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Best Practices for Data Governance in Enterprise Data Warehousing

March 11, 2024

In today’s world which is run by data, firms rely heavily on such solutions as data warehouses for the storage, management and analysis of huge volumes of data. As companies aim to get the best out of their information sources, they must make sure that it is properly governed. Enterprise data warehousing comprises processes, policies and controls that are used to guarantee the quality, security and conformity of data. Within this document, there will be an exhaustive discussion of the practices meant to strengthen the robustness of governance in enterprise data warehousing.

Key Components of Data Warehouse Governance

Data Quality Assurance

According to Gartner, poor data quality costs organizations an average of $15 million per year. Data quality assurance lies at the heart of any data warehouse governance strategy. It ensures the data stored in a warehouse is accurate, complete consistent and timely. This can be done through several processes including profiling, cleansing validating or enriching them. By sticking to high levels of quality for their systems, firms can depend upon their databases to facilitate major corporate decisions.

Data Security Measures

According to the IBM Cost of Data Breach Report 2023, The average cost of a data breach reached an all-time high in 2023 of USD 4.45 million. This represents a 2.3% increase from the 2022 cost of USD 4.35 million. Data warehouse governance is focused on data security by protecting confidential data against unauthorized access, breaches or other harmful actions. This may involve the use of such measures as strong access controls, encryption protocols, authentication mechanisms as well as monitoring tools. Organizations that safeguard their data assets can avoid risks and maintain the confidence of clients, partners and regulators.

Compliance Adherence

A survey by PricewaterhouseCoopers (PwC) found that 91% of organizations consider compliance with data protection laws and regulations a top priority. Compliance observance involves ensuring adherence to applicable regulatory frameworks, industry standards and internal processes in handling data within the data warehouse. These range from regulations like GDPR, HIPAA, CCPA and others that regulate aspects of privacy, security and confidentiality over information. Compliance with these provisions keeps an organization out of legal trouble while protecting its brand image and maintaining customer loyalty.

Strategic Alignment

Data warehouse governance initiatives need to be aligned with the overall business strategy and objectives. This means that IT and business stakeholders collaborate to prioritize the data governance efforts based on business priorities, risk assessments, and value propositions. Organizations aligning their data governance in data warehouse with strategic goals can achieve the maximum value from their data assets and drive business growth.

These key components of data warehouse data governance provide a basis for effective management of data, which in turn results in improved security systems, conformity issues as well as better strategy choices within these firms. By taking care of each component properly, an organization can come up with a strong framework on which it can build its objectives while supporting them through a sustainable network of data governance for data warehouse ensuring the integrity and reliability of its assets.

Data Warehouse Standards and Best Practices

Data warehouse governance is crucial for ensuring the integrity, security, and usability of data within enterprise data warehousing environments. Here are some data warehouse governance best practices to consider:

Establish Clear Policies and Procedures

Research by IBM revealed that organizations lose an average of 12% of their revenue due to poor data quality.

Develop Comprehensive Policies 

Create well-defined data governance policies that outline the objectives, principles, and procedures for managing data within the data warehouse management. These policies should cover data acquisition, transformation, storage, access control, data quality assurance, and compliance requirements.

Document Procedures

Write in great detail how data governance activities are performed such as data profiling among others. Define clearly who is who among the stewards of the company’s information such as administrators and users of the same. Include steps showing how this is done at every stage of management.

Communicate Policies

It is important to make sure that everyone involved understands fully what these policies mean for them including business people who use them to make decisions regarding their IT systems. Conduct sessions where stakeholders can be trained on how to follow the rules they have agreed upon.

Implement Robust Metadata Management

A study by Experian found that 89% of organizations believe that inaccurate data is undermining their ability to provide an excellent customer experience. 

Centralize Metadata Repository

Construct a central store for metadata connected to data assets in the security of data warehousing. The metadata repository should contain comprehensive metadata descriptions such as data definitions, schema information, lineage information, usage statistics and business glossaries.

Automate Metadata Capture

Metadata management tools along with automation technologies should be used to capture and maintain the metadata during the lifecycle of data. Metadata extraction data governance techniques must be implemented to automatically capture metadata from source systems, data integration processes and analytic applications.

Leverage Metadata for Impact Analysis 

Take advantage of metadata by conducting impact analysis and traceability assessments so that stakeholders can easily understand how different pieces relate to each other when it comes to things like, say, elements of data or sources or other applications down-stream. Use knowledge about meta-data for identification of dependencies to determine impact changes that may arise and ensure the integrity of data.

Foster Data Stewardship and Ownership

Research by McAfee estimated that cybercrime costs the global economy over $1 trillion annually. A recent survey found that the average cost per lost or stolen record containing sensitive and confidential information is $150. 

Appoint Data Stewards

Assign data stewards who are dedicated and oversee the conduct of data governance activities within specific business divisions or in functional areas. The individuals assigned should be well-versed in their areas of specialty, and have the needed technical expertise and authority to enforce policies set by the governing bodies on matters about data maintenance.

Empower Data Stewards

Empower your stewards with the necessary tools, resources, and powers for the effective performance of their roles in BI governance. Training support is crucial to enable them to grasp data governance principles, processes, and data warehouse best practices that can be implemented.

Promote Data Ownership

Build a culture of accountability by encouraging business users and those who consume information to take responsibility for quality, accuracy and usability. Promote cooperation between data owners, custodians and stewards to ensure they meet business requirements and objectives.

Embrace Data Lifecycle Management

The International Association of Privacy Professionals (IAPP) reported that non-compliance with GDPR could result in fines of up to €20 million or 4% of the organization’s global annual turnover, whichever is higher. 

