IT Governance and Data Cleansing in Oracle Fusion Freelance Ready Assessment (Publication Date: 2024/03)


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

  • Should it or business drive the data governance program?
  • Key Features:

    • Comprehensive set of 1530 prioritized IT Governance requirements.
    • Extensive coverage of 111 IT Governance topic scopes.
    • In-depth analysis of 111 IT Governance step-by-step solutions, benefits, BHAGs.
    • Detailed examination of 111 IT 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: Governance Structure, Data Integrations, Contingency Plans, Automated Cleansing, Data Cleansing Data Quality Monitoring, Data Cleansing Data Profiling, Data Risk, Data Governance Framework, Predictive Modeling, Reflective Practice, Visual Analytics, Access Management Policy, Management Buy-in, Performance Analytics, Data Matching, Data Governance, Price Plans, Data Cleansing Benefits, Data Quality Cleansing, Retirement Savings, Data Quality, Data Integration, ISO 22361, Promotional Offers, Data Cleansing Training, Approval Routing, Data Unification, Data Cleansing, Data Cleansing Metrics, Change Capabilities, Active Participation, Data Profiling, Data Duplicates, , ERP Data Conversion, Personality Evaluation, Metadata Values, Data Accuracy, Data Deletion, Clean Tech, IT Governance, Data Normalization, Multi Factor Authentication, Clean Energy, Data Cleansing Tools, Data Standardization, Data Consolidation, Risk Governance, Master Data Management, Clean Lists, Duplicate Detection, Health Goals Setting, Data Cleansing Software, Business Transformation Digital Transformation, Staff Engagement, Data Cleansing Strategies, Data Migration, Middleware Solutions, Systems Review, Real Time Security Monitoring, Funding Resources, Data Mining, Data manipulation, Data Validation, Data Extraction Data Validation, Conversion Rules, Issue Resolution, Spend Analysis, Service Standards, Needs And Wants, Leave of Absence, Data Cleansing Automation, Location Data Usage, Data Cleansing Challenges, Data Accuracy Integrity, Data Cleansing Data Verification, Lead Intelligence, Data Scrubbing, Error Correction, Source To Image, Data Enrichment, Data Privacy Laws, Data Verification, Data Manipulation Data Cleansing, Design Verification, Data Cleansing Audits, Application Development, Data Cleansing Data Quality Standards, Data Cleansing Techniques, Data Retention, Privacy Policy, Search Capabilities, Decision Making Speed, IT Rationalization, Clean Water, Data Centralization, Data Cleansing Data Quality Measurement, Metadata Schema, Performance Test Data, Information Lifecycle Management, Data Cleansing Best Practices, Data Cleansing Processes, Information Technology, Data Cleansing Data Quality Management, Data Security, Agile Planning, Customer Data, Data Cleanse, Data Archiving, Decision Tree, Data Quality Assessment

    IT Governance Assessment Freelance Ready Assessment – Utilization, Solutions, Advantages, BHAG (Big Hairy Audacious Goal):

    IT Governance

    IT Governance is the process of setting policies and procedures for managing and using data. The program should be driven jointly by IT and business to ensure alignment with organizational goals and needs.

    1. IT and business collaboration promotes better understanding of data needs and priorities.
    2. Clearly defined roles and responsibilities improve efficiency and accountability.
    3. Documented policies and procedures ensure consistency and compliance.
    4. Automated data validation checks reduce manual errors.
    5. Data stewardship program assigns ownership and accountability for data quality.
    6. Data cleansing tools identify and correct inconsistencies and anomalies.
    7. Regular data audits ensure ongoing data quality and accuracy.
    8. Data governance steering committee ensures alignment with organizational goals.
    9. User training programs promote adoption and proper use of data standards.
    10. Data quality metrics and reporting drive continuous improvement efforts.

    CONTROL QUESTION: Should it or business drive the data governance program?

    Big Hairy Audacious Goal (BHAG) for 10 years from now:
    By 2030, the IT Governance team will have successfully implemented a data governance program that is driven by both IT and business departments in a collaborative and strategic manner. This program will be seen as a model for other organizations, setting the standard for data governance practices.

    Some key achievements that this BHAG aims to achieve in 10 years include:

    1. A robust data governance framework: The IT Governance team will have developed a comprehensive framework for data governance, outlining roles, responsibilities, processes, and policies. This framework will be regularly updated to adapt to evolving technologies and data needs.

    2. Inclusive data governance steering committee: A cross-functional steering committee with members from both IT and business departments will be established to oversee the data governance program. This committee will have regular meetings to review progress, make strategic decisions, and resolve any conflicts.

    3. Clear data ownership and accountability: Through collaboration with business departments, the IT Governance team will have clearly defined data ownership and accountability for different data sets. This will ensure that data is accurate, consistent, and reliable across the organization.

    4. Data privacy and security compliance: The data governance program will prioritize compliance with data privacy and security regulations, such as GDPR and CCPA. Regular audits will be conducted to ensure that data assets are protected and accessed only by authorized users.

    5. Enhanced data quality and integrity: With both IT and business departments working together, the data governance program will have significantly improved data quality and integrity. This will lead to better decision-making, increased efficiency, and reduced costs.

