Do you design or manage products?
Reading a recent Washington post that customer centric brands are thriving in the present market. That means the products offered by these brands are tailored to Consumer tastes. But what if the products are based on incomplete or incorrect information? This is where Data Governance plays a critical role to ensure data integrity. Data Governance is no more a nice to have.

What is Data Governance?

Data governance is a business function that is intended to ensure that enterprise data is managed as effectively as any other valuable asset of the organization.

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Data Governance is an ongoing implementation of

• Data principles and policies,
• Organizational structures,
• Processes, and
• Roles and responsibilities
• That together ensure an effective management of enterprise data assets critical to the operation of the enterprise and its relationships with clients, partners, regulators and investors.

Key Terms in Data Governance?

1. 1 Data Ownership:

Responsibility of a business executive for a collection of enterprise data assets, typically within a particular subject area, that defines a point of authority for that data in the enterprise.

1. 2 Data Stewardship:

A data governance process that monitors and improves an effective management and use of enterprise data assets in accordance with approved data policies and procedures

1. 3 Data Quality:

Characteristics of enterprise data asset that indicate its level of adherence to established business rules typically measured in different criteria (data quality dimensions) such as accuracy, validity, completeness, uniqueness, etc., Quality of data can be measured as a percentage of good data and compared to expected results.

1. 4 Metadata Management:

A data governance process of managing data that describes enterprise data assets, e.g. data element name, description, format, set of valid values, data owner, etc. There are different types of metadata, e.g. business metadata, technical metadata, quality metadata, etc.

1. 5 Data Architecture:

The overall structure of data and data related resources as an integral part of the enterprise architecture.

1. 6 Data Modeling and Design

Analysis, design, building, testing, and maintenance

1. 6 Data Security

Ensuring privacy, confidentiality, and appropriate access

Four Pillars of Data Governance?

• Successful Data Governance is based on evenly matched four pillars:
• Each of the four pillars supports a consistent and balanced view of strategic data management.
• The role of data governance is to establish and oversee the data governance function, so that enterprise data is managed according to the approved principles, policies and controls.

The Sherpa Advantage

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