Define Lifecycle Phases

In creating, collecting, storing, transforming, analyzing, preserving and disposing of data, define unambiguous life cycle steps. Develop procedures and regulations for each stage of the lifecycle which describe the operations to be undertaken on a data asset and the retention requirements.

Automate Lifecycle Processes

Adopt automated workflows and processes that will enable efficient management of the data lifecycle. Employing governance tools for data and platforms for managing it will help coordinate tasks about moving, changing it as well as archiving in line with legal rules and internal guidelines.

Monitor Lifecycle Activities

Oversight is important to ensure compliance with GRC policies and regulatory instructions during all stages of data’s existence. Consequently, logs must be maintained while audit trails are established so that deviations from prescribed processes or unauthorized entry can be detected promptly.

Leverage Technology Solutions

Research by McKinsey & Company revealed that organizations that prioritize data and analytics in their strategic agendas are 23 times more likely to acquire customers, six times as likely to retain customers, and 19 times more likely to be profitable.

Invest in Governance Tools

Invest in data governance tools, metadata management platforms, and data quality solutions which support the adoption of best governance practices. Opt for technologies with such features as metadata catalogues, lineage visualization, policy enforcement and role-based access control.

Integrate with Existing Systems

Merge the data governance tools with existing architectural foundations of the data warehousing system that includes ETL (Extract, Transform, Load) tools; data integration platforms; Business Intelligence Governance tools; and data visualization applications. To ensure completeness in the interoperability and flow of information across compliant systems through operational environments.

Enable Self-Service Capabilities

Give business end users and data consumers self-service capabilities to discover access and analyze governed assets. Implement intuitive user interfaces with search capabilities as well as a visualized lineage feature for ease finding of relevant assets using Data Catalog solutions.

Prioritize Data Privacy and Security

According to Forrester, organizations that prioritize data governance as part of their digital transformation efforts are 166% more likely to achieve their business goals. 

Implement Security Controls

Implement robust security controls to protect sensitive data from unauthorized access, disclosure or tampering. Utilize encryption techniques, access controls, authentication mechanisms and data masking techniques to ensure the privacy and confidentiality of data.

Comply with Regulations

Complying with data privacy regulations and industry standards such as GDPR (General Data Protection Regulation), HIPAA (Health Insurance Portability and Accountability Act), CCPA (California Consumer Privacy Act) PCI DSS (Payment Card Industry Data Security Standard). Regularly review and update security policies and procedures to address evolving threats and regulatory requirements.

Educate Employees

Impart complete training programs that include awareness for employees about best practices in data warehousing about the protection of information like this, standard protocols involving safety measures and meeting rules that are legal. Breed a consciousness promoting accountability for saving records securely among members of staff so they can report any matter related to security at work.

Monitor and Measure Governance Effectiveness

A survey by Harvard Business Review Analytic Services found that 82% of executives believe that data and analytics are extremely important for achieving strategic goals.

Define Key Performance Indicators (KPIs)

Specify the metrics and KPIs that determine the efficiency of data governance initiatives. Identify indicators that are linked to data quality, security compliance, user satisfaction, governance process efficiency and business impact.

Monitor KPIs Continuously

On an ongoing basis keep track of and monitor these performance measures to evaluate how well data management programs are functioning and then pick out areas for improvement. Displaying trends, abnormalities, and associations in KPIs by using dashboards’ tools, the reporting mechanism as well as data & analytics governance techniques.

Iterate and Improve

These numbers should be utilized to improve on existing data governance strategy plans by asking for input from stakeholders such as top management including Chief People Officers (CPOs), Managing Directors (MDs) and Country Managers (CMs). In addition, this will help them in facing new challenges about business objective realization since it is essential to have aligned efforts.

Following these best practices in governing a Data Warehouse allows companies an opportunity to build a solid framework for ensuring high-quality information assets; good security and compliance oversight; thus encouraging job flexibility; promoting innovation & expanding competition for market share.

How can Brickclay Help?

As Brickclay specializes in enterprise data warehouse services, the company can play a pivotal role in helping organizations implement effective data warehouse governance practices. Here’s how Brickclay can assist its clients in this endeavor:

  • Consultation: Brickclay offers expert assessment and consultation services to evaluate clients’ data governance needs and challenges.
  • Strategy Development: We collaborate with clients to develop tailored data governance strategies aligned with their business goals and compliance requirements.
  • Policy Establishment: Brickclay assists in drafting and refining data governance policies, ensuring clarity, consistency, and compliance.
  • Technology Implementation: We deploy and configure data governance tools and platforms to support metadata management, data lineage tracking, and policy enforcement.
  • Training: Brickclay provides comprehensive training sessions to educate client teams on data governance principles, best practices, and tool usage.
  • Continuous Improvement: We offer ongoing support and advisory services to help clients continuously improve their data governance practices.
  • Regulatory Compliance: Our solutions ensure that clients comply with data privacy regulations and industry standards, mitigating risks and protecting sensitive information.
  • Business Value: By enhancing data quality, security, and compliance, Brickclay helps clients drive business agility, innovation, and competitiveness.

For personalized guidance on implementing robust data governance solutions tailored to your organization’s needs, contact Brickclay’s expert team today.

About Brickclay

Brickclay is a digital solutions provider that empowers businesses with data-driven strategies and innovative solutions. Our team of experts specializes in digital marketing, web design and development, big data and BI. We work with businesses of all sizes and industries to deliver customized, comprehensive solutions that help them achieve their goals.

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