What are the best data governance policies and procedures for software development?

1 Data quality

Data quality is essential for software development, as it affects the performance, functionality, and usability of your applications. Poor data quality can lead to errors, bugs, inefficiencies, and customer dissatisfaction. To ensure data quality, you should define standards and metrics for your data sources, processes, and outputs. This can include accuracy, completeness, validity, timeliness, consistency, and uniqueness. It is also important to implement data quality checks and validations at every stage of your data pipeline. This can be done with tools such as SQL queries, data profiling, data cleansing, and data auditing. Additionally, you should monitor and report data quality issues and trends with dashboards, alerts, and logs. Finally, assign data owners, stewards, analysts, and managers to oversee and improve data quality.

2 Data security

Data security is essential for software development since it helps to maintain the confidentiality, integrity, and availability of data. A data breach can have serious repercussions, including legal, financial, and reputational damages, as well as customer loss and trust erosion. To ensure data security, you should identify and classify your data according to its sensitivity and value; for instance, using public, internal, confidential, or restricted classifications. It's also important to implement data security controls and measures for storage, transmission, and processing; for example, using encryption, authentication, authorization, firewalls, antivirus software, and backups. You should also comply with applicable regulations and standards in your industry and location; such as the GDPR, PCI DSS or HIPAA. Finally, you should educate and train your staff on data security best practices and policies; like providing awareness sessions with guidelines and resources to your developers and users.

3 Data usability

Data usability, or the ease of access, understanding, and use of data, is important for software development as it enables developers to leverage data for innovation, optimization, and decision-making. It can also enhance the user experience and satisfaction of applications. To ensure data usability, you should define goals and requirements for your data products and services by using user research, feedback, and testing to identify customer and stakeholder needs. Additionally, you should implement data usability principles and techniques such as data modeling, metadata, data dictionaries, data catalogs, and data visualization to organize and display your data. Finally, offer data access tools, documentation, training, and helpdesk to facilitate and improve data usage for both consumers and producers.

4 Data governance framework

Creating a data governance framework can help you align your data governance objectives with your business goals and ensure the consistency, efficiency, and effectiveness of your data governance activities. To create a framework, you should assess your current data governance maturity and gaps using models, such as the Data Governance Institute's (DGI) Data Governance Framework or the IBM Data Governance Unified Process. Additionally, define your data governance vision and strategy using the SMART criteria (Specific, Measurable, Achievable, Relevant, and Time-bound). Establishing your data governance organization and governance is also important; use the RACI matrix (Responsible, Accountable, Consulted, and Informed) to assign roles and responsibilities. Finally, implement your data governance processes and tools with frameworks like DAMA International's Data Management Body of Knowledge (DAMA-DMBOK) or ISO/IEC 38500:2015 standard. Additionally, use software like Collibra, Informatica, or Alation to automate and support your data governance tasks.

5 Data governance benefits

Data governance can bring many benefits to your software development projects, such as improving data quality and reliability, enhancing data security and compliance, boosting data usability and value, and supporting data collaboration and alignment. This can reduce errors, bugs, rework, and maintenance costs; prevent data breaches, fines, lawsuits, and reputation loss; enable data-driven innovation, optimization, and decision-making; and foster data sharing, reuse, and integration across teams. Ultimately, it can ensure the confidentiality, integrity, and availability of your data while aligning the objectives of data governance with business goals.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?