Data Governance has been a challenge for many organizations; with the digital age comes the complexity of consolidating multiple data structures and formats, and lining them with the business perspective. With the speed in which the data has been growing, we are noticing that data governance is quickly becoming a mandate for every organization, small or large, across all industries.
Data Governance is the overall management of the availability, usability, integrity and security of the data available in an organization. Data Governance also covers the governing body (often called council), a defined set of standards and policies, and a plan to execute those standards and policies. Companies use data governance process to ensure regulatory standards are met, in effect improving data security. It also increases the companies efficiencies by incorporating data quality measures surrounding the data.
A data governance program incorporates the process across the organization to provide standards such as consistent and sustainable definitions of business terms across data systems or applications. It enables the appropriate people to be involved in defining information requirements and set data standards, definitions and usage of data. Data Governance is all about organization standardization and policies.
According to the Association for Information and Image Management (AIIM), the biggest drivers for Information Governance are compliance (61%) and preventing data losses (51%), followed by creating searchable knowledge (48%) and reducing storage requirements via defensible deletion (35%).
The 4 Key processes which every organization needs to incorporate in order for them to enable data governance are:
- Identify the governing body or the executive sponsors (like Data Governance Council), then engage with the Key Governance Stakeholders, including: people who own the data, stewards who work on the data, the architects, etc.
- Identify the data standards and policies related to their business and industry.
- Regulate the defined data standards and policies across the organization by enforcing them in all projects.
- Create dashboards which enables the organization to audit, monitor, control and measure the performance on data governance activities.
Two key components of data governance are a business glossary (or metadata) and data lineage. The business glossary is a way to tag data into business terms, whether it be by products the company sells, customers the company has or regulations the company must follow. It acts as a “dictionary” to avoid terminology debates, information inconsistency and confusion within the organization. Data lineage defines the data’s lifecycle: where it originates from, where it has moved over time, and what has happened to it over time. It gives visibility while greatly simplifying the ability to trace errors back to the root cause.
These components allow for increased confidence in decision making, enabling better planning and improving data security to name a few. Because all parties can understand what rules and policies need to be followed, collaboration also increases.
The AIIM survey also found that 45% of the respondents agree that the lack of information governance leaves their organization wide open to litigation and data protection risks. Many organizations agree with the respondents that information governance is very critical to their business, but they struggle with two things: having too much decentralized data and how to govern all that data end-to-end. In today’s world, enterprises should take a look at different types of online data they create and collect, including emails, tweets and other social media posts, and determine how these new types of records will be managed in an ever-increasing regulatory environment.
If you are interested in improving your company’s ability to track and predict changing patterns of your data, contact our experienced teams today. Apexon’s expert technical team can engage with you and navigate you through the waters of data governance.
