ONLINE GAMING CASE STUDY
To remain competitive, online gaming providers must have the ability to make swift business decisions.
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THE CLIENT

 

The customer is an online sports betting and gaming provider.

To remain competitive in the fast-paced online gambling industry, gaming providers must have the ability to make swift business decisions. Efficient data management systems that assure fast access to data are essential in supporting this.

The gaming provider’s data management solution did not meet its current needs or support future growth. To address this, the customer had identified a need for a solution that assured speed, accuracy and availability of management reporting. As a key requirement, the system needed to facilitate automatic data collection and aggregation in real-time or near-real-time.

BUSINESS NEED


The customer’s existing data management systems and processes were limited, and this was having a negative impact on its business:  

  • The gaming provider relied on Excel spreadsheets and manual processes to collect and manipulate data for management reporting dashboards. Along with being time-consuming, this approach offered limited scalability and was not sufficiently flexible for advanced BI and reporting. Furthermore, it did not allow for verification against source data, thus accuracy could not be ensured.
 
  • Reconciling siloed data from external gaming platforms was an ongoing challenge.
 
  • The customer’s existing data warehouse was not being utilised due to difficulty in accessing the data and uncertainty as to whether the data was trustworthy.

The customer's existing data management systems and processes were limited, and this was having a negative impact on its business.

THE SOLUTION


Intenda conducted a point solution with the following key objectives:

1.  Connect Fraxses with the defined data sources and ingest their data in as close to real-time as possible, through APIs.

2.  Create and curate Fraxses Data Objects that a) allowed for all Excel spreadsheet information to be made seamlessly available to BI tools and other data consumers; and b) incorporated player information from the Player Backoffice platform.

Insights, the Fraxses platform’s data visualisation module, was used to generate dashboards and other reports. For the purposes of the point solution, Fraxses federated to a staging database rather than running live queries against the source systems. The gaming provider’s existing data warehouse was not included in the implementation due to data quality concerns.

The customer required a solution that facilitated automatic data collection and aggregation in real-time or near-real-time.

BENEFITS

 

Fraxses resolved several longstanding pain points, providing a scalable solution that eliminated challenges in accessing data; assured the quality and reliability of data; automatically reconciled data from different systems; and allowed for accurate reports to be produced on demand. 

  • Streaming and real-time data was ingested from gaming platforms, with all historical data being stored in a staging database within Fraxses. Full auditability and lineage assured on all data.
 
  • Transaction dates were aligned across different gaming systems, thereby eliminating duplication, with data cleansing conducted based on defined rules.
 
  • The introduction of secure, centrally controlled access for all users eliminated opportunities for fraud.
 
  • Fraxses allowed for reports based on real-time data to be generated automatically, thus eradicating longstanding difficulties in creating accurate and timely reports.
 
  • Previously siloed data from disparate external platforms was successfully reconciled, based on rules with notifications.
 
  • Daily, monthly and weekly reports and dashboards were reproduced as required. Creating more charts and exporting data for presentations or storyboards is an easy process.
 
  • The Fraxses implementation delivered trusted data that required minimal interpretation, with lineage allowing for changes and calculations to be tracked. 

Fraxses eliminated challenges in accessing data, assured the quality and reliability of data, automatically reconciled data from different systems and allowed for accurate reports to be produced on demand.

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