Unlocking the power of data governance by understanding key challenges

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Authors

Pradeep Kutty

Global Governance and Data Fabric Engagement Leader at IBM

Paul Christensen

Data Elite Architect, IBM Expert Labs

In our last blog, we introduced Data Governance: what it is and why it is so important. In this blog, we will explore the challenges that organizations face as they start their governance journey.

Organizations have long struggled with data management and understanding data in a complex and ever-growing data landscape. While operational data runs day-to-day business operations, gaining insights and leveraging data across business processes and workflows presents a well-known set of data governance challenges that technology alone cannot solve.

Every organization deals with the following challenges of data governance, and it is important to address these as part of your strategy:

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Multiple data silos with limited collaboration

Data silos make it difficult for organizations to get a complete and accurate picture of their business. Silos exist naturally when data is managed by multiple operational systems. Silos may also represent the realities of a distributed organization. Breaking down these silos to encourage data access, data sharing and collaboration will be an important challenge for organizations in the coming years. The right data architecture to link and gain insight across silos requires the communication and coordination of a strategic data governance program.

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Inconsistent or lacking business terminology, master data, hierarchies

Raw data without clear business definitions and rules is ripe for misinterpretation and confusion. Any use of data – such as combining or consolidating datasets from multiple sources – requires a level of understanding of that data beyond the physical formats. Combining or linking data assets across multiple repositories to gain greater data analytics and insights requires alignment. It needs linking with consistent master data, reference data, data lineage and hierarchies. Building and maintaining these structures requires the policies and coordination of effective data governance.

A need to ensure data privacy and data security

Data privacy and data security are major challenges when it comes to managing the increasing volume, usage, and complexity of new data. As more and more personal or sensitive data is collected and stored digitally, the risks of data breaches and cyber-attacks increase. To address these challenges and practice responsible data stewardship, organizations must invest in solutions that can protect their data from unauthorized access and breaches.

To learn more about efficient data privacy and security, checkout the Data Differentiator.

Ever-changing regulations and compliance requirements

As the regulatory landscape surrounding data governance continues to evolve, organizations need to stay up-to-date on the latest requirements and mandates. Organizations need to ensure that their enterprise data governance practices are compliant. They need to have the ability to:

  • Monitor data issues
  • Ensure data conformity with data quality
  • Establish and manage business rules, data standards and industry regulations
  • Manage risks associated with changing data privacy regulations

Lack of a 360-degree view of organization data

A 360-degree view of data refers to having a comprehensive understanding of all the data within an organization, including its structure, sources, and usage. Think about use cases like Customer 360, Patient 360 or Citizen 360 which provide organizational-specific views. Without these views, organizations will struggle to make data-driven business decisions, as they may not have access to all the information they need to fully understand their business and drive the right outcomes.

The growing volume and complexity of data

As the amount of data generated by organizations continues to grow, it will become increasingly challenging to manage and govern this data effectively. This may require implementing new technologies and data management processes to help handle the volume and complexity of data. These technologies and processes must be adopted to work within the data governance sphere of influence.

The challenges of remote work

The COVID-19 pandemic led to a significant shift towards remote work, which can present challenges for data governance initiatives. Organizations must find ways to effectively manage data and track compliance across data sources and stakeholders in a remote work environment. With remote work becoming the new normal, organizations need to ensure that their data is being accessed and used appropriately, even when employees are not physically present in the office. This requires a set of data governance best practices – including policies, procedures, and technologies – to control and monitor access to data and systems.

If any or all of these seven challenges feel familiar, and you need support with your data governance strategy, know that you aren’t alone. Our next blog will discuss the building blocks of a data governance strategy and share our point of view on how to establish a data governance framework from the ground up.

In the meantime, learn more about building a data-driven organization with The Data Differentiator guide for data leaders.

 

 
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