ICT&SS ProfessionalProject Manager (Agile)Digital Service ManagerDigital Business AnalystData EngineerAI Engineer
This introductory programme has been developed to introduce modern data management technologies to participants. Among the topics to be analysed are the definition of basic data management techniques and technologies, the background of such technologies, and the future trends of Data Technology and Management (DTM).
This programme will also explain the differences between various Data Management approaches, environments, and tools, as well as the advantages and disadvantages associated with their diverse applications. Emerging trends in the field of DTM will be reviewed as well.
At the end of the programme, you will be able to:
understand the basic terms of DTM, along with the characteristics and applications of different DTM techniques
articulate the future trends of DTM
compare the advantages and disadvantages of the new DTM platforms and tools in different applications
recommend a set of tools for a given problem
Who Should Attend
Please refer to the job roles section.
Suitable for IT Engineers, IT Managers, IT Executives and IT Consultants.
Minimum two years of working experience in the field of IT.
The programme is conducted virtually and covers the following topics:
Programme Introduction, description of the goals, contents, and scheme
Data management technology: Definitions and basic terms
Big Data and Big Data Technology: Definitions and basic terms
A review of the DBMS/RDBMS technology and trend
Technical details of Big data, Cloud and Edge techniques
Hardware and software requirements
Differences between ordinary DBMS/RDBMS and Big data
Skills and resources needed for big data management
Data quality for big data solutions: data quality assurance for big data systems
Data quality for big data solutions: new methodologies
Cloud and edge technologies introduction
Moving to big data: architecture, infrastructure, application, metadata
Future trends in big data technology
Tools review: Airflow, Kubernetes, Docker, ML Flow, Google Cloud, Mongo DB, Graph Databases, No SQL, and Server-less technologies
Tools Comparison: Airflow, Kubernetes, Docker, ML Flow, Google Cloud, Mongo DB, Graph Databases, No SQL, and Server-less technologies
Security considerations in modern DM
Versatility considerations: Technical and implementation
Volume and Velocity considerations: Technical and implementation
IoT and multi-resources considerations: technical and implementation
Big data implementation: requirements, roadmaps, strategies
Big data implementation: challenges, integration, and validation
Big data analysis challenges and methodologies
Big data scaling challenges, necessities, and the application side
Data warehousing for big data and its challenges
Describing future DTM trends
Full programme fee
9% GST on nett programme fee
Total nett programme fee payable, incl. GST
With effect from 1 Jan 2024
NOTE Funding is available for this programme. Please visit the learning provider's website to find out about the updated programme fee funding breakdown, eligibility, terms and conditions.