Data Lifecycle Management Archives - eGovernance

Understand the Stages of a Data Governance Lifecycle to Upgrade Business Data Value

eGovernance — Thu, 04 Jul 2024 21:07:32 +0000

When companies gain control of their data, they unlock a host of business benefits, from reducing risk to driving decision making. A robust data governance program involves a continuous process that evolves with the organization’s data landscape. Collaboration and clear communication throughout the stages of a data governance lifecycle will help ensure success.

Data governance truly involves a cyclical process, and organizations must revisit the stages periodically as data sources and business processes change. While various regulatory environments and business needs involve unique approaches, this post outlines the stages of a standard data governance lifecycle.

1. Define the Purpose and Goals

Any successful data governance program starts with an assessment of the current data and regulatory landscape. While technologies and trends support data governance, strategic planning should focus on identifying existing risks and business priorities.

For instance, for many organizations regulatory compliance needs provide the initial motivation for gaining control of data assets. Another key driver might include improving data quality to support AI initiatives or other innovations.

Whatever the motivation, an initial step will involve identifying risks and practices that present obstacles to attaining business goals. For example, insufficient data security will compromise regulatory compliance. And poor data quality will reduce the effectiveness of decision making and AI initiatives.

2. Build a Roadmap

With an understanding of the reasons and goals for data governance in the organization, it is time to put together a detailed plan. Begin by identifying the data elements throughout the organization. Look at the types of data collected, the data sources and data owners, and how the organization uses the data.

Next, assess the quality of the organization’s data. Several factors affect data quality. For example, outdated or redundant data will reduce the accuracy of data-driven decision making. Likewise, incomplete data will diminish the reliability of data analytics. And inconsistencies across systems and processes can lead to confusion and errors.

Once you have a detailed picture of the data landscape and the challenges involved, you can construct a data governance plan. This strategic plan will include identifying the steps needed to implement data governance, the key stakeholders, necessary resources, and priorities.

3. Design the Data Governance Strategy

Primary goals of the data governance framework involve establishing standards for data management. They also involve ensuring data security and empowering employees throughout the organization to find and use data effectively.

First, the data governance framework will include determining data governance roles and responsibilities. Properly managing data involves input from stakeholders throughout the organization. Some common roles include data governance sponsors and council, data owners, data custodians, data stewards, and data users.

Next, comprehensive policies and procedures around data access, usage, management, and security form the backbone of a data governance framework. For instance, regulations like PCI DSS and HIPAA impose strict rules around data retention. And numerous privacy laws necessitate security policies to protect sensitive data.

4. Implement the Data Governance Program

With policies and procedures outlined and strategies documented, the real work begins. Technology can play a crucial role in this process. For example, automation can significantly reduce the time involved in labeling and tracking sensitive data. Likewise, automating data retention and destruction policies improves accuracy and defensibility.

Technology solutions can both reduce risk and save time. These solutions will include proactive data security, data compliance monitoring, and comprehensive records management, along with eDiscovery solutions that provide essential visibility into unstructured data.

Additionally, the data governance program must address the human factor, building a culture of data governance from top to bottom. Thus, the program necessarily includes educating and training stakeholders about data governance policies and procedures and their role in maintaining data integrity.

5. Continuously Monitor

Data governance requires continuous monitoring to ensure enforcement of data governance policies and proactively identify risks. This includes both regular audits and automated data compliance monitoring.

6. Review and Adapt

The final stage involves evaluating the effectiveness of data governance initiatives and refining processes and policies accordingly. As new data sets and security risks emerge, and as processes within the organization change, the data governance framework will need to change, as well.

Conduct regular reviews with senior executives and key stakeholders. Track progress against key objectives, measure results, and make any needed adjustments.

Leverage Expert Resources Throughout the Stages of a Data Governance Lifecycle

Many organizations effectively utilize information governance solutions to streamline the data governance process. Working with organizations like eMazzanti Technologies and Messaging Architects provides access to both extensive expertise and cutting-edge technologies.

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The post Understand the Stages of a Data Governance Lifecycle to Upgrade Business Data Value appeared first on eGovernance.

Effective Information Governance Strategy Drives Data Value and Supports Business Goals

eGovernance — Thu, 07 Sep 2023 21:50:53 +0000

Information governance involves locating and managing information wherever it lives throughout the organization. This includes managing the data lifecycle, providing for data security, and maintaining regulatory compliance. An effective information governance strategy helps organizations achieve strategic goals while reducing risk.

However, implementing effective information governance requires careful planning and coordination. And it takes time. Organizations should start with a comprehensive data audit to inform next steps. Leveraging information governance consulting services will streamline the process.

Assess Your Current State and Future Data Goals

To begin with, the organization must learn what data it has and where it lives. An initial data audit will develop a picture of data across the enterprise. The audit includes components such as:

Data mapping – The organization must identify where data lives and how it is stored. This will include understanding information infrastructure elements such as document libraries. It will encompass all storage locations, whether on premises or in the cloud. And it will involve identifying sensitive data.
Determining data quality – Duplicates, outdated information, and data silos all affect the quality of data. Likewise, access issues affect the usefulness of data. If the right people cannot find and access the information they need quickly and securely, the data holds little value.
Assessing data processes and policies – Determine what information policies exist and whether they are enforced. These include policies for accessing and sharing data as well as policies for retaining and destroying information.
Evaluating information security – A cyber security assessment reviews the policies and security controls governing information storage, movement, and access. And it evaluates existing security measures against regulatory requirements, industry standards and business needs.

With an understanding of the current state of information, the organization can define its vision and goals for information governance, aligning those goals with business needs.

Locate and Classify Data

Data classification proves foundational to good information governance. Sensitive and important data may be hidden in documents, meeting minutes, emails, chats and more. Labeling sensitive data allows data stewards to track that data and apply essential protections such as encryption and sharing restrictions.

Manually locating and tagging data proves difficult if not impossible at scale. But AI-powered tools automate the process of finding and classifying data wherever it lives. Properly classified data simplifies regulatory compliance and eases the eDiscovery process.

Define and Implement Data Lifecycle Policies

Data classification plays a key role in enforcing data retention and destruction policies. Regulations such as PCI DSS and HIPAA include strict rules around the minimum amount of time to retain certain types of information. On the other hand, information retained too long can become a liability.

Automating retention policies according to data type gives the organization a defensible way to maintain regulatory compliance. Because regulations and business priorities evolve over time, data stewards should regularly review and update retention policies.

Ensure Compliance Management

To address mandates from a wide variety of regulations, an effective information governance strategy should include regular compliance monitoring. eGovernance monitoring tools deliver visibility into sensitive data from a single console. Content alerts and reports allow for proactive remediation. And monitoring provides proof of policy demanded by many regulations.

Build Comprehensive Data Security

Data security works hand in hand with compliance monitoring as an essential element of information governance. While regulatory compliance mandates reasonable security precautions, organizations must move beyond checkbox compliance to protect against data breaches.

A risk assessment will highlight vulnerabilities and provide a basis for security planning. Security strategies must include ensuring proper access management. Endpoint protection, encryption, data backups, and multifactor authentication prove critical, as well. And organizations must address supply chain security and provide regular security awareness training for all staff.

Adapt Information Governance Strategy to Business Needs

Company structure, business priorities and specific industry requirements all play a role in information governance. Consequently, the optimal strategy will look different from one company to another. In every organization, however, effective information governance requires engagement of stakeholders and users throughout the organization.

eGovernance delivers a cloud-based information governance solution. Our consultants will work with your organization to design and implement an information governance strategy customized to your specific business needs.