Making SAP Information Steward a Key Part of Your Data Governance Strategy – Part 2

SAP Information Steward Overview and Data Insight Review

Part 1 in our series on Data Governance defined the concept of Data Governance and gave suggestions on how to go about implementing an initial program at a corporate level. The definition that we use is:

Data Governance is your organization’s management strategy to meet the data quality needs of final data users and consumers. It verifies that data meets your organization’s security requirements and ensures that it complies with any regulatory laws. It is the marriage of data quality, data management, and risk management principles. It is implemented via corporate policies, procedures, controls, and software.

Now that we know what it is and how to start a program, let’s discuss how SAP Information Steward can fit into a data governance initiative. SAP Information Steward is an enterprise-level data quality solution that allows you to profile data, perform impact and lineage analysis, construct a corporate dictionary, and define custom cleansing rules for incoming data. Each of these functions is performed by a different module of the software, which are: Data Insight, Metadata Management, Metapedia, and Cleansing Package Builder. Your initial data governance goal will determine which of these to utilize first. Data Insight is the data profiling tool and data quality monitor. Metadata Management is the impact and lineage analysis tool that can determine where a piece of data is used through the enterprise and what may affect the data. Metapedia is the corporate dictionary where business terms can be defined for the use throughout the organization. Finally, Cleansing Package Builder is the data quality tool that allows data area experts to define transformations and cleansing rules in order to standardize a particular set of data. This post will cover Data Insight in detail, while subsequent posts will breakdown the other modules of the Information Steward tool.

Data Insight allows you to profile data from a range of sources that include standard relational databases, SAP HANA, SAP ERP, SAP Master Data Services, and even flat files. Data profiling is simply the process of analyzing the data that exists in a source and collecting statistics from that analysis. It answers the question: “What does my data source actually contain?”, as there is often a disparity between what a source should contain and what it contains in reality. Data profiling is the starting point for data integration tasks, data warehouse projects, and many data governance programs. Without this starting point, one cannot properly calculate true measurements of the data quality improvements that are achieved through a data governance or data quality program.

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About Rich Hauser
Rich is a senior Business Intelligence consultant specializing in Enterprise Information Management. He has delivered customized SAP BusinessObjects solutions for customers of all sizes across a variety of industries. With Decision First Technologies, Rich utilizes SAP Data Services and SAP Information Steward.