by Angela Guess
Sunil Soares of IBM Business Magazine recently laid out a framework for Big Data Governance. He writes, “Big data governance is part of a broader information governance program that formulates policy relating to the optimization, privacy, and monetization of big data by aligning the objectives of multiple functions. However, big data governance is meaningless without an understanding of the underlying data types. This article provides a framework for big data governance. As shown in Figure 1 (above), the framework consists of three dimensions.”
Those dimensions are: “(1) Big data types. Big data can be classified into five types: web and social media, machine-to-machine (M2M), big transaction data, biometrics, and human-generated. (2) Information governance disciplines. The traditional disciplines of information governance—organization, metadata, privacy, data quality, business process integration, master data integration, and information lifecycle management—also apply to big data. For example, sensor data needs to be integrated into a preventive maintenance process. However, if sensors from different machines generate inconsistent event codes, it will be difficult to streamline the maintenance process. (3) Industries and functions. Big data analytics are driven by use cases that are specific to a given industry or function such as marketing, customer service, information security, or information technology.”
photo credit: IBM
