Data Governance is the concept of information within an organization being secure, of high quality and integrity, readily available, and also includes the methods by which this information is managed. It is an information management concept applied to the complete lifecycle of data ensuring high usability and defining accountability for poor data.
History of Data Governance
With the rise of mainframes and enterprise servers in the early 1980s came the aggregation of varying datasets in centralized, secure tape formats.
Early Days of Database Administration
Data was safely kept on the corporate mainframe, and only those programmers who had the skills to navigate pre-relational databases could access it. They managed secure databases and would print out business data at their discretion to hand over to analysts.
The release of the desktop PC gave less IT savvy users greater access to business data in easier to digest formats. They could query daily performance data in relational databases from remote servers in offices across the state or even country using dial-up internet connections. However, this also introduced confusion with different departments having different data schemas and even widely different versions of the same datasets.
Evolution of The Data Warehouse
This is where the data warehouse became a tool with great utility. Large datasets could be stored in one location, thus reducing data silos with different versions of the same data set. However, the problem of disparate data schemas in the warehouse needed solving.
Master Data Management (MDM) became central to alleviating this issue by focusing on consistent uniformity. MDM is a set of processes and protocols that ensures uniformity of master data assets such as client, supplier, and vendor details. Data quality and integrity are managed by setting consistent identifiers and data elements throughout an organization by leveraging effective stewardship.
Goals Data Governance Programs
Bringing data warehouses, MDM protocols, and their oversight together constitutes data governance. A data governance program must be developed, monitored, and maintained within an organization to meet local and international standards for that business' industry.
The main goal of data governance programs is to break down data silos across an organization. This helps create data consistency and compatibility across departments leading to accurate business intelligence and analytics. For example, proper data governance ensures records like names are the same across sales, customer service, and logistics departments.
Data Governance Roles Within an Organization
Every organization decides how to structure its data governance team with respect to the other roles and job descriptions; however, these are the typical roles that can be integrated into its functional departments.
This is the group of people that will carry out executive-level decisions, and therefore it usually comprises C-level officers or company Vice Presidents. Members' responsibilities include setting the overall governance strategy with specific outcomes, championing the work of data stewards, and holding the governance organization accountable to timelines and outcomes.
This is a non-voting member of the steering committee responsible for data definitions and glossaries for other team members. This role ensures data accuracy and quality across functional departments. MDM protocols and applications are reviewed by the data owner and reported back to the steering committee. This includes choices on measures to satisfy regulatory compliance, such as internal policies and software implementations.
The data steward is the role responsible for day-to-day data management and MDM policy implementation. Directly reporting to the data owner, the data steward is the subject matter expert who works cross-functionally across the different business units to ensure the MDM is adequately understood and applied.
Benefits of Data Governance
There are many advantages to defining a cohesive data management strategy across the functional departments of a business. Data governance as a practice establishes systematic, formal control over company processes, allowing rapid response to changes in size and scale of the company.
Costs of storing, retrieving, and analyzing data from multiple departmental silos are significantly reduced as the company scales. For example, analyzing info on 1000 clients from 1 location is very different when doing the same thing for 1 million clients across 20 locations. An efficient data governance strategy will handle both scenarios similarly without having to deal with differences in record reporting and management.
Risks of data loss and lawsuits are reduced with a competent data governance procedure. Data stewards effect policies and procedures developed by the data owner and overseen by the steering committee. They take into account current and possible future use cases for their data and take necessary steps to secure it accordingly.
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