Info-Tech Research Group1 Effectively Manage Data Governance Convert the management of organizational data from a burden to a competitive advantage. Info-Tech's products and services combine actionable insight and relevant advice with ready-to-use tools and templates that cover the full spectrum of IT concerns.© Info-Tech Research Group

Info-Tech Research Group2 With advancements in technology such as big data, Cloud, and privacy laws, data governance has become a necessity for every organization. Introduction Leaders such as CIOs, Senior Executives, IT Managers, Data Owners, Data Stewards, Data Integration (DI) Specialists, Business Analysts, and Process Owners Business Subject Matter Experts who are involved in, overseeing, or are responsible for the launch of a Data Governance program. Provide an overview of data governance, and why it’s important to your organization. Assist in making the case, and securing buy-in for data governance. Identify data governance best practices, and the challenges associated with them. Provide guidance on how to implement data governance best practices for a successful launch. Demonstrate how data governance positively impacts existing IT services. This Research Is Designed For:This Research Will:

Info-Tech Research Group3 Executive Summary Make the Case for Executive Sponsorship: A data governance initiative can bring an organization many positive benefits including elements to help with value creation, mitigation of risk, and the reduction of operating costs. Some of the largest challenges associated with launching a data governance initiative are budget constraints, and a lack of stakeholder participation. Highlighting positive benefits in a business case will help overcome the challenges associated with launching the data governance program. Assess Readiness to Launch a Data Governance Program: Many organizations that fail at launching a data governance program, face staff resistance, data standardization difficulties, and have a lack of available stakeholders. To mitigate these challenges, assess your organization’s readiness to launch before the data governance program starts. Having best practices such as formal communication plans, data governance steering committees, and data owners in place will ensure that the launch of the data governance program is a success. Understand Data Governance and Why your Organization Should Invest in it: Data governance is a process that is essential to the management of organizational data, and affects many existing IT services including, but not limited to, the Cloud, business intelligence, and master data management. Although data governance initiatives have varying definitions specific to each organization and its business processes, almost all programs create policies and procedures that will affect enterprise data. Data governance is a must-have in order to keep organizational data clean, accurate, and usable.

Info-Tech Research Group4 Ensure that the organization has a basic understanding of data governance, and plan the process appropriately Data Governance is a strategic program that will help your organization control data by managing the people, processes, and technology needed to ensure that accurate and consistent data policies exist across varying lines of the business within your organization. Overall success of the data governance program will be seen when your organization begins to view data as a valuable asset. While some venture to explain data governance in a short description, these definitions are often vague and do not explain the component parts of data governance. Ultimately, data governance encompasses a variety of processes critical to the management of data. Defining these processes is different for every organization because they all have different data and applications that require management. However, organizations will find that its data governance programs have at least two things in common: 1.The power of decision making for policies and procedures that will affect enterprise data. 2.The maintenance of resources, and alignment with corporate strategies

Info-Tech Research Group5 If your organization’s MDM initiative is failing, it might be because a data governance program is not in place. Data governance is mandatory for the success of a Master Data Management (MDM) initiative To manage the organizational changes necessary for master data improvement, a data governance program is essential. Proactive data governance is critical to the success of the MDM initiative. An MDM program will involve business units such as marketing, finance, sales, and any other data driven areas within the organization. As MDM affects data processes, and applications spanning across organizational boundaries, data governance is essential to provide consistent data standards, and processes to be used by multiple data owners to create one version of the truth. Data governance provides a decision framework for negotiating MDM initiatives, and generating consensus in a way that aligns data management practices with business objectives. By finding solutions that respect established data stewardship practices, data governance empowers the business with a more consistent, and accurate view of core business entities. An MDM program will involve business units such as marketing, finance, sales, and any other data driven areas within the organization. As MDM affects data processes, and applications spanning across organizational boundaries, data governance is essential to provide consistent data standards, and processes to be used by multiple data owners to create one version of the truth. Data governance provides a decision framework for negotiating MDM initiatives, and generating consensus in a way that aligns data management practices with business objectives. By finding solutions that respect established data stewardship practices, data governance empowers the business with a more consistent, and accurate view of core business entities. A data governance program puts the MDM pieces together: For more information on the Master Data Management, please refer to Info-Tech’s set: Implement a Master Data Management Strategy Implement a Master Data Management Strategy

