The Transformative Landscape of Data Platforms

Brian Henn
Blog Post
January 19, 2024
The Transformative Landscape of Data Platforms
AI & Data

Over the last 20+ years, the technology landscape has experienced substantial changes that continue to reshape how organizations operate. As the technology landscape continues to evolve, it is evident that the world of data is experiencing significant transformations, too. These transformations continue to make a direct impact on an organization’s ability to interact with and utilize their data in real time, leading to more informed business priorities and data-driven business decisions. Organizations must prioritize data by reflecting on past practices, current priorities and by giving renewed attention to three fundamental data categories.  

Increased Prioritization of Data Platforms

Historically, organizations have not always prioritized their data platforms, but that trend is changing as they continue to evolve. As an example, a clinical research organization hired a professional in the early stages of their career as a systems administrator, responsible for overseeing four major, mission-critical business applications. These applications were highly regulated and required extensive testing and documentation that often led to significant amounts of paperwork.

One of the specific applications they were responsible for included Crystal Reports/Crystal Enterprise. Despite the crucial role the application played in generating reports for internal operations and key external stakeholders like big pharmaceutical clients, the organization did not deem the data application as imperative. The decision rested on the belief that the team could retrieve the data directly from the source applications if an outage occurred in the reporting environment. Developing and maintaining the reports required a substantial amount of time, effort and resources, leading to many questions about this peripheral view. Interestingly, this perspective persisted through the years, even as technologies like data warehousing, big data and cloud-based data platforms emerged. 

As today’s data landscape evolves with the emergence of technologies like cloud-based data platforms and agile delivery methods, organizations are moving away from a peripheral stance, like in the business scenario described above, and shifting to a prioritized stance around their data platforms. A recent survey of over 500 business leaders found that 88% of those surveyed believe market disruptors, like artificial intelligence, increased operational costs, skill shortages and consumer expectations, will escalate in 2024. To combat these trends, 87% of those leaders surveyed confirmed that high quality, trusted data will play a critical role, leading to an increased investment in high-quality data platforms.  

Now more than ever, organizations must renew their focus on three fundamental categories as the data landscape continues to expand:

1. Data Platforms as "Critical" Applications

The shift towards recognizing data platforms as critical applications is essential, and not just from a technological standpoint. The integration of an impactful data platform provides organizations with a more comprehensive understanding of their strategic value.  

Data, in these instances, become the cornerstone of informed decision-making, where large amounts of data from various sources comes together to drive real-time decisions and insights. Improved data movement and integration allows different systems to communicate effectively, eliminating data silos while streamlining operations and increasing organizational collaboration.  

Data platforms also play a pivotal role in generating accurate and timely reports, allowing internal stakeholders at all levels to quickly access information that can range from financial reports and performance metrics to customer insights, with an ability to customize them to meet specific organizational requirements. Identifying data platforms as a critical application is a foundational element of an organization’s digital transformation that generates sustainable growth, empowers innovation and drives adaptability through changing market dynamics.

2. Data Security and Governance 

The implementation and documentation of robust security and governance measures is paramount to an effective data platform. Specific security measures like data encryption, access controls and data masking techniques allow an organization to safeguard sensitive information of both customers and employees. Limiting access to specific data sets minimizes the risk of data exposure and the potential financial and reputational damage that often follows.

Effective data governance has a significant impact on an organization’s bottom line, and not just by maintaining regulatory compliance. By properly leveraging its data streams, a company can identify new revenue opportunities based on customer preferences and create personalized offerings through targeted marketing opportunities. In addition to uncovering new revenue opportunities, efficient data governance can identify data redundancies, allowing an organization to optimize its operations and reduce its costs by maximizing its existing resources, policies and procedures.    

3. Data Trustworthiness

Establishing and maintaining data trustworthiness should always be a top priority for an organization and it is why having established data security and governance measures in place is necessary—since they directly influence the reliability, accuracy and integrity of a data platform.  

To provide trustworthy data, organizations should adopt standardized compliance and quality assurance procedures. Conducting regular compliance audits highlights a dedication to ethical data practices and allows an organization to immediately address areas of non-compliance. By conducting automated and manual data checks and regular data cleanses, an organization can eliminate outdated or incorrect data and ensure they provide stakeholders with high-quality, reliable data. This instills confidence and trust in the data that is driving critical business decisions.  

When organizations prioritize data as an asset, they signal a shift in how they maintain and prioritize data, establishing a foundation of collaboration, trust and transparency throughout the organization.

BUILT's Approach to Cloud and Data Services 

How does your organization value its data environments? This is a question that every organization must answer as they navigate the ever-changing terrain of data management. The evolution of data platforms is ongoing and recognizing their critical role is key to staying ahead in the dynamic world of technology. 

At BUILT, our cloud and data services practice dedicates itself to helping organizations determine the best strategies for protecting and prioritizing their investments in data movement, reporting systems and digital assets.  

For more information on BUILT’s cloud and data services, or to speak with one of our digital transformation experts, go to  

About the author, Brian Henn, Partner at BUILT and Head of Solution Delivery: Brian is a proven IT leader with a broad depth of experience serving clients across many industry verticals. Focused most recently on banking and retail clients, helping them to think in new and innovative ways to allow data, specifically strategic data management initiatives and architecture, to become a trusted, secure, and monetized asset for their organization.

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