Faster, Cheaper, Better Solution with Triniti Business Intelligence Service for Oracle ERP Cloud

 

In a data-driven world, businesses are facing information overload. Those who are interested in working smarter are investing in ways to control and understand this information. Although adopting new technology to understand the available information may seem like a daunting task, implementing BI right has a good payoff.
 

BI Analytics Should:

  • Provide insights on data related to business functions having an impact on the operational and financial performance of the enterprise

  • ​Generate information they may not have, and advise on possible action plans to take

  • Monitor key performance indicators (KPIs)

  • Turn analyst's insights into action when they use these tools to communicate their findings to stakeholders

  • Provide fast and accurate reporting

  • Identify meaningful data trends

  • Increase operational efficiency

  • ​Help make data-driven decisions


Limitations of Out-of-the-box OTBI (Oracle Transactional Business Intelligence) Reporting in Oracle ERP Cloud​

  • Difficult to measure the KPIs when data lives in multiple applications and sources

  • Suitable for operational reporting only

  • Absence of advanced analytics for performance measurement

  • Lacks powerful visualizations provided by tools such as Oracle Analytics Cloud, Power BI, Qlik, and Tableau


​Connecting BI Analytics with Oracle ERP Cloud: The Triniti Solution

  • Automated data extraction from Oracle Cloud using web services

  • Integration using data pipeline for workflow execution, data processing, and scheduling (daily, weekly, monthly along with the capability for ad-hoc refresh)

  • Alerts and reports for data movement from source to destination

  • Data lakes/RDBMS for storing Metadata / raw data

  • Connecting BI tool with multiple end-points that overcome the limitations of the out-of-the-box solution

  • Triniti fully manages the data movement, orchestration, and monitoring service

  • Flexible choices for different components as illustrated below.



Data Lakes

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