We currently offer two formats of this seminar, depending on the situation. On our homepage and at each seminar, icons and text clearly indicate which format is scheduled. If there is a choice for online attendance or live attendance, you can indicate this on the registration form. You cannot deviate from this choice (online or live) without prior consent due to reserved seats, lunch and the price difference in registration fees.

1. Three full days on location. The costs for participating in the three-day seminar at our venue amount to € 1935,- per person if you register at least 30 days before the start and after that € 2150,- (excl. VAT)*. Course proceedings, lunch and coffee are included. Depending on COVID-19 restrictions and possibly online attendees, a live video stream for online participants will also be provided from the classroom (format 2 below).
2. Three full days online. If you participate online in the hybrid format of the three-day workshop, the costs are € 1755,- per person if you register at least 30 days before the start and after that € 1950,- (excl. VAT)*. In order to provide the live video stream in the hybrid format, we require a minimum of six online attendees.

Members of DAMA NL or Intl. are eligible for 5 percent discount on the registration fee.

The Data Management Fundamentals examination costs € 311 and if you check the box on our registration form at least two weeks in advance, it will be added to the invoice for the course. You can also purchase the exam directly at CDMP and full details of the CDMP examinations, levels, fees and support are available at https://cdmp.info/.

In completing your registration form you declare that you agree with our Terms and Conditions.

*) All pricing is VAT-excluded and EU VAT regulation stipulates that if you attend an event on-premise in The Netherlands, we are required to include local VAT. In case of discrepancy in registration fee between the website and the PDF brochure, the information on this page of the website always prevails.

Extra discounts
Discounts are available for group bookings of two or more delegates representing the same organization made at the same time. Ten percent off for the second and third delegate and fifteen percent off for all delegates when registering four or more delegates (all delegates must be listed on the same invoice).
This cannot be used in conjunction with other discounts.

Payment
Full payment is due prior to the event. An invoice will be sent to you containing our full bank details including BIC and IBAN. Your payment should always include the invoice number as well as the name of your company and the delegate name.
Payment by credit card is also available. Please mention this in the Comment-field upon registration and find further instructions for credit card payment on our customer service page.

The course starts at 09.30 am and ends at 5 pm. Registration commences at 08.30 am.

[IF ONLINE FORMAT] We will send the course materials and meeting instructions well in advance as well as the invitation with hyperlink to join us online. The online meeting will be available at least one half hour earlier so please log in timely in order to check your sound and video settings beforehand.

Course Outline

Introduction to Data Management, DMBoK & overview of CDMP certification:   

• What is Data Management, the drivers and issues if it goes wrong.
• What is the DMBoK, its intended purpose and audience of the DMBoK.
• What are the disciplines of Data Management in the DMBoK
• Changes in DMBoK 2., and the relationship of the DMBoK with other frameworks (TOGAF / COBIT etc.).
• The DAMA CDMP professional certification overview and CDMP exam coverage by DMBoK 2 section, the different levels and how can you progress through them.

Data Governance

• What is Data Governance and why Data Governance is at the heart of successful Information Management.
• A typical Data Governance reference model including Data Governance roles and responsibilities.
• Organisation structures and types of Operating models to support Data Governance.
• Principles for Data Governance and how to get started with Data Governance.
• The role of the Data Governance Office (DGO) and its relationship with the PMO.
• Data ethics & sampling considerations.

Data Quality Management

• The different facets of Data Quality, and why Validity is often confused with Quality
• The Dimensions of Data Quality.
• The policies, procedures, metrics, technology and resources for ensuring Data Quality is measured and ultimately continually improved.
• A Data Quality reference model & how to apply it.
• Root cause analysis & the “5-whys” approach
• Capabilities & functionality of tools to support Data Quality management.
• Data Quality measures – guidelines for their creation & monitoring.
• Common myths & pitfalls about Data Quality management & how to avoid them.

Master & Reference Data Management

• The differences between Reference & Master Data.
• Identification and management of Master Data across the enterprise.
• 4 generic Master Data Management architectures & their suitability in different cases.
• A Master Data Management maturity assessment to consider business procedures for Master Data Management and the provision and appropriateness of Master Data Management solutions per major data subject area.
• How to incrementally implement Master Data Management to align with business priorities.
• Genres of Master Data Management solutions & common pitfalls if you select the wrong type;
• Different approaches for Master Data Management implementation & why you must be careful in the approach selected;
• The essential relationship between Master Data Management, Data Quality and Data Governance
• The under looked but critical aspect of Reference Data Management

Data Warehousing & BI Management & Big Data Analytics

• What is a Data Warehouse & why are they used.
• Provision of Business Intelligence (BI) to the enterprise and the way data consumed by BI solutions and the resulting reports are managed. Particularly important if the data is replicated into a Data Warehouse. 
• The major DW architectures (Inmon & Kimball)
• Introduction to Dimensional Data Modelling
• Types of BI, DW, Analytics & Visualisations.
• Data Analytics & Big Data – a brief overview.

Data Modelling

• What are Data Models & why do we need them.
• Different types of Data models, their use and how they interrelate
• The development, and exploitation of data models, ranging from Enterprise, through Conceptual to Logical, Physical and Dimensional.
• A maturity assessment to consider the way in which models are utilized in the enterprise and their integration in the System Development Life Cycle (SDLC).
• Data modelling & Big Data – why data modelling is NOT just about Relational Database design
• Data Modelling – an essential component of Data Governance

Metadata Management

• What is (and isn’t) Metadata
• Provision of metadata repositories and the means of providing business user access and glossaries from these.
• Types of Metadata & their uses
• Sources of metadata
• Metadata & Business Glossaries. What’s the connection?
• The uncomfortable truth about Big Data technologies

Data Integration & Interoperability

• Data integration & Data interoperability – What’s the difference?
• What are the business (and technology) issues that Data Integration is seeking to address?
• Different styles of Data Integration & Interoperability, their applicability and implications.
• The approaches, plans, considerations and guidelines for provision of Data Integration and access.
• Consideration of P2P, ETL, CDC, Hub & Spoke, Service-orientated Architecture (SOA), Data Virtualization and assessment of their suitability for the particular use cases.

Data Architecture & Data Lifecycle Management

• Types of Architectures
• Enterprise Architecture approaches & Process vs Data interaction.
• Proactive planning for the management of Data across its entire lifecycle from inception through, acquisition, provisioning, exploitation eventually to destruction.
• Considerations for Data across the value chain.
• Differences between Data Life cycle & a Systems Development LifeCycle (SDLC).

Data Risk Management, Security, Privacy & Regulatory compliance

• Identification of threats and the adoption of defences to prevent unauthorized access, use or loss of data and particularly abuse of personal data.
• Exploration of threat categories, defence mechanisms & approaches, and implications of security & privacy breaches.
• Identification of risks (not just security) to data and its use, together with risk mitigation, controls and reporting.
• Adapting to the changing legal and regulatory requirements related to information and data.
• Assessing the approach to regulatory compliance & understanding the sanctions of non-compliance.
• Data Management considerations for different regulations, e.g. GDPR, BCBS239

Data Operations Management

• Core roles & considerations for data operations
• Obstacles to performance
• Good Data Operations practices

Document, Records & Content Management

• Why document & records management is important
• The legal implications of significant records
• The records management lifecycle
• Audit and records control

Data Management Tools & Repository

• Examination of the categories of tools supporting the IM disciplines.
• How to select the appropriate toolset.
• Discussion of an example policy for use of specific technology to ensure consistency and interoperability across the enterprise.