When beginning any programme, starting with the end in mind is essential. Starting with the end in mind will help you stay focused and use your structured and unstructured records efficiently and sometimes effectively.

1. Take the time to plan out the result you want to achieve and
2. Map out the steps you need to take to get there.

Should we apply this approach to your data privacy programme?

Caroline Mouton recommends this approach and has provided us with questions to help us define the target state.

Join DAMA Southern Africa for more webinars:
https://www.meetup.com/dama-sa-data-m...

Follow Howard Diesel & Caroline Mouton on LinkedIn:
linkedin.com/in/howarddiesel-infogovernance
https://www.linkedin.com/in/carolinemouton/

For more information on our services:
https://dama.org.za

Data Protection for Data Management Professionals 2023-04-12

Last week, the DAMA SA community was treated to a very informative session with Lucien Pierce providing a lawyer's perspective from his 20+ years regarding data privacy, ethics and service-related issues.

Lucien is a director at PPM Attorneys who have a passion for commercial, regulatory and ICT law and he shared lots of real-life examples with the DAMA (Data Management Association) Southern Africa community.

The panel discussion considered learnings from use cases spanning a range of industries.

The discussions considered the complexities and intricacies from a legal perspective of anonymization of healthcare data; the profiling challenges of insurance data and finally the desire to drive broad usage of government data to improve the lives and facilitate commercial opportunities for citizens.

A key takehome was that a privacy-by-design philosophy should be employed during the process of creating data products, for legal teams to try to resolve disputes retrospectively is an inefficient way to leverage scarce resources.

A real privilege to see how active the data management and analytics community is in South Africa and the desire to share and learn from each other.

Please comment below if you want to heat the recording and the Modelware Systems Team will gladly send it.

Thank you Lucien Pierce for sharing with our community!

Join DAMA Southern Africa for more webinars:
https://www.meetup.com/dama-sa....-data-management-mee

Follow Howard Diesel & Lucien Pierce on LinkedIn:
linkedin.com/in/howarddiesel-infogovernance
linkedin.com/in/lucienpierce

For more information on our services:
https://dama.org.za

00:00:00 African Data Management Community Forum 2023-05-11
00:02:53 Unexpected Career Journey
00:05:19 Career as a Writer and Lawyer
00:07:38 Career background and upcoming presentation on law firm of the future
00:10:45 Anonymization in Healthcare
00:12:22 Anonymization Challenges in Healthcare Data
00:17:03 Debates on Laws and Data Breach Reporting
00:20:03 Anonymization and Aggregation in data usage
00:23:07 Privacy and Security Concerns in Data Aggregation
00:26:29 Pseudonymization and Anonymization in Health Data and the Use of Synthetic Data for Training Learning Algorithms
00:29:41 Importance of Proactive Client Communication and Data Destruction
00:31:26 Data Destruction and Ensuring Compliance
00:35:18 Data Traceability and Archiving Process
00:37:32 Data Deletion and Privacy by Design in Data Governance
00:41:00 Legal Considerations in Data Profiling for Insurance
00:43:39 Data Collection and Profile Building by Insurers
00:46:42 Profiling and the Impact of GDPR
00:50:27 Implications of Insurance Fraud in the Era of Data Collection and Governance
00:53:26 Balancing Public Interest and Privacy in Legislation
00:55:39 The Importance of Responsible Data Collection and Government Involvement
00:59:37 Database Integration Debate
01:02:27 Challenges of data anonymization and re-identification
01:05:19 The Importance of Responsible Data Usage and the Future of Society

This webinar covers three Data Strategy lessons (illustrated by examples), which will help you to establish realistic expectations and demonstrate business value. View more Data-Ed webinars with Peter Aiken: https://www.dataversity.net/ca....tegory/education/web

This webinar covers three lessons, each illustrated with examples, that will help you distinguish the difference between Data Strategy and Data Management processes. View more Data-Ed webinars with Peter Aiken: https://www.dataversity.net/ca....tegory/education/web

Michele Koch will be presenting Sallie Mae's successful approach to deriving business value metrics by quantifying the impacts to generating revenue and avoiding costs. My hope is that our lessons learned with help others in this area since I know how difficult determining metrics can be.

