Data Governance & Management
Establish rules, regulations, and quality standardsto ensure success
As an organization takes the path of data quality management and data cleansing, it is important that the organization establishes a data governance framework that serves as the foundation of all data policies and data standards. It is critical for companies to establish the benchmark by which all data standards are to be supported and followed. Defining what data means to an organization helps develop the governance framework process and procedures.
There are advantages to having a successful data governance strategy. Centralized policies and systems will reduce most IT costs related to data compliance efforts. Data standards will allow for better decision-making and communication across different levels of the organization, as governance keeps data controlled and organized.
Keep data controlled & organized
Develop a data governance team
Establishing ownership of the organization’s data governance is necessary. There should be cross-organization accountability, and a committee comprised of individuals from all departments, including executives. Establishing rules and regulations, data quality standards, and transparency are key principles in developing a strategy that ensures the governance initiative succeeds.
Executing Data Policies
GoDgtl can assist the process of securing, learning, and establishing the main principles of data governance and data management for any organization.
Data Governance
A data governance framework creates a single set of rules and processes for collecting, storing, and using data. By doing so, the framework makes it easier to streamline and scale core governance processes. This enables companies to maintain compliance, democratize data, and support collaboration— no matter how rapidly their data volumes grow.
A governance framework should be designed to deliver value today and adapt as the governance requirements change. GoDgtl experts can help your company build a framework across hybrid, cloud, and multi-cloud environments, with the flexibility to handle extreme fluctuations in data and users.
Data Management
Data management is viewed more as an IT practice, whereas data governance is viewed as a business strategy. The goal is to organize, control, and make data more accessible and reliable. Established organizations will have their IT teams trained on the practices and theories, as well as processes and systems to manage and maintain data.
Data management has its own lifecycle, from initial creation of data to the retirement/archival of data. It includes principles of data stewardship and data architecture as well as rules of metadata and data security.
Articles
Let's Talk
Our GoDgtl team is ready to help you!
We appreciate your interest in GoDgtl. Please select which team of experts you wish to engage: