Enterprise Data Management (EDM) refers to the data quality in an organization to secure, integrate and disseminate data from a variety of data streams. This includes the organization's ability to securely and accurately transfer data between applications, subsidiaries, partners and processes.
Effective EDM involves the skillful management of business intelligence by employees who are skilled in handling data themselves, and that they adhere to established protocols for handling and storage. The following describes areas of EDM, including components, roles and responsibilities of personnel involved, processes, and benefits.
Enterprise Data Management Components
In general, enterprise data management uses the following components-
Data Integration This part of the process involves consolidating structured data across an organization's disparate data into a central locale. This is critical to ensure that the disparate data is accessible. Types of data integration include virtualization, consolidation, propagation and federation.
Master Data Management Master Data Management (MDM) uses some data integration methods, but there is a distinct difference between the two. While MDM is about reconciling business data from different sources and putting it into a usable form, data integration is simply about consolidating data and making it accessible.
Master data management has similarities with enterprise data management, but the latter is more comprehensive in its scope; it is listed here as a component of enterprise data management. Master data management is structured data from master data records that describe the essentials for processes or a data strategy.
Data Security With more and more data breaches and high profile hacking attacks in the press these days, it should come as no surprise that security is a critical and evolving component of data-related strategies. Data security addresses the organization's policies and procedures to ensure that data is protected from aggregation to dissemination, at all points between the organization, including storage. This includes not only protecting data from damaging incidents (theft and leaks), but also from destruction or corruption.
Data Governance This addresses the policies and processes used to ensure the integrity, quality and security of data. It includes the standards related to governance authority, enforcement and accountability. It is the playbook or guide for how data is handled globally and who has authority in this area.
Enterprise Data Management Roles and Responsibilities
In most cases, enterprise data managers are IT project managers, IT administrators, or database administrators for a company. Although they may not be involved in the overall business process, they will oversee the process of managing the company's entire data and data master.
Because these parties are familiar with all technical aspects of data quality management, aggregation, transmission, and storage, they will be in the best position to identify weak links in processes and ensure that data is minimally vulnerable to breaches, leaks, and analytical errors. Data management policies are typically overseen by the chief data officer (CDO) or chief technical officer (CTO), the decision makers who can approve policies related to data management.
Benefits of enterprise data management
How do companies manage enterprise data? It may be surprising, but according to Oracle, [you] do it through conversations, phone calls, spreadsheets and email. For example, if a department head wants to add another cost center, or if management wants to move facilities from human resources to finance, the business decision must first be approved by all relevant decision makers.
All of this and similar inefficient transactions take time. Unfortunately, the manual data management of collecting past and new data is prone to errors and lack of visibility and traceability of data. As changes are made manually, often the end result is many people making many mistakes with many business critical data files that go undetected due to lack of visibility or traceability in the process. This is compounded by the sheer number of changes taking place in organizations today (Oracle).
However, when an organization prioritizes data management, it ensures that its data is secure throughout the cycle and available when users need access to it. Finally, a well-regulated data lineage allows managers and decision makers to quickly identify data dependencies and understand who is using data sources.
Enterprise Data Management Process and Practices
The data audit is usually the first step in implementing data management. The person responsible for data management will record the data generated, used or deleted during a particular process. Once the data has been curated in this way, it is then presented in a standardized format.
Defining the outcomes is critical to helping the organization determine the desired outcome of implementing enterprise data management. Goals and end objectives should be identified, as well as what is outside the scope of mandates or objectives. Finally, criteria for measuring success should be established.
It is important that data management and data governance projects be planned regularly to keep pace with administrator and staff changes, as well as hardware and software changes or upgrades. The IT manager (or other responsible party) will be familiar with these aspects and integrate maintenance protocols in line with the overall data management strategy.
Finally, publishing documents in shared locations will make data accessible to appropriate (authorized) personnel and ensure that they are properly informed of content, changes, and updates to procedures. This ensures transparency for all stakeholders, increases confidence in the strategy, and promotes a high level of efficiency.
As companies grow and evolve, the number and complexity of systems in use increases. Therefore, it is important that the people involved in EDM always have the available methods and technologies for managing master data. Understanding the nuances of EDM may not be for everyone, but with the right tools, knowledge and commitment, any organization can enjoy a successful, smooth EDM implementation.
