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Document management includes records management. Managing records has special requirements. Records management includes the full lifecycle: from record creation or receipt through processing, distribution, organization, and retrieval, to disposition. Records can be physical (e.g., documents, memos, contracts, reports or microfiche); electronic (e.g., email content, attachments, and instant messaging); content on a website; documents on all types of media and hardware; and data captured in databases of all kinds. Hybrid records, such as aperture cards (paper record with a microfiche window imbedded with details or supporting material), combine formats. A Vital Record is type a record required to resume an organization’s operations the event of a disaster.
Trustworthy records are important not only for record keeping but also for regulatory compliance. Having signatures on the record contributes to a record’s integrity. Other integrity actions include verification of the event (i.e., witnessing in real time) and double-checking the information after the event.
Well-prepared records have characteristics such as:
Structure: The appearance and arrangement of a record’s content should be clear. They should be recorded on the correct forms or templates. Content should be legible, terminology should be used consistently.
Many records exist in both electronic and paper formats. Records Management requires the organization to know which copy (electronic or paper) is the official ‘copy of record’ to meet record keeping obligations. Once the copy of record is determined, the other copy can be safely destroyed.
Exciting updates are coming to the Certified Data Management Professional (CDMP) certification exams starting in October 2024. The exams will now cover the DAMA-DMBOK2 Revised Edition, an updated and improved version of the Data Management Body of Knowledge. This revised edition addresses known inconsistencies and inaccuracies, making it a more reliable and comprehensive resource for data management professionals. For those preparing for the CDMP certification, it's important to note that this revised edition will be the new reference material.
The DAMA-DMBOK2 Revised Edition has been created to ensure the content remains relevant and accurate for data management practitioners. DAMA International embarked on this update to improve upon the previous version, incorporating feedback from members and volunteers. The revised edition aims to provide a more consistent and precise framework, making it easier for professionals to understand and apply the principles of data management.
Key improvements in the DAMA-DMBOK2 Revised Edition include standardized terminology and acronyms, corrections of typos and errors, improvements to context diagrams, and enhancements to the Data Quality chapter. These updates ensure the content is not only accurate but also easier to comprehend and apply. The revised edition is available for purchase (and discounted for Professional Members) through DAMA-RMC at DMBoK.
For those currently preparing for the CDMP certification, you can continue using the DAMA-DMBOK 2nd Edition until October 2024. After that date, the revised edition will be the authoritative resource.
We encourage you to join one of our upcoming 30-minute informational sessions on the CDMP Study Group during the week of August 26th. You can also enroll in our 12-week virtual study program which will start in September. To enroll in the study program, you must be a Professional Member anyone can attend the informational sessions. We also have a self-paced study option available.
Information session links:
DAMA-RMC CDMP Information Session 1 - ZOOM LINK
DAMA-RMC CDMP Information Session 1 - ADD TO CALENDAR
DAMA-RMC CDMP Information Session 2 - ZOOM LINK
DAMA-RMC CDMP Information Session 2 - ADD TO CALENDAR
For more information, please contact jhorner@dama-rockymountainchapter.org or visit the CDMP Webpage. Additionally, please update your DAMA RMC profile to indicate your interest in the CDMP so we can keep you update to date on all things DMBoK and CDMP.
We are pleased to invite you to a concise and informative session on the Certified Data Management Professional (CDMP) certification. This 30-minute meeting will cover essential topics and recent updates, ensuring you are well-prepared for the certification process.
The study sessions will run from the week of September 9th - December (Meeting time and day of week TBD tentatively planning for Wednesday at 6pm)
At the conclusion we will host to ½ day virtual prep reviews and host the annual pay if you pass event which allows attendees to only pay the exam fee if they pass.
**Agenda:**
1. **CDMP Exam Overview**
2. **Study Session Logistics**
3. **New Changes to DMBOK / CDMP Exams**
4. **General Q&A**
**Date and Time:**
We are offering two 30 minute information sessions:
Please RSVP to ProfessionalDevelopmentVP@damarmc.org as soon as possible to confirm your attendance. We look forward to your participation and engaging discussions.
Document and Content Management entails controlling the capture, storage, access, and use of data and information stored outside relational databases. Its focus is on maintaining the integrity of and enabling access to documents and other unstructured or semi-structured information which makes it roughly equivalent to data operations management for relational databases. However, it also has strategic drivers. In many organizations, unstructured data has a direct relationship to structured data. Management decisions about such content should be applied consistently. In addition, as are other types of data, documents and unstructured content are expected to be secure and of high quality. Ensuring security and quality requires governance, reliable architecture, and well-managed Metadata.
