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Управление данными (Data Governance, DG) на все случаи жизни

23 мая 2013 Для компаний, избравших путь возведения бизнеса на фундаменте управления мастер-данными (Master Data Management, MDM), главным фактором успешной реализации проекта является активное соответствие принципам и практике управления данными (Data Governance, DG). Внедряя решения MDM чрезвычайно важно учитывать 3 основных аспекта: управление критичными элементами данных, постановка стандартов и правил использования информации и мониторинг исполнения установленных процедур. Об этом и многом другом читайте брошюру компании SAS на английском языке у нас на сайте.
As a result of both external pressures, such as compliance, and internal pressures triggered by aggressive enterprise information management programs, there is growing interest on behalf of both data management professionals and senior business managers to understand the motivations, mechanics, virtues and ongoing operations of instituting data governance within an organization. The objective of data governance is predicated on the desire to assess and manage the many different kinds of risks that lurk hidden within the enterprise information portfolio. And while many data governance activities are triggered by a concern about regulatory compliance, the definition, oversight and adherence to information policies and procedures can create additional value across the enterprise.

One of the major values of a master data management (MDM) program is that, because it is an enterprise initiative, a successful initiative will be accompanied by the integration of a data governance program. As more lines of business integrate with core master data object repositories, there must be some assurance of adherence to the rules that govern participation. Yet while MDM success relies on data governance, a governance program can be applied across different operational domains, providing economies of scale for enterprisewide deployment.

There are many different perceptions of what is meant by the term “data governance.” Data governance is expected to address issues of data stewardship, ownership, compliance, privacy, data risks, data sensitivity, metadata management, MDM and even data security. What is the common denominator? Each of these issues revolves around ways that technical data management is integrated with management oversight and organizational observance of different kinds of information policies.

Whether we are discussing data sensitivity or financial reporting, the goal is to integrate the business policy requirements as part of the metadata employed in automating the collection and reporting of conformance to those policies. Especially in an age where noncompliance with external reporting requirements (e.g., Sarbanes-Oxley) can result in fines and prison sentences, the level of sensitivity to governance of information management will only continue to grow.

For companies undertaking MDM, a hallmark of successful implementations will be the reliance and integration of data governance throughout the initiative. There are three important aspects of data governance for MDM and beyond:
  • Managing critical data elements – Ensuring consensus in identifying data elements associated with common business terminology, researching their authoritative sources, agreeing on their definitions, and managing them within the master repository as the enterprise source of truth.

  • Setting information policies and data rules – Determining the critical business policies that relate to data, and devising the information policies that embody the specification of management objectives associated with data governance, whether they are related to management of risk or general data oversight.

  • Enforcing accountability – Empowering the right individuals in the organization to enforce well-defined governance policies and to establish the underlying organizational structure to make it possible by defining a management structure to oversee the execution of the governance framework along with the compensation model that rewards that execution.

Keeping these ideas in mind during the development of the MDM program will ensure that the master data repository doesn’t become relegated to the scrapheap of misfired enterprise information management initiatives. Rather, developing a strong enterprise data governance program will benefit the MDM program as well as strengthen the ability to manage all enterprise information activities.

Source:  sas.com
Data Governance for Master Data Management and BeyondБрошюра компании SAS
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