi, Bengaluru & Hyderabad, a resort in Bengaluru and plans to open its 4th amusement park in Chennai, expected to be operational soon.
Business Challenge
The Client sought Speridian’s help for recommendations on setting up a centralized analytics framework to track of their B2B and B2C customer transactions. The enterprise sources include ERP (Oracle EBS), Ticketing PoS (Oracle forms), Kapture CRM, online channels like org website, BookMyShow, Paytm, ClearTrip and PoS transactions from Park restaurants and apparel shops. Various departments like Accounts, Finance, Sales, and Marketing, etc. have their own SILO reporting which causes reconciliation challenges and requires manual efforts for corrective actions.
Solution
Speridian built a solution encompassing the following products taking into account the client’s preference for an open-source solution stack.
- Microsoft Power BI Cloud (for Data visualizations, predictive analytics, dashboards, and BI reporting)
- Talend Data Integration Studio Version 7.1 (Open source ETL)
- MariaDB AX ColumnStore 1.1.6 GA (Open source EDW)
Impact
Speridian’s Analytics solution provides:
- Centralized Analytics Reporting Framework with role-based access for decision-makers at different levels.
- Allows authorized users to create ad-hoc reports, analyze, discover insights to make fast & right decisions to increase footfall.
- Allows slicing and dicing KPIs including bookings, footfall, revenue, expenses, incentives, utilization and other KPIs by Parks, Geography, Time Period, Departments, Channels, Payment Modes, Price Category, and Cost Centers, etc.
- Finds hidden insights in Promotions management, Feedback portals, Spreadsheets used by Departments, Event correlations, Trends, and patterns, etc.
- Relieves IT personnel of manual report generation and data reconciliation issues which are time-consuming.
- Offers predictive and advanced analytics for metrics like estimated footfall for upcoming monsoon based on weather forecast / historical data.
