Business Measurement Sophistication
‘Business Measurement Sophistication’ outlines the importance of utilising measurement frameworks in business decision-making, understanding the Balanced Scorecard and OKR frameworks, and identifying North Star metrics. Howard Diesel discusses the impact of metrics on business and agile teams, the alignment of business strategy and data metrics, and the importance of countermeasures in agile team performance. The webinar discusses key business metrics and analysis concepts, big data context diagrams and analytics, and the uncertainty framework and team structure. Howard stresses that by understanding and utilising these concepts effectively, businesses can measure performance and culture, align data with business metrics, and ultimately achieve their strategic goals.
Working with Data in South Africa Challenges and Opportunities with Daan Steenkamp
‘Working with Data in South Africa Challenges and Opportunities with Daan Steenkamp’ highlights the importance of data management, the value of intangible assets, and the significance of reliable and timely data in decision-making. Dr Daan Steenkamp focuses on South Africa's data ecosystem, its comparison with global best practices, and the challenges and opportunities in data management and open science. He emphasises the importance of data maturity and infrastructure, data sharing, governance, privacy concerns, and utilising alternative data for real-time understanding. The webinar discusses metadata implementation in time series data, community-driven data collaboration, and basic data management.
Riskiest Risks - Data Protection for DM Professionals
‘Riskiest Risks - Data Protection for DM Professionals’ outlines key considerations for effective data management, governance, and privacy in modern organisations. Caroline Mouton and Howard Diesel cover data understanding, security and risk assessment, data architecture, and data compliance. The webinar explores the importance of data classification and emphasises cataloguing and lineage, along with the utilization of metadata to analyse data assets. Additionally, Caroline and Howard highlight the significance of data privacy and compliance in automated decision-making and the need for collaboration and accountability in data management. They suggest implementing these strategies as essential for ensuring data integrity, security, and compliance while facilitating effective decision-making processes.
DMBOK Revised Edition – Episode 2
‘DMBOK Revised Edition – Episode 2’ outlines various data management and examination procedures topics. Howard Diesel covers the transition to the new exam platform, Canvas, and provides online quiz procedures and navigation information. Additionally, he discusses the evaluation and exam procedures for D2L, exam feedback, and technical issues. The webinar discusses the changes to data quality dimensions, data integration, data lineage, and metadata. It emphasises the significance of understanding data quality and information security regulations and the role of data modelling and cardinality in relationship types. Lastly, Howard highlights the essential points for data science and ethics exam preparation, the importance of using a dictionary in data management, and data lineage tools.
CDMP Specialist RMD (Reference & Master Data) – Golden Rules
It is no use dragging your organisation through the Reference and Master Data gauntlet if you do not radically improve the quality of your data and simplify data sharing and integration.
The critical success factor to Master Data Management is keeping your data GOLDEN! If you can not achieve this level of reliability you are selling empty promises and dreams.
Just the Facts - Information Modeling with Business Communication with Marco Wobben
‘Just the Facts - Information Modeling with Business Communication with Marco Wobben’ focuses on the evolution, challenges, and importance of information exchange, data management, and communication in the context of consultancy and technical environments. Marco Wobben emphasises the significance of communication between domain experts and technical professionals, the management of data, and the development of communication-oriented methodologies. Additionally, he addresses the importance of data modelling, information structure, data quality, and the collaborative approach needed to bridge the gap between technical and business stakeholders in the context of agile methodologies and fail-fast principles.
Data Privacy & Unstructured Data - DAMA SA
Caroline Mouton covers various aspects of information management, privacy compliance, and data security.
She includes the importance of document and records management and the differences between documents and records.
She explained the challenges of managing records and metadata, the relationship between technology and information, enterprise information management, and records management.
She reviews the significance of website snapshots as records, privacy risks, data breaches, unstructured data risks, and sharing and securing access to team spaces and channels.