Info-Tech Research Group6 Data integration projects increase in value when organizational data quality is high Data integration prevents silos of information, and enables an enterprise-wide view of data. Any data integration solution must have the ability to provide accurate data at all times, and be able to maintain data consistency between lines-of-business. In order for data to be in the proper condition upon delivery, accurate integrations, including data synchronization and cleansing, must be performed on a regular basis. One of the problems with integration is that it can be very tactical in nature, sometimes neglecting that inconsistent, and duplicate data can exist in a variety of enterprise applications. Once this data is integrated, data quality issues become apparent. Data governance can help IT determine who is responsible for the data, so that data quality questions can be addressed to the business user who will know the correct answer. Data integration prevents silos of information, and enables an enterprise-wide view of data. Any data integration solution must have the ability to provide accurate data at all times, and be able to maintain data consistency between lines-of-business. In order for data to be in the proper condition upon delivery, accurate integrations, including data synchronization and cleansing, must be performed on a regular basis. One of the problems with integration is that it can be very tactical in nature, sometimes neglecting that inconsistent, and duplicate data can exist in a variety of enterprise applications. Once this data is integrated, data quality issues become apparent. Data governance can help IT determine who is responsible for the data, so that data quality questions can be addressed to the business user who will know the correct answer. “When we [did] the [data] conversation…in some instances, 30 percent of an organization’s [data] collection didn’t convert because it didn’t match the [data standards] rules.” - Robert Erhardt San Diego Zoo For more information on Data Integration Tools, please refer to Info-Tech’s set: Vendor Landscape Plus: DI Tools Vendor Landscape Plus: DI Tools Data Standards Data standards and definitions keep integration between enterprise wide databases simple

Info-Tech Research Group7 BI initiatives are only successful if data quality standards are high. A data governance program can increase the success of your organization’s Business Intelligence (BI) Solution Hit the BI bulls eye by building a data governance program “We had a lot of [business users] who were writing their own reports…and we put a stop to that. [Our data governance program helped us] standardize the queries and views for the data and [now] the reports that are run out of production are run through queries that database folks…have developed and tuned.” -George Neill Organic Valley BI uses your organizations data to build reports, and dashboards for business decision makers. With the emergence of self-serve BI, a lot of reports and queries are not under the control of IT anymore. As a result, it becomes less possible for IT to control, and manipulate inaccurate data. Data duplication, stale data, incomplete data, invalid data, and data conflicts can actually make reporting inaccurate. Although the problem is that all data quality issues affect BI, a few in specific are helped by the emergence of a data governance initiative. How BI is affected by bad data For more information on the Business Intelligence, please refer to Info-Tech’s set: Develop a BI Strategy Develop a BI Strategy

Info-Tech Research Group8 Pair your organization’s social media strategy with a data governance program Appropriate strategies to manage data inputted, and extracted from social media sites will mitigate the risks associated with social media exploration. Data Governance can help! Communication and training programs on the appropriate use of social media as a marketing tool to avoid the posting of potentially damaging material. Policies on what defined data can be extracted from social media sites to maintain reporting accuracy. Social media (like Big Data) is a form of unstructured data. Tapping into these websites can give your organization valuable insights on consumer opinions. Venturing into social media data is not without major cautions. A few concerns exist: The level of accuracy in reporting with such unstructured data. The worry associated with security. Potential leaks of sensitive, and damaging information. This could increase costs of litigation, and reputation management. For more information on social media, please refer to Info-Tech’s set: Implement a Social Media Program Implement a Social Media Program

Info-Tech Research Group9 Data Governance Survey Demographics Industry Country Revenue Full-time Employees IT Employees Department Job Title

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