Effective EDM involves the skillful management of business intelligence by employees who are skilled in handling data themselves, and that they adhere to established protocols for handling and storage. The following describes areas of EDM, including components, roles and responsibilities of personnel involved, processes, and benefits.
Enterprise Data Management Components
In general, enterprise data management uses the following components-
Data Integration This part of the process involves consolidating structured data across an organization's disparate data into a central locale. This is critical to ensure that the disparate data is accessible. Types of data integration include virtualization, consolidation, propagation and federation.
Master Data Management Master Data Management (MDM) uses some data integration methods, but there is a distinct difference between the two. While MDM is about reconciling business data from different sources and putting it into a usable form, data integration is simply about consolidating data and making it accessible.
Master data management has similarities with enterprise data management, but the latter is more comprehensive in its scope; it is listed here as a component of enterprise data management. Master data management is structured data from master data records that describe the essentials for processes or a data strategy.
Data Security With more and more data breaches and high profile hacking attacks in the press these days, it should come as no surprise that security is a critical and evolving component of data-related strategies. Data security addresses the organization's policies and procedures to ensure that data is protected from aggregation to dissemination, at all points between the organization, including storage. This includes not only protecting data from damaging incidents (theft and leaks), but also from destruction or corruption.
Data Governance This addresses the policies and processes used to ensure the integrity, quality and security of data. It includes the standards related to governance authority, enforcement and accountability. It is the playbook or guide for how data is handled globally and who has authority in this area.
Enterprise Data Management Roles and Responsibilities
In most cases, enterprise data managers are IT project managers, IT administrators, or database administrators for a company. Although they may not be involved in the overall business process, they will oversee the process of managing the company's entire data and data master.
Because these parties are familiar with all technical aspects of data quality management, aggregation, transmission, and storage, they will be in the best position to identify weak links in processes and ensure that data is minimally vulnerable to breaches, leaks, and analytical errors. Data management policies are typically overseen by the chief data officer (CDO) or chief technical officer (CTO), the decision makers who can approve policies related to data management.
Benefits of enterprise data management
How do companies manage enterprise data? It may be surprising, but according to Oracle, [you] do it through conversations, phone calls, spreadsheets and email. For example, if a department head wants to add another cost center, or if management wants to move facilities from human resources to finance, the business decision must first be approved by all relevant decision makers.
All of this and similar inefficient transactions take time. Unfortunately, the manual data management of collecting past and new data is prone to errors and lack of visibility and traceability of data. As changes are made manually, often the end result is many people making many mistakes with many business critical data files that go undetected due to lack of visibility or traceability in the process. This is compounded by the sheer number of changes taking place in organizations today (Oracle).
However, when an organization prioritizes data management, it ensures that its data is secure throughout the cycle and available when users need access to it. Finally, a well-regulated data lineage allows managers and decision makers to quickly identify data dependencies and understand who is using data sources.
Enterprise Data Management Process and Practices
The data audit is usually the first step in implementing data management. The person responsible for data management will record the data generated, used or deleted during a particular process. Once the data has been curated in this way, it is then presented in a standardized format.
Defining the outcomes is critical to helping the organization determine the desired outcome of implementing enterprise data management. Goals and end objectives should be identified, as well as what is outside the scope of mandates or objectives. Finally, criteria for measuring success should be established.
It is important that data management and data governance projects be planned regularly to keep pace with administrator and staff changes, as well as hardware and software changes or upgrades. The IT manager (or other responsible party) will be familiar with these aspects and integrate maintenance protocols in line with the overall data management strategy.
Finally, publishing documents in shared locations will make data accessible to appropriate (authorized) personnel and ensure that they are properly informed of content, changes, and updates to procedures. This ensures transparency for all stakeholders, increases confidence in the strategy, and promotes a high level of efficiency.
As companies grow and evolve, the number and complexity of systems in use increases. Therefore, it is important that the people involved in EDM always have the available methods and technologies for managing master data. Understanding the nuances of EDM may not be for everyone, but with the right tools, knowledge and commitment, any organization can enjoy a successful, smooth EDM implementation.