Business Intelligence (BI) became part of the core focus of IT departments in the late 1980s. BI encompasses a wide range of practices, technologies, and applications. Together, they help companies collect, analyze, and present information that, in turn, helps leaders make informed business decisions.
Data Governance (DG), on the other hand, is a discipline. DG provides the strategy and structure necessary to manage data as an asset that can be transformed into meaningful information for the organization. In other words, DG is becoming a major point of focus for organizations that invest in BI and data science.
WHY ARE COMPANIES ADOPTING BI GOVERNANCE?
While DG fails to garner the same media attention as Big Data and similar concepts, it is worthy of discussion. Currently, the intersection of DG with BI is more visible, and there’s good reason. With the adoption of a DG strategy, companies realize that they can significantly improve the ROI (Return on Investment) of BI investments.
THE ESSENTIALS OF SUCCESSFUL DATA GOVERNANCE IMPLEMENTATION
As Forbes warned in their 2016 study titled, “Strong Data Governance Enables Business Intelligence,” DG is the key to successful BI implementation. It is essential that DG policies are both consistent and flexible. The study detailed some key barriers faced by companies trying to leverage BI and highlighted data inconsistency, slow adoption rates, and multiple ways to view data as the top challenges.
Forbes drew a critical conclusion, which matched the opinion of 75% of corporate executives: In order for Business Intelligence to advance and become mainstream, Data Governance must be enforced within organizations––especially those aiming to tackle BI at the enterprise level. After all, Data Governance is about treating and managing data as an asset. Therefore, it is able to impact (and improve) every aspect of the BI ecosystem, because it is all data and business-centric.
Data Governance is about treating and managing data as an asset
MOVING FORWARD WITH DATA GOVERNANCE
It all starts with data ownership, Data Quality (DQ), and Master Data Management (MDM). That’s where the first intersection occurs between BI and Data Governance. From there, companies are able to reap the benefits of an enhanced Data Strategy, which, in turn, enables them to get more from their BI initiatives.
In this sense, Business Intelligence champions Data Governance. Data Governance:
- Improves the capabilities of Business Intelligence by reducing Data Quality risks
- Lowers operational costs by eliminating duplicate data
- Lowers redundant data management tasks
- Reduces privacy and security risks by establishing and enforcing enterprise-wide data and information policies
- Achieves consensus with the business and technical metadata
- Aids enterprises in extracting information
- Yields a higher ROI from data dissemination
The combination of these factors creates an interesting ecosystem in which Data Governance and Business Intelligence can evolve together.