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

Part 3 – SAP Information Steward Metadata Management and Metapedia

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. Part 2 provided an overview of how SAP Information Steward can help you get started with a Data Governance program and detailed the Data Insight module of the tool. In Part 3, we will now turns towards the Metadata Management and Metapedia module of Information Steward to show how they can help in other areas of Data Governance.

Common Concerns
The following questions and comments coming from within an organization are ones that we hear often:

  • How were the values on this report calculated?
  • Where is this data being sourced from?
  • I can’t trust this report; some values look right but others seem way off base
  • What definition of Customer do you mean here? We define it differently
  • We view this set of material as Finished Goods, but some other plants view them as semi-finished. We sell these but that other plant is responsible for putting these materials into a large assembly

Mostly these conversations boil down to two main problems:

  1. Business users are completely blind to how the data they see in a report has been processed.  They don’t know where it came from or how it was calculated, and therefore they don’t know if it can be trusted.
  2. Common terms are being lost in translation across the enterprise. One group defines a term one way, and the rest of the company defines it another. As a result, communication has become challenging as conversations devolve into how to properly define certain terms, rather than solve the actual business problem that has come up.

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rich

About Rich Hauser
Rich is a Manager in the Data & Analytics practice of Protiviti, specializing in Enterprise Information Management.  He has delivered customized Data Governance and SAP BusinessObjects solutions for customers of all sizes across a variety of industries.  With Protiviti, Rich utilizes SAP Data Services and SAP Information Steward.

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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Richard HauserAbout 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.

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

Part 1 – Data Governance Defined

Data Governance: You’ve probably heard the buzz about this topic that is becoming a larger part of many IT conversations. But similar to the vague term “Big Data” these days, just what exactly is data governance? Is it a piece of software that one can simply buy off the shelf? And what are the benefits that one can expect to receive by implementing it?

Chances are that if you are reading this article you have some kind of data issue in your organization, and you are not alone. Data problems are costly in a variety of ways. For example, they can result in lost of potential sales due to incomplete customer demographic data. Or, they can cause an unnecessary expense, such as a sales return that resulted from an undeliverable address. Worst of all, a data problem can become systemic if the error is propagated throughout the enterprise via normal integration channels. A Data Governance program will be your strategy for finding data error, repairing these errors, and preventing them from occurring in the future. But more importantly, it will be an overarching set of policies and information management principles that apply to your entire enterprise.

It’s helpful to start by defining Data Governance. A quick internet search will retrieve a large number of definitions that all sound relatively familiar, but the common themes that run throughout all of them are:

  • A data governance strategy is a set of policies and procedures that manage the quality of information assets
  • Data governance is a program to manage information. It is an ongoing process that will change over time. It is not a one-time project (wishful thinking)
  • Data is an enterprise asset. Like any other asset, it requires an investment in order to be maintained and improved

Data Governance, in summary, is your organization’s management strategy to meet 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.

To download PDF and Continue Reading…

Richard HauserAbout 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.