Additionally, Caroline sheds light on tools for mapping data flow and creating diagrams, data flow and risk assessment in website form process, data storage and management, the importance of structured data and data visualisation in business, the importance of language and data management in the workplace, the importance of data governance and tools in content management, the importance of case management and workflow tools in business operations, and importance of data management and tools for incident management and compliance.
Lastly, Caroline provides a quick playbook for file shares and managing privacy risks with data flow diagrams, effective communication, and simplified diagrams.
Data Abstraction for Data Professionals
Abstraction involves breaking down a model into smaller parts for presentation to different audiences, with an emphasis on reducing noise and clutter to focus on essential elements. There are different types of abstraction, including horizontal and vertical abstraction.
Data modelling involves creating a high-level diagram of the house, a data estate, or a data landscape and then breaking it down into conceptual, logical, and physical models. It also involves abstracting reality to present to users and hiding details to make it more communicable. When building data models, it is crucial to understand the difference between horizontal and vertical abstraction. Horizontal abstraction partitions the diagram by subject area, while vertical abstraction involves drilling down to detail.
Data Abstraction for Data Managers
The topic of abstraction and its uses and dangers in development, object-oriented programming, and data modelling is discussed by Howard. He shares his experience of learning about the hazards of abstraction from Steve Hoberman’s course and how it can create more responsibility for developers.
The concept of abstraction safety guide and its use in simplifying data models and presenting information to business users is explored. Partitioning and absorption are also discussed. The process of specifying, from business requirements to technical details, and the definitions of "specification" and "abstraction" are explained in detail.
The different levels of understanding for specifications, such as a detailed description of work or materials for a project, instructions on how to do or make something, and architect specifications for a new building, are described.
Creating a believable visual presentation to define high-level requirements and using a conceptual model to get precise definitions for eliciting requirements to create a business glossary and threading logic from top to bottom is explained.
Revised Edition Changes to DMBOK v2
‘DMBOK R2’ highlights the key topics discussed during a virtual meeting on the revised edition of the Certified Data Management Professional (CDMP) exams and the Data Management Body of Knowledge (DMBoK). The meeting covers updates to the DMBoK, data governance, data modelling, professional data management, data quality, metadata management, risk management, big data, and sustainability concerns. Suggestions were made to improve exam questions and align exam answers with the DMBoK’s definitions. Howard Diesel provides valuable insights and learning opportunities for professionals in the field of data management and information technology.
Transitioning from Business Intelligence to Decision Intelligence with Erwin Bisschops
Erwin Bisschops will explore the Theory of Perception and how individuals can perceive the same object in different ways. To demonstrate this concept, an experiment will be conducted using images of a rabbit/duck, an old/young lady, and a nurse/frog. He will delve into Decision Intelligence, which combines quantitative and qualitative elements to enhance decision-making and actions.
The Theory of Perception and Decision-Making will be explored, focusing on applying it to business intelligence. The challenges of self-service business intelligence will be examined, along with how Gartner's magic quadrant for analytics and BI platforms considers components like security, Cloud enablement, metadata, natural language queries, data storytelling, reporting, and visualisations.
The discussion will shift to the focus on technical capabilities in BI, which has led to a lack of understanding of how decisions are made. The alternative of an engineering approach to decision-making will be proposed, as opposed to romanticising gut-feel decisions.
How to Evaluate a Data Vault Warehouse Automation Tool & Why Willibald Will Help
Discover some fascinating topics that may interest you!
These include analysing data tools in an online store, the importance of delivery dates and partnership associations in e-commerce, exploring the relationship between gardening associations and point-of-sale data models, key factors to consider when testing data warehouse automation tools, challenges in managing relationships in data vault, perspectives on data vault modelling and automation, discussing automation tools and data integration, an overview of common data management challenges and their solutions, the significance of data warehousing and related topics, feedback on Insert Statement and Presentation, tips for implementing data modelling and technical patterns, integrating database automation tools with Azure, implementing automation tools and data integration in software development, the benefits of data modelling, and selecting the right tools for creating a data warehouse.