Governed Data Discovery is one of the trending buzzword of 2014.
The term made its debut in Gartner’s 2014 Magic Quadrant Report. Gartner first popularized the term data discovery and now is adding governed to the term.
While it forms a great acronym, GDD, the clear question here is what does Governed Data Discovery actually mean?
Way Back When
Traditionally, a company’s Business Intelligence and Analytics was handled by a handful of trained, tech-savvy business professionals.
The mega-vendors were the ones who provided powerful, scalable, and secure platforms for the highly skilled IT professionals and business analysts to understand and operate. However, a large gap formed between the people who knew and understood the business problems and the people who could build the technology and methods to solve them.
Data discovery solutions made their entrée into society as they were easy-to-understand and operate, as well as capable of delivering immediate, high-value business impact. With data discovery solutions, businessmen who knew the questions could easily extract the needed information to help them gain insights and take appropriate actions to improve their business’s performance.
While the Business Analytics data discovery tools are easy to set up quickly, over time the needs of business expands as well as new content, users, and data are added in the backend. Many of these data discovery tools are not built to manage these changes, so organizations are faced with a data fissure that can be expensive, time-consuming, and extremely frustrating to resolve.
The GDD Solution
“Governed data discovery – the ability to meet the dual demands of enterprise IT and business users” asserts Gartner. There is a critical space in the market for a Governed Data Discovery tool as companies now need to look into replacing their disparate systems for managing their Business Intelligence. To be a true Governed Data Discovery solution, the BI platform needs to offer four main components:
1) Self-Service Central Control
A built-in, self-service, and centralized administrative toolset to govern an organization’s BI. This robust and extensive administrative backend is required to provide the capability for managing every user’s experience, security, content, and data access from a singular, intuitive interface.
2) Data Governance
For one version of truth for data, it is important that data models or mashups not be isolated on a desktop machine. The data needs to remain centralized – easily shareable, securable, and consistently updated.
A Data Lineage capability that tracks the life-cycle of the model is also highly recommended. This allows you to see the data model’s different versions, over time and across different platforms. By tracking the implementation of how the data models (and elements) are being used downstream, one can gain insights into resource allocation and optimization.
3) The Content Lifecycle
Content repository in a centralized, shared paradigm – that also tracks the content life-cycle is needed. This ensures content integrity and makes it easy to find and implement any changes or upgrades. Content can be then shared by groups or kept private.
4) Secure & Protected
A strong security model is vital so that the data is not only secure from the external populace, but also kept confidential internally. Specific capabilities include: Integrated Security, Role Based Security, Content Security, Data Security, Multi-Tenancy, Social Networking Security, User Profiles, User Licensing, Auto Provisioning, and Authentication.
These are the four overarching components that contribute to a powerful Governed Data Discovery platform. There are many more elements within each topic to discuss and further explore.
About the Author: Ofer Avnery is the VP Product Marketing at Pyramid Analytics. Ofer uses his wide range of product knowledge to help inform and educate business users about the scope of BI Office, the premier BI platform for the enterprise — with full Governed Data Discovery capabilities.