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**

• Description of the CDMP certification levels and exam structure.
• Key topics and study resources.

2. **Study Session Logistics**

• Registration, scheduling, and common logistical questions
• Format

3. **New Changes to DMBOK / CDMP Exams**

• Overview of recent updates to the Data Management Body of Knowledge (DMBOK) and changes in CDMP exam content.

4. **General Q&A**

**Date and Time:**

We are offering two 30 minute information sessions:

• Tuesday, August 27 at 6pm MST 

• • DAMA-RMC CDMP Information Session 1 - ZOOM LINK

  • DAMA-RMC CDMP Information Session 1 - ADD TO CALENDAR

• Wednesday, August 28 at 12:30 MST

• • DAMA-RMC CDMP Information Session 2 - ZOOM LINK

  • DAMA-RMC CDMP Information Session 2 - ADD TO CALENDAR

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: Data migration and conversion Data consolidation into hub or marts Integration of vendor packages into an organization's application portfolio Data sharing between applications and across organizations Distributing data across data stores and data centers Archiving data Managing data interfaces Obtaining and ingesting external data Integrating structured and unstructured data Providing operational intelligence and management decision support DII is dependent on these other areas of data management: Data Governance: For governing the transformation rules and message structures Data Architecture: For designing solutions Data Security: For ensuring solutions appropriately protect the security of data, whether it is persistent, virtual, or in motion between applications and organizations Metadata: For tracking the technical inventory of data (persistent, virtual, and in motion), the business rules for transforming the data, and the operational history and lineage of the data Data Storage and Operations: For managing the physical instantiation of the solutions Data Modeling and Design: For designing the data structures including physical persistence in databases, virtual data structures, and messages passing information between applications and organizations 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:

• The sensitivity of the data stored or in transit
• The requirements to protect that data, and
• The current security protections in place

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.

Short for de-militarized zone, a is an area on the edge or perimeter of an organization, with a firewall between it and the organization. A DMZ environment will always have a firewall between it and the internet (see this figure). DMZ environments are used to pass or temporarily store data moving between organizations.

The Doyle Group is an IT Consulting and Placement firm known for their strategic talent solutions and consultative approach. 

With deep roots in the Denver community, the Doyle Group serves clients locally and across the United States. Bringing over 50 years of collective industry experience, they have built a reputation for delivering solutions tailored to meet each client's unique needs. Their mission is to forge meaningful partnerships with clients seeking top technology talent and to support highly skilled candidates in finding their next career opportunity. By providing personalized guidance and insights, The Doyle Group helps clients secure professionals who seamlessly integrate into their teams and culture and drive long-term success. 

The Doyle Group understands the importance of exceptional talent in today's dynamic technological landscape. Their dedicated team goes beyond matching candidates with opportunities; they provide ongoing support to both clients and consultants, fostering relationships that thrive over time. They offer a range of services, including project-based, contract-to-hire, direct placement, executive search, offshore, and nearshore solutions. Their consultants specialize in an array of areas, including Digital Solutions, Project and Program Management, Software Development, Data & Analytics, and more. 

Whether a business is seeking strategic technology talent or a professional is looking for their next career move, The Doyle Group stands as a reliable partner, committed to delivering lasting value through their expertise and customized services. 

Thank you to The Doyle Group for sponsoring our July 2024 meeting!