virtual
Intensive Data Management covers the essentials for information systems professionals wanting to increase their Data Management skills and effectiness.
- Virtual
- 6 x 4 hour session
- Next course commencing 10 March
A$2850 +gst
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Intensive Data Management
Increase your effectiveness in Data Management, Data Governance and Data Quality
Level 2
- 6 live instructor sessions
- Hard copy workbook
- Case study videos
- Certificate of completion
Course objectives
On completion of this course, you will be able to:
- Explain the core concepts of Data Management using the international standard expressed in DAMA’s DMBoK V2
- Understand the steps to set up Data Governance including purpose, strategy, glossaries and steward case studies
- Communicate the key concepts in managing Data Quality; diagnose issues, document requirements and know a variety of practical approaches to improve data quality
Benefits of this course
Gives you confidence to:
- Assist in establishing the right (data) culture within your organisation
- Use data effectively and efficiently
- Decide when to trust data and when not to
- Keep data secure and youself out of trouble
Who is this course for?
If you are someone who is just appointed to a data management role, this is the course for you. It will help you get started and give you a number of guidelines that will sustain you for the first couple of years.
If you have data management experience and are looking to review the DMBoK ready for an examination have a look at the CDMP Exam Cram.
Why Intensive Data Management?
- Organisations mandate training to protect valued assets: People, Money, Reputation and Data
- Helps staff Improve their understanding and confidence in handling data assets.
- “Organisations rely on their data assets to make more effective decisions and to operate more efficiently” (DMBoK V2 P20)
Course content
The course contains three sections:
- Data Management
- Data Governance
- Data Quality
DATA Management
Data underpins every business decision and every single successful customer experience. Data and Information Management is one of the world’s newest disciplines. Creating, moving and using quality data and information is not an accident. It is data management.
The data management sessions cover the basic and foundational aspects of data management to provide understanding of data management.
It is targeted at anyone working in data management or is needing a broader overview or those working extensively with data management professionals.
These sessions teach:
- what is Data Management?
- the core knowledge areas from Data Management Body of Knowledge (DMBOK)
- how to apply Data Management learning in your organisation
Topics in these sessions include:
- Data Management definition
- Data Architecture
- Data Modelling and Design
- Data Storage and Operations
- Data Security
- Data Integration
- Documents and Content
- Reference and Master Data
- Data Warehousing Business Intelligence
- Meta-Data Management
- Data Quality
- Data Governance
DATA Governance
Your business has to ensure everyone is on the same page when it comes to setting and enforcing rules.
It is targeted at anyone working as a data steward or with data stewards implementing or trying to improve Data Governance.
These sessions teach:
- the practical establishment of data governance
- how to properly consider policy and strategy
- how to hold practical meetings with realistic agendas
Topics in these sessions include:
- Introduction to Data Governance
- Your choice of operating models
- Writing a data policy/ strategy
- Managing glossaries, dictionaries and data models
- Links to Data Management Knowledge areas
- A menu of promotion options
DATA Quality
Data Quality is understood by DMBOK as the application of manufacturing principles to data.
The data quality sessions provide a practical foundation in understanding data quality.
It is targeted at anyone working in data quality function, who wants to prepare for certification or needs to interact with Data Quality managers.
These sessions teach:
- how quality is systemically manufactured, (and not just lucky!)
- how to forward and reverse engineer data quality requirements
- Practical case studies
Topics in these sessions include:
- Learning to express what we mean by “fit for purpose”
- Data Quality Strategy and business cases answering “why do it?”
- Common sources of data quality issues, how to find them and how to get to a root cause
- Completing data quality requirements
- Operations (monitoring and responding)
- Sampling quality at key points in the value chain
- Data quality tool requirements