Data – The “New” Enterprise Asset
Data and information are the life force of business today. Like other valuable assets, they must be acquired, organized, maintained, and managed for optimum business performance. Metaview360 has helped many companies like yours to develop and implement their data management strategies.
Data quality, clarity, and organization dictate the way that your business is able to communicate within your organization, as well as with suppliers, customers, partners, and regulatory agencies. In today’s world, information management is critical to the effective management of your business.
Metaview360 uses a proven architected approach to understand and document the state of your data at the enterprise, data warehouse, or project level. The data architecture is comprised of data principles, standards, models and inventory. Integrated within your overall information systems context, it becomes the basis for implementing your data strategy.
Three Pillars of Data Management
Data governance, metadata management, and a focus on continuous data quality improvement are key foundational elements of your enterprise data strategy. They represent the three points of stability for the data management discipline – like the three legs of a stool that allow it to stand and make it strong. They overlay the Data Architecture as follows:
An Architectural Approach to Managing Data and Information
Spurred by laws and competitive pressures, the top levels of businesses are stepping up to the requirement for this critical management function. Metaview360 mentors organizations while developing data policies and standards that address organizational accountability, data definition, security, availability, and retention. Experienced consultants guide management to define its data governance agenda and to construct the appropriate organizational roles, charter and procedures to launch a successful data governance initiative.
Metadata is the structured description of your data and information assets, from both the business and the technical perspectives. An effective meta-data management environment captures metadata from all points in your Data Warehouse development process, organizes it for analysis, and makes it available to all the processes and people that need it.
Specialized databases, metadata repositories, provide you with the services to support your effort. The metadata solution you select should allow you to collect, analyze, organize, and share metadata in your environment. Metaview360 has specialized expertise in metadata repository technology to help you to evaluate and select a solution to meet your needs.
Corporations are more likely than ever to recognize the costs associated with poor data quality. The business-to-business relationships between vendors and customers require timely, accurate information for product and payment to flow smoothly. Regulatory agencies have brought data quality to the “front page” by imposing fines and other legal charges against company officers for inaccurate corporate reporting.
Assessing, improving and monitoring Data Quality are no longer ad-hoc activities. Metaview360 uses structured, proven methods and quality analysis tools to guide an organization from initial evaluation through long-term management of data quality.
The Benefits of Using Logan Data with Metaview360
- A wide range of specialized data-related services
- A proven architected method for Data Governance, Metadata Management and Data Quality assessment
- Decades of experience implementing best practices for Fortune 1000 companies
- A network of consultants & partners delivering leading edge services from data experts
- A Training curriculum to sustain the Data Governance function in your company
Discovery phase for Data Governance Projects
Objectives of Discovery Phase
- Identify area of key business benefit or need
- Identify data areas of greatest capability and greatest areas for improvement
- Obtain quantitative data quality results from a key data structure
- Define some practical, actionable recommendations that could be undertaken in 90 days
Management report and presentation:
- Executive Summary
- Data Quality Findings
- Data Governance Findings
- Data Standards Findings
- 90-day Recommendations
- Longer Term Projection
Duration: 3-4 weeks
90 Day Consulting Engagement:
Objectives and Potential Deliverables:
- 1. Define Project Scope
- Business Area of Focus
- Required Resources (Personnel, Tools, Time…)
- Project plan
2. Socialize the Data Governance Concepts
- Business Interviews and Presentations
- Technical Interviews and Presentations
3. Identify Key Data Elements for Standardization (could be several KPIs)
- Building the Corporate Vocabulary Training (1 day course)
- Introduction to Data Modeling Training (1-2 day course)
4. Conduct Key Data Element Standards working sessions
- Initial Business Glossary
5. Provide Organizational Framework for Data Governance
- Job Descriptions
- Template for Mission, Charter and Goals for a Data Governance board or council
- Identify Data Owners, Stewards and Stakeholders for Key Data Elements
- Initial Processes for data definition, approval and conflict resolution
- Strategy for technical implementation of standard data definitions
- Conduct initial Data Governance Board meeting
6. Initiate data-related Tool assessments and recommendations
- Data Modeling
- Business Glossary
- Data Quality Assessment
- Metadata Repository