Data is the lifeblood of decision-making. Yet, for large enterprises managing vast volumes of reports, dashboards, and analytics daily, extracting meaningful insights can feel like navigating a maze. Success hinges on bridging the gap between raw data and actionable insights—but for many organizations, this remains an ongoing challenge.

Three Challenges in Analytics Management

#1. Data Fragmentation and Duplicated Reports

#2. Challenges in Democratizing Data

#3. Cost Challenges with Traditional Licensing Models

One Simplified Solution

Our study, The State of Enterprise Analytics, which surveyed 200 respondents from mid-size to large organizations, revealed the following insights:

• • 53% of Data Product Managers struggle to communicate data effectively to the business.
  • 46% of Data Analytics Managers face disorganization and a lack of standardization in analytics.
  • 67% of Data Governance Managers cite a lack of data literacy and awareness across departments.

These challenges perpetuate what we call the “Vicious Cycle of Enterprise Analytics.”

On one side, Business Users demand quick, data-driven decisions; on the other, Data Teams focus on delivering high-quality, governed analytics. Despite the best intentions, ad-hoc analytics often bypass governance checks, leading to poor data quality, security risks, and a general mistrust in corporate analytics.

Three Challenges in Analytics Management

#1. Data Fragmentation and Duplicated Reports

Data fragmentation is a significant obstacle in large organizations, with various teams generating reports across multiple tools and systems. This results in:

Redundant reporting creates inconsistencies, making metric alignment and cross-department comparisons difficult.

Managers spend more time searching for data than analyzing it for strategic decisions.

Poor organization leads to user frustration, with many abandoning tools altogether.

Fragmentation undermines efficiency and creates governance challenges, leaving businesses unable to fully capitalize on their analytics investments.

#2. Challenges in Democratizing Data

Building a data-driven culture requires democratizing analytics, but this process must be balanced with solid governance to avoid pitfalls:

Without oversight, metrics and reports often vary, leading to confusion and decision-making based on unreliable insights.

A lack of visibility into existing analytics assets increases effort duplication and quality risks.

Transparency about metrics, calculations, and data sources fosters trust and usage, improving overall data literacy and culture.

Organizations must ensure users have clear, accessible insights into the analytics ecosystem while maintaining governance.

#3. Cost Challenges with Traditional Licensing Models

The high cost of per-user licenses in traditional BI tools presents a financial burden for organizations. Cloud-based capacity consumption models offer a cost-reduction solution, often saving up to 50%. By paying only for the actual usage of the platform, businesses eliminate the need for individual licenses and gain access to a scalable infrastructure that adjusts to their data volume without wasting resources.

One Simplified Solution

To tackle these challenges, we developed Genuz, a platform designed to centralize and streamline the management of your organization’s analytics assets. With Genuz, you and your team will:

+ Overcome bottlenecks.
+ Manage and oversee reports from a central location.
+ Save up to 50% and avoid costly per-user licenses of some BI tools.

Propel your business (and analytics) forward with Genuz!
Contact our specialists today to take the next step.