Some of the topics that will be covered include:

* Our methodology for determining business value categories
* Assigning business value status criteria ranges
* Deriving business value calculations
* Generating our DQ dashboard

Recorded: 07/07/2022
Presenter: Ben Wu

Presented at the Australian and New Zealand Data Quality Interest Group meeting.

Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business.

Takeaways:

- Understanding how to contribute to organizational challenges beyond traditional data architecting
- How to utilize data architectures in support of business strategy
- Understanding foundational data architecture concepts based on the DAMA DMBOK
- Data architecture guiding principles & best practices

Organizations must realize what it means to utilize data quality management in support of business strategy. This webinar will illustrate how organizations with chronic business challenges often can trace the root of the problem to poor data quality. Showing how data quality should be engineered provides a useful framework in which to develop an effective approach. This in turn allows organizations to more quickly identify business problems as well as data problems caused by structural issues versus practice-oriented defects and prevent these from re-occurring.

Takeaways:

Understanding foundational data quality concepts based on the DAMA DMBOK
Utilizing data quality engineering in support of business strategy
Data Quality guiding principles & best practices
Steps for improving data quality at your organization

About the Webinar:
Much like project team management and home improvement, Data Governance sounds a lot simpler than it actually is. In a nutshell, Data Governance is the process by which an organization delegates responsibility and exercises control over mission-critical data assets. In practice, though, Data Governance directs how all other Data Management functions are performed, meaning that much of your Data Management strategy’s capacity to function at all depends on your effectiveness in governing its implementation. Understanding these aspects of governance is necessary to eliminate the ambiguity that often surrounds effective Data Management and stewardship programs, since the goal of governance is to manage the data that supports organizational strategy.

This webinar will:

Illustrate what Data Governance functions are required for effective Data Management, how they fit with other Data Management disciplines, and why Data Governance can be tricky for many organizations
Help you develop a detailed vocabulary and set of narratives to facilitate understanding of your business objectives and imperatives that demand governance
Provide direction for selling Data Governance to organizational management as a specifically motivated initiative
Discuss foundational Data Governance concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)

En este taller revisamos el marco de trabajo DAMA y en particular el tema de Datos Maestros y Referenciales, datos que constituyen la base de los datos de una organización y que muchas veces se encuentran distribuidos en distintos sistemas, son inconsistentes entre sí y generan dificultades para el cruce y consolidación de información. La identificación, estandarización y gestión de estos datos es por tanto fundamental para poder hacer análisis y ciencia de datos de calidad.

Expone: Óscar Herrera, Profesor gobernanza de datos.

Este taller fue realizado como parte de la V Feria de Innovación Pública del GobLab de la Escuela de Gobierno de la Universidad Adolfo Ibáñez.

Presentación: https://bit.ly/49bcSKs
Más información: https://goblab.uai.cl

Data Retention & Disposal Policies. Data Retention certainly generates a lot of discussions and questions:
1. Where should I start?

2. What type of data/information is involved?

3. Which systems need to adhere to the policy?

4. What justifications are acceptable, and for how long?

5. How should I record data disposal?

6. Who is part of the RACI

Caroline Mouton did a great job answering many of the questions; specific questions usually lead to more questions. For example, de-identification and anonymisation.

I believe that the Data Retention Policy is one of the policies that should be a top priority. Templates are available; you don't need to start with a blank page.

Follow Howard Diesel on LinkedIn:
linkedin.com/in/howarddiesel-infogovernance

For more information on our services:
www.modelwaresystems.com
https://dama.org.za

2022-09-14

Every organization produces and consumes data. Because data is so important to day to day operations, data trends are hitting the mainstream and businesses are adopting buzzwords such as Big Data, NoSQL, data scientist, etc., to seek solutions for their fundamental issues. Few realize that the importance of any solution, regardless of platform or technology, relies on the data model supporting it. Data modeling is not an optional task for an organization’s data effort. It is a vital activity that supports the solutions driving your business.

This webinar will address fundamental data modeling methodologies, as well as trends around the practice of data modeling itself. We will discuss abstract models and entity frameworks, as well as the general shift from data modeling being segmented to becoming more integrated with business practices.

