Data Governance in Oracle Fusion Dataset (Publication Date: 2024/02)

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Discover Insights, Make Informed Decisions, and Stay Ahead of the Curve:



  • Is your organization accessing the live case management system or receiving data extracts?
  • What motivates your organization to assess data and related infrastructure maturity?
  • What motivates your organization to establish a vision for data governance and management?


  • Key Features:


    • Comprehensive set of 1568 prioritized Data Governance requirements.
    • Extensive coverage of 119 Data Governance topic scopes.
    • In-depth analysis of 119 Data Governance step-by-step solutions, benefits, BHAGs.
    • Detailed examination of 119 Data Governance case studies and use cases.

    • Digital download upon purchase.
    • Enjoy lifetime document updates included with your purchase.
    • Benefit from a fully editable and customizable Excel format.
    • Trusted and utilized by over 10,000 organizations.

    • Covering: Business Processes, Data Cleansing, Installation Services, Service Oriented Architecture, Workforce Analytics, Tax Compliance, Growth and Innovation, Payroll Management, Project Billing, Social Collaboration, System Requirements, Supply Chain Management, Data Governance Framework, Financial Software, Performance Optimization, Key Success Factors, Marketing Strategies, Globalization Support, Employee Engagement, Operating Profit, Field Service Management, Project Templates, Compensation Plans, Data Analytics, Talent Management, Application Customization, Real Time Analytics, Goal Management, Time Off Policies, Configuration Settings, Data Archiving, Disaster Recovery, Knowledge Management, Procurement Process, Database Administration, Business Intelligence, Manager Self Service, User Adoption, Financial Management, Master Data Management, Service Contracts, Application Upgrades, Version Comparison, Business Process Modeling, Improved Financial, Rapid Implementation, Work Assignment, Invoice Approval, Future Applications, Compliance Standards, Project Scheduling, Data Fusion, Resource Management, Customer Service, Task Management, Reporting Capabilities, Order Management, Time And Labor Tracking, Expense Reports, Data Governance, Project Accounting, Audit Trails, Labor Costing, Career Development, Backup And Recovery, Mobile Access, Migration Tools, CRM Features, User Profiles, Expense Categories, Recruiting Process, Project Budgeting, Absence Management, Project Management, ERP Team Responsibilities, Database Performance, Cloud Solutions, ERP Workflow, Performance Evaluations, Benefits Administration, Oracle Fusion, Job Matching, Data Integration, Business Process Redesign, Implementation Options, Human Resources, Multi Language Capabilities, Customer Portals, Gene Fusion, Social Listening, Sales Management, Inventory Management, Country Specific Features, Data Security, Data Quality Management, Integration Tools, Data Privacy Regulations, Project Collaboration, Workflow Automation, Configurable Dashboards, Workforce Planning, Application Security, Employee Self Service, Collaboration Tools, High Availability, Automation Features, Security Policies, Release Updates, Succession Planning, Project Costing, Role Based Access, Lead Generation, Localization Tools, Data Migration, Data Replication, Learning Management, Data Warehousing, Database Tuning, Sprint Backlog




    Data Governance Assessment Dataset - Utilization, Solutions, Advantages, BHAG (Big Hairy Audacious Goal):


    Data Governance


    Data governance involves establishing processes and policies for managing, accessing and using data, including whether to use the live case management system or receive data extracts.

    1. Solutions:
    - Implementing a data governance framework for consistent and secure data management.
    - Utilizing data encryption to ensure sensitive information is protected.
    - Using access controls to restrict data access based on user roles and permissions.
    - Establishing data backup and recovery procedures to prevent data loss.
    - Conducting regular data audits to identify any gaps or inconsistencies in data management processes.

    2. Benefits:
    - Ensures data integrity, accuracy, and consistency across the organization.
    - Enhances data security and privacy, reducing the risk of data breaches.
    - Allows for better control and management of data access, reducing the risk of unauthorized use.
    - Provides a safety net in case of system failures or human error, ensuring data availability.
    - Helps identify and address any weaknesses or inefficiencies in data management processes.

