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Bae Systems [LON: BA]
Unveiling the Power of Data Visibility
Muhammad Saleem, Head of Data Architecture, BAE Systems, a seasoned data professional with extensive experience in designing and delivering data solutions for large organizations. He leads a multi-disciplinary team that helps clients across various industries achieve their strategic objectives through effective data management and delivery.
In this article, Muhammad draws on his expertise to explore the concept of data visibility, emphasizing its importance for informed decision-making, enhanced data processes and regulatory compliance. He delves into the challenges organizations face in achieving data visibility, such as data complexity, silos and governance issues, offering practical strategies and a framework for successful implementation. With a focus on collaboration, communication and ongoing maintenance, Muhammad provides valuable insights for organizations seeking to unlock the full potential of their data assets.
What is data visibility?
Data is like everyday items—useful when found, but useless when hidden. Just as a misplaced item takes up space and costs you without providing any benefit, hidden data presents a similar issue. This is where data visibility comes in, making data accessible and usable for analysis and decision-making.
Data visibility is the ability to identify, locate, access, track and oversee data usage throughout your entire organization. This encompasses knowing what data you possess, where it's stored, who can access it and how it's utilized.
Why it matters?
We all know that data holds the key to making smart decisions, uncovering customer insights and building innovative products and services. Without knowing what data we have and where it is, we cannot hope to secure it. Data visibility is key to enabling the provision of secure and accessible data.
For an organization to truly embrace data-driven practices, data visibility is essential. It also brings the following additional benefits:
Figure #1: Data Visibility Benefits
• Improved Customer Experience: End-to-end data visibility fosters a deep understanding of customer behaviour, aiding product development and trust-building.
• Better decision-making: Having data visibility enables you to conveniently view all relevant business data, making it easy to access the information necessary for informed decision-making.
• Regulatory Compliance: One will be capable of meeting regulatory compliance requirements such as responding to Subject Access Requests (SAR), ensuring data security and privacy.
• Improved Security: Organizations with strong data visibility can enforce security measures and manage user permissions to protect valuable information in line with policies and regulations.
• Smooth Data Migration: Just as with relocating, having a dependable inventory of data and applications is crucial for a smooth data migration especially to Cloud. It can also lead to cost savings by avoiding unnecessary transfers.
• Greater efficiency: Data visibility enhances operational efficiency by streamlining processes. When you have a clear view of your data's location and access permissions, you can eliminate redundant steps and efforts.
• Better-Trained AI Models: Data visibility means making all accessible data visible and usable, which can improve AI model training and result in better outcomes.
• Uncover Dark Data: Data visibility helps identify ‘dark data,’ which is data owned by an organization but not used in its operations or decision-making.
Put simply, data visibility is essential for ensuring data is accessible, used correctly, securely and in line with legal requirements. It aids in making informed decisions, enhancing data processes and fostering trust with stakeholders.
What challenges do organisations face in achieving data visibility?
If the benefits of data visibility are so apparent, one might question why organizations don't implement it more often. Implementing data visibility can be challenging for organizations due to various factors, such as:
• Data Complexity: Organisations face difficulty-maintaining visibility across all data assets due to the diverse range of data types, formats and sources they handle.
• Data Volume and Velocity: The growing volume and speed of data generated by organizations pose challenges for data visibility. Real-time data streaming, big data analytics and IoT devices contribute to this, making it harder to maintain visibility and control.
Figure #2: Data Visibility Challenges
• Data Silos: Data silos occur when data is scattered across different parts of an organization, hindering visibility and making comprehensive data analysis difficult.
• Distributed Data Management: The increasing use of cloud computing, especially hybrid and multi-cloud setups, leads to distributed data management, creating challenges for organizations to centrally track data.
• Lack of Data Governance: Poor data governance practices like undefined ownership, inconsistent policies and low data quality can impede data visibility.
• Integration Issues: Integrating data visibility solutions with current IT infrastructure, legacy systems and third-party apps can be difficult due to compatibility issues and data migration complexities. Interoperability challenges may also arise.
Data visibility is essential for ensuring data is accessible, used correctly, securely and in line with legal requirements. It aids in making informed decisions, enhancing data processes and fostering trust with stakeholders
• Resource Constraints: Limited budget, IT resources and expertise can hinder organizations from implementing comprehensive data visibility solutions.
• Change Management: Implementing data visibility often requires cultural and organizational changes. Resistance to change, lack of awareness and poor communication can hinder adoption and success.
Another significant challenge is that a data visibility initiative is not a one-time event—it's an ongoing process requiring maintenance due to the inevitability of changes.
To overcome these challenges and others, a strategic approach, departmental collaboration, investment in technology and resources, adherence to best practices and ongoing monitoring and improvement efforts are essential.
How can organisations achieve data visibility?
There isn't a single solution that can magically solve all the challenges associated with implementing data visibility. However, by following the framework outlined below, you can significantly improve the chances of success:
Figure #3: Data Visibility Implementation Framework
• Start with Why?: Documenting the reasons for needing data visibility and explaining how it can deliver anticipated business benefits is crucial.
• Get Business Buy-in: Share the findings with relevant business stakeholders to secure their approval and commitment to support the journey.
• Start small: Begin with modest scope, delivering value gradually and demonstrate progress to the business stakeholders. Adopt risk based approach by prioritising high-risk data sets initially. To comprehend your data landscape, document and assess the data you possess and its storage locations. Conduct this assessment at a broad level to gain insight and prioritize tasks effectively.
• Crowd Source: It might come as a surprise that various teams unknowingly gather metadata that could aid the data visibility initiative and should be leveraged. Instead of starting from square one, consider crowdsourcing from teams such as data architecture and integration.
• Deliver: Concentrate on the agreed-upon scope to deliver the data visibility solution. It is likely that there have been unsuccessful attempts to implement data visibility in the organisation. It would be beneficial to take learnings from those efforts and to review any available lessons learned documents.
• Collaborate: Collaborate with data management teams to ensure they fulfil responsibilities. Work closely with the data governance team to align data management with organizational policies, including communicating data changes for visibility.
• Communicate, Communicate and Communicate:
Consistently communicate progress and report back to stakeholders regarding achievements and value delivered to sustain their interest and support.
Remember, this is not just a one-time task, it is a continuous journey. It necessitates ongoing maintenance as new data, products and systems are regularly incorporated into the data ecosystem.
Integrate data visibility requirements into your data governance processes to ensure that necessary information is consistently captured during changes to data and associated systems. Regularly measure the benefits delivered by the data visibility to ensure focus high value and high-risk items.
Finally, implement relevant tooling to facilitate and automate data visibility maintenance processes.