    6. Empowered data governance champions: The IT Governance team will have identified and trained data governance champions within each department, who will act as ambassadors for the program and ensure its successful implementation and adoption.

    7. Data-driven culture: By 2030, the organization will have transformed into a data-driven culture, where decisions are informed by data and not just gut instinct. This will foster innovation, improve customer experience, and increase competitiveness.

    The success of this BHAG will not only benefit the organization but also the larger community as it will have a positive impact on data governance practices across industries. With IT and business departments working together, data will be seen as a valuable asset and managed in a strategic and mindful way, ultimately driving the organization towards success.

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    IT Governance Case Study/Use Case example – How to use:


    ABC Corporation is a leading global technology services company, providing IT and business solutions to clients in various industries. With the increasing importance of data in driving business decisions, the company recognized the need to establish a data governance program that would help them effectively manage and utilize their data assets. However, there were conflicting opinions within the organization regarding who should drive the data governance program – IT or business. This case study aims to evaluate the benefits and drawbacks of each approach and provide recommendations for ABC Corporation on whether IT or business should drive their data governance program.

    Consulting Methodology:

    To address the client′s situation, a consulting team was engaged to assess the current state of data governance in the organization and identify the best approach for driving the data governance program. The team consisted of experts in data governance, IT management, and business process optimization. The consulting methodology followed a three-step approach:

    1. Assessment: The first step involved conducting a thorough assessment of the organization′s current data governance practices. This included a review of existing policies, processes, and roles related to data governance, as well as interviews with key stakeholders from both IT and business functions.

    2. Gap Analysis: Based on the assessment, a gap analysis was performed to identify the strengths and weaknesses of the current data governance program. This helped in understanding the areas where improvement was required and provided insights into the challenges that needed to be addressed.

    3. Recommendations: The final step involved presenting the findings and recommendations to the senior leadership team. The recommendations included a roadmap for implementing the preferred approach, along with key deliverables and KPIs for measuring the success of the data governance program.


    The following deliverables were provided to ABC Corporation as part of the consulting engagement:

    1. Current State Assessment Report: This report provided an overview of the current data governance practices in the organization, including a detailed analysis of the policies, processes, and roles related to data governance.

    2. Gap Analysis Report: The gap analysis report highlighted the gaps and weaknesses in the current data governance program and provided recommendations for improvement.

    3. Roadmap for Implementation: Based on the assessment and gap analysis, a roadmap was developed for implementing the preferred approach – whether IT or business-driven data governance.

    4. Key Performance Indicators (KPIs): A list of KPIs was identified to measure the success of the data governance program, including the number of data quality issues, compliance with regulatory requirements, and cost savings achieved.

    Implementation Challenges:

    The consulting team encountered several challenges during the implementation of the data governance program, including:

    1. Resistance to Change: As with any organizational change, there was resistance from some stakeholders who were used to the current data governance practices. The consulting team had to address this by highlighting the benefits of the new approach and involving key stakeholders in the decision-making process.

    2. Lack of Awareness: Many employees were not fully aware of the importance of data governance and its impact on business outcomes. The team had to conduct awareness sessions to educate employees about the benefits of data governance and their role in its success.

    3. Resource Constraints: Implementing a robust data governance program requires adequate resources, including budget, skilled personnel, and technology. The organization had to allocate resources to support the implementation, which posed a challenge.

    KPIs and Management Considerations:

    To measure the success of the data governance program, ABC Corporation adopted the following KPIs:

    1. Number of Data Quality Issues: This KPI measured the total number of data quality issues identified and resolved, indicating the effectiveness of the data governance program in maintaining data accuracy and consistency.

    2. Regulatory Compliance: Compliance with regulatory requirements was a critical factor for the organization, and this KPI helped in monitoring the level of compliance achieved through data governance.

    3. Cost Savings: The data governance program aimed to reduce operational costs by improving data management processes and reducing errors. This KPI measured the cost savings achieved through the implementation of the program.

    In terms of management considerations, ABC Corporation needed to make a strategic decision on who would drive the data governance program. The following factors were taken into consideration:

    1. Organizational Culture: The culture of an organization plays a significant role in determining who should drive the data governance program. In a hierarchal organization with strict control, it may be more feasible for IT to lead the program. On the other hand, in a collaborative and agile culture, business leaders are better positioned to drive the program.

    2. Business Goals: The ultimate goal of data governance is to enable better decision making and support business objectives. Therefore, it is vital to align the data governance program′s objectives with the organization′s overall business goals.

    3. Expertise and Resources: Both IT and business have distinct skills and expertise related to data governance. As such, the organization needs to assess its internal capabilities and resources before deciding who will lead the program.


    Based on the assessment of the client′s situation and the consulting team′s recommendations, it was determined that a hybrid approach would be the best fit for ABC Corporation. This approach involved collaboration between IT and business in driving the data governance program. IT would be responsible for developing and maintaining the technical infrastructure, while business would define the business rules and processes for managing and utilizing data. This approach allowed for leveraging the strengths of both IT and business functions, leading to effective data management and decision making within the organization.

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