Abstraction for Data Citizens
Executive Summary
This webinar outlines key concepts and practices in data modelling. Howard Diesel emphasises the critical role of these concepts and practises in data governance and effective business operations. He then highlights the importance of various modelling techniques and the necessity of documenting requirements to ensure all stakeholders have a clear understanding of data structures and their implications. Additionally, the webinar underscores the value of building a comprehensive business glossary and the essential role of visual communication in facilitating collaboration and clarity among teams. By integrating these elements, organizations can enhance their data management processes and drive informed decision-making.
Webinar Details
Title: Abstraction for Data Citizens
Date: 27 July 2023
Presenter: Howard Diesel
Meetup Group: Data Citizens
Write-up Author: Howard Diesel
Contents
Elements of Abstraction in Data Modelling
Notes on Business Discussion
Data Modelling for Data Governance
Different Modelling Techniques
Importance of Documenting Requirements in Data Modelling
Building a Business Glossary and the Importance of Visual Communication
Elements of Abstraction in Data Modelling
During a discussion on the elements of abstraction in data modelling, Howard Diesel points out that there are varying degrees of abstraction to consider. While abstraction can be helpful in some cases, it's crucial to distinguish it from generalisation. Remco illustrates this concept using the example of party and role as abstract and generalised terms in a technical solution. However, Remco cautions that such abstraction may not be appropriate for communicating with business personnel. Remco and Howard agree that abstraction is challenging to comprehend, create, and maintain, and its value must be carefully assessed. Howard suggests describing the company's requirements and characteristics first to start the data modelling process. It's crucial to match the level of abstraction with the customer's specific needs.
Notes on Business Discussion
It's important to find the right level of detail and focus when analysing data, much like adjusting a camera zoom. A broad overview can provide understanding, but too much detail can be overwhelming.
To ensure data privacy, all individuals, whether customers or vendors, must be treated equally. In the event of a data breach, it's necessary to communicate with all data subjects at an individual level.
Effective communication with businesspeople at the start of a project can be aided by discussing focus, terminology, and desired information level. The discussion focused on data breaches and reporting rather than other assessments or business events.
Data Modelling for Data Governance
Data models are crucial for data governance and can be used in a data governance assessment. The CDMP® exam covers subtypes, supertypes, and conceptual models. It also includes questions about the benefits and uses of conceptual models and their differences. Learning data governance concepts is essential for personal and professional growth, as Patricia acknowledges that he is always learning.
Hesham inquires about making data models agile to adapt to future changes. He is seeking best practices, methodologies, or frameworks to make data models adaptable.
Different Modelling Techniques
During the discussion, Howard brought up a presentation about Data Vault that emphasised its agility and core concepts. The Anchor Vault modelling technique is known for its extreme agility and is often called an additive model. However, when dealing with abstraction, the process of breaking apart and rebuilding can become complex depending on the initial design. The choice of modelling technique ultimately depends on the application environment and goals. Software vendors often prioritise abstraction and flexibility, but it may not be necessary if it doesn't add value to the business. Abstraction suits operational or module-based applications like ERP or CRM systems. For data warehousing, dimensional or flat file modelling is preferred for integration. However, when frequent changes are expected, Anchor modelling is recommended for data warehousing. Lastly, adjusting “camera settings” at the beginning of a project to achieve optimal results is important.
Importance of Documenting Requirements in Data Modelling
To ensure the model's direction is clear, it's essential to document the requirements. An Excel spreadsheet can store “camera settings” as a reference for future modellers. Remco is motivating Hans to write about different Warehouse layers and their requirements. Hesham recognises the significance of data governance and management. Including a business glossary in a data, model can help reach an agreement. Creating a scorecard displaying relationships between glossary terms can be helpful. An image-based approach can simplify communication and sign off on business rules.
Building a Business Glossary and the Importance of Visual Communication
The Financial Markets Department was advised to create a glossary as a starting point. Howard and his team spent a weekend compiling around 3,500 business terms. However, the glossary presentation did not generate much enthusiasm or discussion. To overcome this, Howard suggested dividing the glossary into sections and offered to create a data model, which led to spirited debates. Hesham favours visual communication and is skilled at presenting information visually. During workshops, Remco uses drawings and models to clarify and encourage discussion. Remco stresses the significance of visual aids, such as PowerPoint and icons, in conveying intricate ideas. Data modelling tools' limitations in visually representing concepts are acknowledged and addressed.
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