Transforming BI Governance: Datalogz Tackles BI Ops for the Critical Consumption Layer

NEW YORK--()--Business intelligence (BI) has revolutionized the way organizations interact with their data, making advanced analytics accessible to non-technical users and empowering decision-makers with actionable insights. With tools like Microsoft Power BI, Tableau, Looker, and Qlik, BI has become the critical interface between enterprise data and business users. However, as BI adoption accelerates, a critical gap has emerged: governance at the consumption layer.

BI sits at the intersection of data and decision-making. It’s where insights are generated, dashboards are built, and reports are delivered. Yet the rapid proliferation of BI tools and reports—coupled with growing data volumes—has introduced new challenges. Organizations are grappling with fragmented standards, duplicate datasets, conflicting reports, and potential security risks.

According to McKinsey, BI and reporting now account for 5-10% of total IT spend. Despite investments in data governance at the warehouse level, many organizations are finding that these efforts do not extend to the consumption layer where BI operates. This gap has created inefficiencies, eroded trust in data, and exposed organizations to security vulnerabilities.

Introducing BI Ops: Governance at the BI Layer

Datalogz is proud to introduce BI Ops, a new approach to governance designed specifically for the consumption layer. By focusing on BI reporting, datasets, user behavior, platform administration, and resource consumption, BI Ops bridges the gap between data governance and BI operations.

“BI is where the majority of employees interact with data directly. Without proper governance, the benefits of democratized data can quickly become liabilities,” said Logan Havern, CEO at Datalogz. “BI Ops ensures that business intelligence remains a trusted, secure, and efficient driver of decision-making.”

The Three Pillars of BI Ops Governance

  1. Source of Truth: BI Ops ensures data is accessible through reliable, verified sources, reducing redundancy and improving clarity.
  2. Trust: By promoting consistency and accuracy, BI Ops builds confidence in BI reports and dashboards.
  3. Security: BI Ops provides robust oversight of data access and sharing, safeguarding sensitive information.

Datalogz Control Tower: Enabling BI Ops

At the core of Datalogz’s BI Ops solution is the Datalogz Control Tower, a platform designed to bring visibility, monitoring, and security to the consumption layer.

Key features include:

  • Unified Metadata Extraction: Provides visibility into BI environments across multiple platforms.
  • Monitoring and Alerts: Tracks asset creation, engagement, and failures while identifying discrepancies, redundancies, and unverified datasets.
  • Security Oversight: Monitors user behavior, data exports, and administrative changes to mitigate risks.

By addressing these areas, the Datalogz Control Tower empowers organizations to optimize BI usage, eliminate inefficiencies, and enhance security across their analytics stack.

The Future of BI Governance: BI Ops

The rise of BI underscores the need for governance that extends beyond traditional data warehouses. BI Ops is that solution, ensuring that the consumption layer operates as a well-governed, efficient, and secure extension of an organization’s data strategy.

To learn more about BI Ops and the Datalogz Control Tower, schedule a demo at https://www.datalogz.io/book

About Datalogz

Datalogz is a fast-growing, culture-focused, venture-backed startup dedicated to building products that re-imagine an organization's Business Intelligence environments. Datalogz is creating the future of BI Ops and is on a mission to end BI and analytics sprawl. The team comprises elite data technology entrepreneurs and analytics leaders and is always looking to bring on talent that aligns with its vision, mission, and values.

Contacts

Tina Bhatia
Datalogz
+1-315-216-2203
Tina@datalogz.io

Contacts

Tina Bhatia
Datalogz
+1-315-216-2203
Tina@datalogz.io