JULY 2024CIOAPPLICATIONSEUROPE.COM 19Data 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 stakeholderscontribute to this, making it harder to maintain visibility and control.· 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.· 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:· 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. Figure #2: Data Visibility ChallengesFigure #3: Data Visibility Implementation Framework
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