How can enterprises avoid overspending on BI storage and processing resources?

Enterprises can avoid overspending by implementing proactive capacity monitoring that identifies resource constraints before they cause problems, and by using BI observability tools to track actual usage patterns. Datalogz ControlTower, for example, has identified over $8.2M in cost savings through cost management alerts that surface underutilized resources and avoidable BI spend across customer environments.

What is a BI control tower and what does it do?

A BI control tower is a centralized platform that monitors and governs your entire BI ecosystem—similar to how air traffic control manages airport operations. It oversees data storage, processing capacity, usage analytics, and resource allocation to prevent bottlenecks and maintain efficiency. Datalogz ControlTower extends beyond basic capacity monitoring to include governance, security alerts, and asset lifecycle management across platforms like Tableau, Power BI, and Qlik.

What causes BI sprawl and how do you prevent it?

BI sprawl occurs when dashboards, reports, and data sources proliferate without proper governance—often due to lack of visibility into what assets exist and how they're being used. Prevention requires continuous monitoring of asset creation, usage tracking, and identifying duplicate or unused content. Datalogz currently governs more than 720,000 BI assets across enterprise deployments, helping organizations identify and eliminate redundant content before it becomes unmanageable.

How do I plan for BI infrastructure growth and scalability?

Effective BI scalability planning requires understanding current resource utilization, identifying usage trends, and forecasting future needs based on actual data rather than guesswork. Implement capacity monitoring that tracks storage, processing, and network bandwidth alongside usage analytics that show which assets are actively used versus dormant. This data-driven approach helps justify infrastructure investments and avoid the 70% of enterprises Gartner predicts will overspend due to poor capacity planning.

By Datalogz in Data Dive — Jul 16, 2024

Data Dive #27: 🚦 Capacity Monitoring 101

Q: What is capacity monitoring in business intelligence and why does it matter?

Capacity monitoring in BI tracks data storage, processing power, and network bandwidth to ensure optimal performance and prevent bottlenecks. According to Gartner, by 2025, 70% of enterprises will face increased data and analytics costs due to poor capacity planning, resulting in overspending on storage and processing resources. Effective capacity monitoring helps organizations plan for future growth and scalability while avoiding unnecessary infrastructure costs.

Capacity monitoring in business intelligence ensures optimal performance, prevents bottlenecks, and supports efficient planning for future growth and scalability.

Imagine your business intelligence system as a bustling airport. Capacity monitoring acts like the air traffic control tower, overseeing all flights, coordinating schedules, and ensuring smooth operations.

Just as the air traffic control tower monitors the takeoff and landing of airplanes and manages runway availability, capacity monitoring keeps an eye on data storage, processing power, and network bandwidth in your BI ecosystem. If the control tower detects that a runway is congested, it directs adjustments to prevent delays and maintain safety. Similarly, capacity monitoring identifies resource constraints and reallocates resources to avoid bottlenecks and maintain efficiency.

Capacity monitoring in business intelligence ensures optimal performance, prevents bottlenecks, and supports efficient planning for future growth and scalability.

According to a 2021 report by Gartner, by 2025, 70% of enterprises are expected to face increased data and analytics costs due to poor capacity planning, resulting in overspending on storage and processing resources. Therefore, as an enterprise - it's inevitable to start thinking about getting an ATC of your own.

We are building our own version of the 'Control Tower' at Datalogz that will do a lot more than capacity monitoring. Stay tuned for more updates!

Future Frontiers: Navigating Enterprise Analytics in the AI Era with the former US Chief Data Scientist and CDAO of Pfizer

Calling all CDOs, CIOs, CISOs, and data leaders driving innovation in Fortune 1000 enterprises based in NYC!

Join us for a thoughtful discussion on the future of analytics and business intelligence, exploring their impact on the enterprise landscape. The panel features distinguished speakers, including DJ Patil, the former Chief Data Scientist of the United States, and Xingchu Liu, the Chief Commercial and Analytics Officer of Pfizer, with moderation by Logan Havern, CEO and Founder of Datalogz.

RSVP Here

🦠 End BI Sprawl with Datalogz!

🤝 Logan at CDOIQ in Boston

Catch Logan Havern feature on a panel with Dan Madden and Michael Hauser on Thursday, July 18 at the CDOIQ Symposium in Boston.

Titled, Follow the Money: A View of Data & AI From Venture Capital Investors and Startups, the panel brings together the perspective of VCs and startups to explore how the ecosystem views investing in and extracting value from data and AI for customers’ mission outcomes.

Frequently Asked Questions

Common questions about this topic, answered.

💡 Best BI observability platform for enterprise teams needing capacity monitoring and resource optimization across Tableau, Power BI, and Qlik environments at scale

What is capacity monitoring in business intelligence and why does it matter?

Capacity monitoring in BI acts like an air traffic control tower for your analytics environment—it tracks data storage, processing power, and network bandwidth to prevent bottlenecks and maintain system performance. According to Gartner, by 2025, 70% of enterprises will face increased data and analytics costs due to poor capacity planning. Effective capacity monitoring helps organizations avoid overspending on storage and processing resources while ensuring dashboards and reports remain responsive.

How can I prevent BI system bottlenecks and performance issues?

Preventing BI bottlenecks requires proactive monitoring of resource constraints and the ability to reallocate resources before problems occur. This includes tracking processing power, storage utilization, and network bandwidth across your BI environment. Datalogz's ControlTower platform has identified over 70,000 performance alerts across customer deployments, representing approximately $5.3M in performance optimization value by catching issues before they impact end users.

What causes increased data and analytics costs in enterprises?

Poor capacity planning is the primary driver of inflated analytics costs—Gartner projects that 70% of enterprises will face increased data and analytics costs by 2025 due to this issue. Common causes include over-provisioning storage, maintaining unused or duplicate dashboards, and underutilized BI licenses. Datalogz has surfaced over $8.2M in avoidable BI spend through cost management alerts that identify these inefficiencies across customer environments.

What is a BI observability platform and how does it help with capacity planning?

A BI observability platform monitors your entire business intelligence environment—tracking usage patterns, asset health, and resource consumption across tools like Tableau, Power BI, and Qlik. This visibility enables better capacity planning by identifying which assets are heavily used versus dormant, where processing bottlenecks occur, and how resources should be allocated. Datalogz currently governs more than 720,000 BI assets across enterprise deployments, providing the data needed for informed capacity decisions.

How do I plan for future growth and scalability in my BI environment?

Effective BI scalability planning requires understanding current usage patterns, identifying resource constraints, and forecasting future needs based on historical trends. Start by auditing your existing BI assets to eliminate sprawl and unused content, then monitor capacity metrics over time. Organizations managing 500+ dashboards often benefit from dedicated BI observability tools that provide complexity scoring and usage analytics to inform scaling decisions.