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Modernizing Platforms: A Roadmap to Advanced Analytics

By
Culture

In the era of data-driven decision-making, the demand for advanced analytics and artificial intelligence has never been higher. Yet, many organizations find themselves held back by outdated, fragmented business intelligence platforms that stifle innovation, limit scalability, and impede their ability to compete. Modernizing these platforms isn’t just about staying current — it’s about creating a foundation for transformative growth.

This blog is the third in a three-part series about fast-tracking data and analytics maturity to accelerate value from advanced analytics and the content was featured in a webinar hosted by the International Institute for Analytics. Part Three provides a roadmap to explore the critical steps to modernizing your analytical infrastructure and how this journey unlocks the full potential of your data.

Tackling Business Intelligence Maturity: The Key to Advanced Analytics

As data and analytics leaders are making the strategic turn toward data-driven decision-making and advanced analytics for the enterprise, progress is slow for many because of BI maturity challenges—from data quality and accuracy to analytical integration. Catch Nathan Hombroek as he shares strategies to achieve high BI maturity and make significant strides in advanced analytics and AI.

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The Case for Business Intelligence Platform Modernization

A modernized business intelligence platform serves as the backbone for successful advanced analytics. Studies consistently reveal that organizations leveraging unified platforms for data provisioning and analytics achieve better outcomes. However, legacy systems often trap organizations in inefficiencies, such as:

  • Replicated Business Logic: Different tools maintain overlapping logic, complicating consistency and increasing maintenance.
  • Tool Sprawl: Years of accumulating disparate tools create redundant systems, driving up costs and complexity.
  • Barrier to AI Readiness: Older platforms struggle to integrate the seamless, real-time capabilities required for advanced analytics and AI.

These issues result in more than operational inefficiencies — they limit the organization’s ability to innovate. A fragmented BI landscape hinders agility, leading to delayed decision-making, slower response to market changes, and missed opportunities. Platform modernization, therefore, becomes a strategic necessity rather than a technical luxury.

Step 1: Understand Your Current Environment

Before you can modernize, you need a clear and comprehensive understanding of your existing BI systems. This diagnostic phase includes:

  • Analyzing Metadata: Use APIs and automated tools to extract information about how current systems are used. This analysis provides insight into who is using what, how often, and why. Metadata analysis can also reveal inefficiencies like underutilized resources or bottlenecks in workflows.
  • Assessing Usage: Identify outdated or underutilized applications. For instance, one organization I worked with recently analyzed over 1,000 legacy applications, with 70% deemed unnecessary after review. Such insights free up resources and reduce complexity, enabling focus on high-value systems.
  • Documenting Systems: Leverage APIs and automation to create detailed documentation of the current architecture. This ensures alignment among stakeholders and enables smooth transitions. It also highlights areas where duplication or conflicting business logic might exist.
  • Tracing Data Lineage: Understand how data flows through your systems, especially where business logic is embedded within tools. This mapping identifies redundancies and highlights areas needing simplification. For example, discovering that multiple reports derive similar insights but use different datasets can help streamline processes.

This phase is crucial not just for identifying inefficiencies but for fostering stakeholder buy-in. A clear understanding of the current environment builds a shared vision of what success looks like.

Step 2: Chart the Path to BI Modernization

With a detailed understanding of your infrastructure, the next step is to create a strategic roadmap for modernization. Legacy applications go in one of three directions:

  1. Deprecate: Retire systems and applications that no longer add value. Usage analytics can pinpoint redundant tools and reports for decommissioning. For instance, if two reporting tools serve overlapping functions, consolidating to a single, more capable platform reduces costs and simplifies maintenance.
  2. Lift and Shift: Migrate critical reports or applications to the new platform as-is if they don’t require reengineering. This approach accelerates migration while maintaining continuity for business-critical processes.
  3. Reimagine: Redesign complex applications or redundant application sets to take full advantage of modern capabilities. Consolidate similar tools or reports into streamlined, user-friendly solutions. Reimagining also involves adopting new technologies like cloud-native architectures or AI-driven analytics for increased scalability and innovation.

A well-crafted roadmap aligns technical priorities with business objectives, ensuring modernization efforts deliver tangible value. Collaborating with stakeholders from IT, business units, and leadership ensures alignment and helps prioritize initiatives that yield the greatest impact.

Step 3: Define Success Beyond Migration

True modernization success is not merely about completing migrations on time or reducing costs. It’s about enabling transformation and innovation. Success metrics should include:

  • Data Accuracy: Maintaining integrity during and after migration. Without accurate data, even the most advanced platform will fail to deliver meaningful insights.
  • Enhanced User Experience: Ensuring the new platform meets or exceeds user expectations. This includes improving accessibility, reducing query times, and providing intuitive interfaces.
  • Increased Adoption: Measuring how well end users embrace the modernized platform. High adoption rates indicate that the platform meets business needs effectively.
  • Value Creation: Demonstrating improved decision-making, operational efficiency, and new opportunities unlocked by the modernization effort. For example, faster reporting cycles or AI-driven insights that lead to revenue growth.

These metrics ensure the modernization effort aligns with long-term goals and delivers sustained benefits. Regularly revisiting these metrics post-modernization ensures continuous improvement.

Leveraging Automation for Efficiency

Modern tools and technologies make the daunting task of platform modernization more manageable. Tools like Vortex from Axis Group provide:

  • BI Metadata Extraction and Analysis: Automated tools identify inefficiencies and opportunities for optimization with unparalleled speed and precision. This enables rapid decision-making and resource allocation.
  • Accelerated Migrations: Automated conversion processes can handle up to 70% of migration work and reduce manual intervention. Converting legacy reports to cloud-based dashboards can be streamlined.
  • Consistency and Quality: Automation ensures uniformity in migrated systems, eliminating dual-platform expertise requirements and minimizing errors. By automating testing and validation, organizations can ensure smooth transitions without sacrificing quality.

Automation allows teams to focus on strategic priorities, such as integrating advanced analytics or enhancing user capabilities, rather than being bogged down by technical complexities.

The Benefits of BI Modernization

BI platform modernization delivers wide-ranging benefits, including:

  • Streamlined Operations: Consolidating tools reduces maintenance overhead and simplifies licensing. For example, a client of mine recently cut its licensing costs by 40% after retiring redundant tools.
  • Enhanced Decision-Making: Real-time data access and improved system performance empower faster, more informed decisions.
  • Catalyzed Innovation: Removing technical bottlenecks opens the door to advanced analytics, machine learning, and AI initiatives. Modern platforms enable predictive models, such as forecasting customer demand or identifying fraud patterns.
  • Cost Savings: Decommissioning outdated systems frees up budget for strategic investments.

The cumulative effect of these benefits is a more agile, resilient, and competitive organization. Organizations that embrace BI platform modernization position themselves not just to compete but to lead in their industries.

Conclusion: Modernization as a Catalyst for Innovation

Modernizing your BI and analytics platform is not merely a technical project; it is a strategic imperative. By rationalizing existing systems, charting a deliberate modernization plan, and leveraging automation, organizations can build a platform that supports their aspirations for innovation and growth.

In today’s competitive landscape, a modern platform is no longer optional. It is the launchpad for advanced analytics and AI, empowering teams to unlock value, embrace opportunities, and lead in their industries. Whether it’s enabling real-time decision-making, fostering collaboration, or driving AI adoption, the rewards of modernization are transformative.

It is the foundation on which organizations build their future, ensuring sustained success and industry leadership.

Next: Transforming Data Culture: The Key to Unlocking Analytics Potential