    CONTROL QUESTION: Is the organization accessing the live case management system or receiving data extracts?


    Big Hairy Audacious Goal (BHAG) for 10 years from now:

    In 10 years, the organization will have fully implemented a comprehensive data governance strategy that seamlessly integrates the live case management system with data extraction and monitoring capabilities. This will enable real-time access to accurate and complete data, allowing for informed decision making and proactive identification of process improvements. With highly trained data governance professionals leading the way, the organization will have established a culture of data ownership and accountability, ensuring data is treated as a valuable asset throughout all levels of the organization. This will result in a data-driven approach to operations, leading to increased efficiency, improved customer satisfaction, and sustained growth for the organization.

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    Data Governance Case Study/Use Case example - How to use:



    Synopsis:
    Our client is a large public sector organization that provides case management services for various social and health programs to the community. They are responsible for managing sensitive data, including personal and medical information of clients. The organization had been facing challenges in effectively and securely accessing real-time data from their live case management system. This resulted in delays and inconsistencies in decision-making, leading to an increase in errors, complaints, and operational costs. To address these issues, they approached our consulting firm to implement a robust data governance framework that would allow them to access the live case management system efficiently and securely.

    Consulting Methodology:
    Our consulting methodology for this project was based on industry best practices and guidelines from established data governance frameworks such as DAMA-DMBOK (Data Management Body of Knowledge) and COBIT (Control Objectives for Information and Related Technology). This approach ensured that the solution was customized to meet the specific needs and challenges faced by our client.

    Deliverables:
    1. Data Governance Framework: We developed a comprehensive data governance framework that included policies, procedures, and guidelines for managing data access, security, quality, and privacy.
    2. Data Architecture: We designed a data architecture that allowed the organization to seamlessly integrate their live case management system with other applications and data sources.
    3. Data Governance Training: We conducted training sessions for the organization′s employees to raise awareness about the importance of data governance and their roles and responsibilities in maintaining it.
    4. Data Quality Assessment: We performed a thorough assessment of the organization′s data quality and provided recommendations for improving it.

    Implementation Challenges:
    The implementation of data governance posed several challenges, including resistance from employees who were used to accessing data without any restrictions, lack of understanding of the importance of data governance, and the complexity of integrating multiple systems. To overcome these challenges, we collaborated closely with the organization′s stakeholders, providing regular updates and training to ensure their buy-in and support.

    KPIs:
    1. Data Access Time: This KPI measured the amount of time taken to access real-time data from the live case management system. The goal was to reduce the access time by 50%.
    2. Data Quality: We measured the accuracy, completeness, consistency, and timeliness of data to ensure that it met the organization′s standards. The goal was to improve data quality by 80%.
    3. Cost Savings: We tracked the organization′s operational costs before and after the implementation of the data governance framework. The goal was to achieve at least 20% cost savings.
    4. Employee Training Participation: We measured the number of employees who participated in the data governance training sessions. The goal was to have a 100% participation rate.

    Management Considerations:
    1. Ongoing Monitoring and Maintenance: Data governance is an ongoing process, and it was essential for the organization to continue monitoring and maintaining the framework to ensure its effectiveness.
    2. Change Management: The implementation of data governance required a significant change in the organization′s culture and processes. Effective change management was critical to ensure successful adoption and long-term sustainability.
    3. Periodic Audits: Regular audits were necessary to ensure compliance with data governance policies and identify any gaps or inconsistencies. These audits would help the organization continuously improve its data governance practices.

    Conclusion:
    The implementation of a robust data governance framework enabled the organization to securely and efficiently access real-time data from their live case management system. This resulted in improved decision-making, decreased errors, and cost savings. The KPIs showed that the data governance framework was successful in meeting its intended objectives. Additionally, the organization was now better equipped to manage and protect sensitive client data, leading to increased trust and satisfaction from both clients and stakeholders.

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