Lowell Fryman, Customer Success Practice Principal at Collibra will discuss that without Data Governance principles and policies in place, members of the Data Governance team are left with no standards for how to define data, how to identify appropriate sources for reporting and compliance activities, and who is responsible for the associated technical and business processes.

Data Governance principles and policies establish the core objectives and basis for measuring compliance. Principles and policies identify the roles and responsibilities and are used for communications and education throughout the enterprise.

A key aspect of creating Data Governance principles is to make them short and sweet so everyone can remember! The principles establish the data culture, drive desired outcomes and form the Data Governance roadmap. Data Governance policies can then be developed for multiple principles and are used to measure Data Governance compliance. The policies outline the What, Why and Who level and support the operating procedures and standards. Implementing both Data Governance principles and policies into practice provides your team with the guidance and knowledge necessary to succeed.

Lowell Fryman, Customer Success Practice Principal at Collibra will discuss how Data Governance maturity models determine your data maturity level based upon an assessment. There are multiple maturity models and associated assessments on the market and have been standardized within the technology markets but businesses rarely sees the correlation between maturity levels and the impact for their own objectives – and on business results. This course will examine two Data Governance maturity models to help you classify areas to assess, determine criteria for evaluation.

Today we are joined by Chris Cooper, the Director of Healthcare at Collibra. He will discuss how Collibra engages with our Healthcare customers and some challenges they encounter as their Data Governance program advances.

Lowell Fryman, Customer Success Practice Principal at Collibra will discuss Data Quality. The challenge is that data quality is a complex issue. The sole objective of Data Governance is not to improve data quality, but rather to identify quality data. Evaluation includes front office and back office activities. It includes a strategy, policies, standards, operational life-cycle activities & resources, measurements & dashboards, thresholds for usage and technology support.

We need to address data quality from many angles and we begin with a data quality assessment. A Data Quality Assessment is a “point in time” profile and analysis of a specific set of data. It’s important to conduct an analysis and then make recommendations for data quality improvements. The Collibra Data Governance Center has a wide array of tools at your disposal to verify and define data quality. This effort will require various roles and responsibilities from Content Owners, IT Data Custodians, Data Consumers, Data Stewards and of course, the Data Governance team. All of these efforts combined will improve the data quality levels of your organization.

Lowell Fryman, Customer Success Practice Principal at Collibra will discuss the Top-Down and Bottom-Up processes. How do you know what data is necessary for regulatory reporting and how to ensure compliance? With the massive amount of data available to employees across an enterprise, how will they determine which is most valuable and critical for compliance activities?

Evaluating the data elements which are most important to the enterprise will allow for clarity and establish a scope. Analyzing the data used for reporting, the reporting currently being used, the computations and models being implemented and analysis of data lineage will establish the first step in identifying the most valuable critical data for the enterprise.

Applying a top-down process will aid in developing a business glossary, therefore creating critical business terms and define the terminology for the data. This process supports consistency and improved communications across the company.

Ram Naresh Pratti, Principal of the Center of Excellence at Collibra will discuss adoption and usage of the Business Glossary and how they are key to the success of a data governance program. By integrating the Business Glossary in the current workspace of your business users, you lower the barriers and ensure adoption. In this course you will explore the process for operationalizing a business glossary within your organization.

Ram Naresh Pratti, Principal of the Center of Excellence at Collibra will introduce you to the Business Glossary. Different terms mean different things depending on the context. For example: Is “Customer” the same for Finance as it is for Sales? Do the same rules apply? What are the policies? Which underlying business objectives are they representing? Who are the owners, stewards and stakeholders? A business glossary is a key component to tackle the questions above. The collaborative and iterative creation of such an inventory is a mandatory first task for the core data governance team. Once this process is up and running you have a solid foundation to move data governance forward. In this course you will gain the foundation by learning the principles of a business glossary and by exploring terms, definitions and relationships used in your organization.

Lowell Fryman, Customer Success Practice Principal at Collibra will provide an introduction to the principles and practices of Data Governance. This course will review the business relevance of data governance and how to establish the business value proposition, use cases and business cases. Our business leaders recognize the shifting focus to view 21st century business capabilities. Today’s data leaders leverage governance principles to support the massive reuse of quality, controlled and well understood data across the enterprise.

Data Governance leadership should focus on identifying specific business value statements that will drive the establishment and roadmap for the Data Governance program. Consider the desired outcomes, potential improvements, business value and financial returns. The major business value propositions are addressed in use cases from the perspectives of stakeholders and executives. Use Cases are short statements of the outcomes we desire to achieve. The business case should define objectives and associated financial considerations.