We often think of the merits of business intelligence (BI) in terms of speed and accessibility, which is partially correct. The advanced platforms available today absolutely aim to reduce the time to insights and provide them to many users throughout an ecosystem.
However, it’s important to remember lightning-fast insights widely available to everyone mean nothing if those results are not verifiable and trustworthy. And widespread access without sufficient oversight can actually make companies vulnerable to a data breach or misuse.
The underlying factor here determining how accessible, secure, scalable, and successful an enterprise’s data endeavors are is BI governance — or the “processes and framework involved in managing data assets,” according to CIO.
Governance takes a bird’s eye view of strategy, usage, and outcomes. Whereas many data users only ever interact with it through the front-end interface — taking granular looks at metrics related to their duties — governance is the overarching custodian of the entire system as a whole.
As the CEO of ThoughtSpot notes, companies have long faced the constant challenge of “balancing standards and governance with speed and agility” when it comes to governed business intelligence. On a positive note, modern platforms address this challenge by prioritizing both enterprise-wide oversight for leaders and responsive user experiences for employees.
Whether you’re evaluating your current BI governance or searching for a new solution, keep these four key components in mind.
Key Components of BI Governance Today
Governance is a collection of practices, infrastructures, and rules to oversee data — which means there are a lot of moving parts.
#1 Leadership
Which stakeholders will take ownership over which aspects of data governance? This is the time to bring IT leaders and business leaders together to forge a workable partnership — one capable of balancing control with agility and security with user-friendliness.
#2 Granular Permissions
A huge part of governance is granting and restricting access to certain data points on an as-needed basis.
Administrators need the controls to do so individually and for security groups. This will minimize the chances of data falling into the wrong hands, while simultaneously democratizing data to users who need quick access.
#3 Data Lineage
The ability to trace data all the way back to its source ensures transparency and accuracy for everyone involved.
This ability to trace data lineage helps administrators reduce liability on their end in case they need to conduct an audit for any reason. It also helps users verify the origination of data insights so they can act upon them confidently and with full context.
#4 Evaluating Success
Additionally, governance entails measuring the success of enterprise BI efforts in terms of return on investment — and identifying areas ripe for improvement.
The exact metrics covered by these evaluations depend on the specific business goals tied to BI. The leaders in charge of governance are also responsible for examining metrics related to BI usage, like employee adoption rates.
Risks Associated with Weak BI Governance
As one expert writes for Information Week, potential risks of weak or non-existent BI governance include:
- Failure to comply with regulatory, security or privacy requirements
- Poor decision-making fueled by inaccurate or outdated data
- Multiple versions of the truth acting at odds with each other
- Inability to verify data sources and changes
- Issues with scalability and cybersecurity
In other words, poor governance can undermine the goals of a data strategy. Think of it as akin to the framework of a house. Skipping this step, or choosing inferior materials will lead to the entire structure tumbling down at the first gust of wind — if you’re even able to build it in the first place.
