# Data Warehousing

*Game Studio Workflow:*

1. Studio Registration: Game studios register their games on the WPL platform, providing necessary game listing requirements along with game code and data log fields for player code matching.
2. Integration of SDK: Studios embed WPL SDK into their game applications to facilitate data logging and telemetry.
3. Performance Review: Studios review game performance through comprehensive reports, statistics, and analytics provided by the WPL platform.
4. Player Tracking: Utilizing player analytics, ranking systems, and behavior tracking, studios monitor player engagement and interactions within their games.
5. Reward Management: Studios manage player rewards and incentives based on performance and engagement metrics.

*Game App Logging Flow:*

1. Player Interaction: As players launch and engage with the game application, various events such as game start, pause, resume, abandonment, and completion are logged within the game event log.
2. Data Collection: Logged events are captured and transmitted to the WPL API for telemetry purposes, contributing to the WPL Telemetry Database.

*Log Parsing/Sanitizing:*

1. Data Parsing: Logged data undergoes parsing and sanitization processes, ensuring compatibility with registered game data parsers.
2. Authorization Check: Parsed data is evaluated to verify if it originates from registered games by associated studios. Authorized logs are processed further, integrating player details where applicable.
3. Error Handling: Logs that do not match authorized game criteria are redirected to the WPL Studio API for resolution, facilitating comprehensive reporting, statistics, and analytics.

*Player Workflow:*

1. Player Registration: Players register their played games on the WPL platform, associating game codes with their usernames for tracking purposes.
2. Performance Review: Players review game performance metrics provided by the WPL platform, aiding in informed decision-making and engagement strategies.
3. Reward Tracking: Players monitor their earned rewards and incentives, tracking progress and achievements within registered games.

*Data Lake (ML and AI Purposes):*

1. Data Sources: Various data sources, including databases, logs, and SaaS platforms, contribute to the WPL Data Lake.
2. Ingestion and Processing: Data undergoes ingestion processes, facilitating real-time analysis, machine learning, predictive analytics, and data discovery activities.

*Data Warehousing (BI Purposes):*

1. Standardization: Data is standardized in terms of structure to ensure compatibility and consistency.
2. ETL Processes: Extract, Load, Transform (ETL) processes facilitate the transfer of data to the WPL Data Warehouse for analysis, data mining, and reporting purposes, accessible through the WPL API.

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