Learning Objectives:

- How are anchor modeling, data vault, etc. different and when should I apply them?
- Integrating data models to business models and the value this creates
- Application development (Data first, code first, object first)

Organizations must fully understand the difference between Data Management and Data Strategy to fully achieve their respective goals. View more Data-Ed webinars with Peter Aiken: https://www.dataversity.net/ca....tegory/education/web

Kewal Dhariwal talks about the Value of Professional Associations.

Kewal Dhariwal, CCP, CDMP, CBIP, I.S.P., ITCP is the ICCP Executive Director (www.iccp.org ) and is the Former CIPS National President (www.cips.ca).

InfoCompass CEO, Nitza Medina-Garcia, CRM, MLIS, gives a presentation to the Greater Sacramento Chapter of ARMA on Data Migration for Records Managers.

The last month of intense DQ activity has exposed some exciting observations:
1. By doing DQ early, we can achieve Data Veracity (trusted data assets)

2. 2 to 3 hours is all you need to profile your data sets and create visualizations which inform your DQ Business Rules.

3. Using a consistent set of DQ Visualizations tools, you can provide a compelling DQ Dashboard that data consumers can benefit from

4. Data Citizens (Scientists) can get involved early to expose challenges and suggest reasonableness business rules.

An essential outcome of a DQ Initial Assessment is a Business Impact Assessment.

If done correctly, the results of this impact assessment can lead to all sorts of revenue-generation opportunities for business operations.

JG Cowper demonstrated using Box Plots to create an Impact Analysis that revealed to the business that it could achieve higher revenue volumes than it is currently experiencing.

Follow Howard Diesel on LinkedIn:
linkedin.com/in/howarddiesel-infogovernance

For more information on our services:
www.modelwaresystems.com
https://dama.org.za

Join DAMA Southern Africa and Modelware Systems events to learn about data management:
https://www.meetup.com/dama-sa....-data-management-mee

African Data Management Community Forum 2022-09-15

The last month of Data Quality immersion for JG Cowper, Estie Boshoff (Pr. Eng.), and I have been eye-opening. I have done several DQ projects, but I never approached DQ with a view of delivering value.

The DQ Initial Assessment delivers value in spades:
1. Feedback to application developers as to where we faced DQ challenges

2. Stakeholder Interactions that revealed Data Capture quirks

3. Data Issues for the Data Management Office

4. Data Remediation suggestions which will lead to subsequence Data Projects, for example, Reference and Master Data

5. Frequency analysis for the Data Scientists

6. Business Revenue impact analysis

The most important revelation was that this assessment could be done quickly and reveal all sorts of challenges, even before building the data product.

To learn more about our training and upcoming webinars:

Follow Howard Diesel on LinkedIn:
linkedin.com/in/howarddiesel-infogovernance

For more information on our services:
www.modelwaresystems.com
https://dama.org.za

Join DAMA Southern Africa and Modelware Systems events to learn about data management:
https://www.meetup.com/dama-sa....-data-management-mee

African Data Management Community Forum 2022-09-22

CPHIMS/CAHIMS Exam preparation video. Chapter 4, Systems Design

https://dama.org/sites/default..../files/download/DAMA
00:00 Intro
1:26 The System Development Life Cycle (SDLC)
2:24 SDLC stages
2:40 SDLC methodologies
3:07 System Design
3:50 Purpose and Goals of System Design
4:12 Create accurate technical specifications
8:45 Request for Information (RFI)
10:05 Chose between build or buy development approaches
10:38 Process for build decision
10:55 System design processes, technique, and deliverables when system is developed in-house
11:12 Processes
13:17 Process for a by decision
13:31 Best of breed
14:01 Single vendor
14:21 Request for Proposal (RFP)
16:19 System design considerations
19:38 Business process management (BPM)
20:37 List of role in system design phase
21:22 Data management practices
21:56 DAMA-DMBOK functional framework

Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business world’s consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords: “big data,” “NoSQL,” “data scientist,” and so on. Few realize that any and all solutions to their business problems, regardless of platform or relevant technology, rely to a critical extent on the data model supporting them. As such, Data Modeling is not an optional task for an organization’s data effort, but rather a vital activity that facilitates the solutions driving your business. Since quality engineering/architecture work products do not happen accidentally, the more your organization depends on automation, the more important the data models driving the engineering and architecture activities of your organization become. This webinar illustrates Data Modeling as a key activity upon which so much technology depends.

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