The primary business drivers for document and content management include regulatory compliance, the ability to respond to litigation and e-discovery requests, and business continuity requirements. Good records management can also help organizations become more efficient. Well-organized, searchable websites that result from effective management of ontologies and other structures that facilitate searching help improve customer and employee satisfaction.
Laws and regulations require that organizations maintain records of certain kinds of activities. Most organizations also have policies, standards, and best practices for record keeping. Records include both paper documents and electronically stored information (ESI). Good records management is necessary for business continuity. It also enables an organization to respond in the case of litigation.
E-discovery is the process of finding electronic records that might serve as evidence in a legal action. As the technology for creating, storing, and using data has developed, the volume of ESI has increased exponentially. Some of this data will undoubtedly end up in litigation or regulatory requests.
The ability of an organization to respond to an e-discovery request depends on how proactively it has managed records such as email, chats, websites, and electronic documents, as well as raw application data and Metadata. Big Data has become a driver for more efficient e-discovery, records retention, and strong information governance.
Gaining efficiencies is a driver for improving document management. Technological advances in document management are helping organizations streamline processes, manage workflow, eliminate repetitive manual tasks, and enable collaboration. These technologies have the additional benefits of enabling people to locate, access, and share documents more quickly. They can also prevent documents from being lost. This is very important for e-discovery. Money is also saved by freeing up file cabinet space and reducing document handling costs.
An Enterprise Service Bus (ESB) is a system that acts as an intermediary between systems, passing messages between them. Applications can send and receive messages or files using the ESB, and are encapsulated from other processes existing on the ESB. An example of loose coupling, the ESB acts as the service between the applications.
Coupling describes the degree to which two systems are entwined. Two systems that are tightly coupled usually have a synchronous interface, where one system waits for a response from the other. Tight coupling represents a riskier operation: if one system is unavailable then they are both effectively unavailable, and the business continuity plan for both have to be the same.
Where possible, loose coupling is a preferred interface design, where data is passed between systems without waiting for a response and one system may be unavailable without causing the other to be unavailable. Loose coupling can be implemented using various techniques with services, APIs, or message queues. This figure illustrates a possible loose coupling design.
Service Oriented Architecture using an Enterprise Service Bus is an example of a loosely coupled data interaction design pattern.
Where the systems are loosely coupled, replacement of systems in the application inventory can theoretically be performed without rewriting the systems with which they interact, because the interaction points are well-defined.
The load step of ETL is physically storing or presenting the result of the transformations in the target system.
Depending on the transformations performed, the target system’s purpose, and the intended use, the data may need further processing to be integrated with other data, or it may be in a final form, ready to present to consumers.
If the target system has more transformation capability than either the source or an intermediary application system, the order of processes may be switched to ELT – Extract, Load, and Transform. ELT allows transformations to occur after the load to the target system, often as part of the process. ELT allows source data to be instantiated on the target system as raw data, which can be useful for other processes. This is common in Big Data environments where ELT loads the data lake.
July 2024 Newsletter.pdf
Data Integration and Interoperability (DII) describes processes related to the movement and consolidation of data within and between data stores, applications and organizations. Integration consolidates data into consistent forms, either physical or virtual. Data Interoperability is the ability for multiple systems to communicate. DII solutions enable basic data management functions on which most organizations depend:
DII is dependent on these other areas of data management:
Data Integration and Interoperability is critical to Data Warehousing and Business Intelligence, as well as Reference Data and Master Data Management, because all of these focus on transforming and integrating data from source systems to consolidated data hubs and from hubs to the target systems where it can be delivered to data consumers, both system and human.
Data Integration and Interoperability is central to the emerging area of Big Data management. Big Data seeks to integrate various types of data, including data structured and stored in databases, unstructured text data in documents or files, other types of unstructured data such as audio, video, and streaming data. This integrated data can be mined, used to develop predictive models, and deployed in operational intelligence activities.
Security risks include elements that can compromise a network and/or database. The first step in identifying risk is identifying where sensitive data is stored, and what protections are required for that data. Evaluate each system for the following:
Document the findings, as they create a baseline for future evaluations. This documentation may also be a requirement for privacy compliance, such as in the European Union. Gaps must be remediated through improved security processes supported by technology. The impact of improvements should be measured and monitored to ensure risks are mitigated.
In larger organizations, white-hat hackers may be hired to assess vulnerabilities. A white hat exercise can be used as proof of an organization’s impenetrability, which can be used in publicity for market reputation.
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