1. JCU Marine Data Technology Hub (M-DataTech)
1.1. Technology Solutions for capturing and processing data streams relevant to marine management and conservation
1.2. Linking Science and Technology for coastal Management
1.3. Science for effective coastal restoration
1.4. Value and Dynamics of Coastal Ecosystems
2. Key roles
2.1. Dr Adrian Langley
2.1.1. Program Manager
2.1.2. Researcher
2.2. Ram Sivalingam
2.2.1. Data Engineer
2.2.2. Expert Analyst
2.3. Todd Bartholomew
2.3.1. Data Scientist
2.3.2. Applied Machine Learning Engineer
3. Team Members
3.1. Dr Adrian Langley
3.1.1. Specialist in Anaesthesia/Intensive care Medicine
3.2. Ram Sivalingam
3.2.1. Database/Data Warehouse Developer
3.3. Todd Bartholomew
3.3.1. Telecommunications Engineer
4. MA5854 Assessment 1 Todd Bartholomew 24/01/2021
5. Critical Issues
5.1. Does the team have the skills and experience to take on the data science consultancy task?
5.1.1. We formed a team with experience working with each other
5.1.2. Skill of the team member compliment each other
5.1.3. Clear team leader with Dr Adrian Langley
5.2. Is the project achievable in the time frame given?
5.2.1. Initial analysis of the scope and data suggests the project is achievable
5.3. Client motivation to proceed with consultancy project?
5.3.1. Initial meetings with client show that they are highly motivated to proceed and provide support in the project.
6. Data Science Problem Scope
6.1. Develop methodologies and approaches to analyse and understand water quality time series data
6.2. Present data to facilitate decision making
6.3. Provide repeatable analysis process to be used on new datasets
7. Process and Methods
7.1. Phase 1: Project Initiation
7.1.1. Meet with Dr Carlo Mattone from the Marine Data Technology Hub
7.1.2. Unpack the problem
7.1.3. Seek clarification on any questions
7.2. Phase 2: Discovery, design and dialogue
7.2.1. Collect data from client and external resources
7.2.2. Perform exploratory analysis
7.2.3. Determine strategy and break down problem into achievable pieces
7.3. Phase 3: Analysis and decision to act
7.3.1. Analyse the data
7.3.2. Apply a number of algorithms and analysis techniques
7.3.3. Evaluate results
7.3.4. Share results with client for feedback
7.4. Phase 4: Implementation
7.4.1. Present final solution and recommendations to client
7.5. Phase 5: Extension, recycle or terminate
7.5.1. Discuss further consulting opportunities
7.5.2. Close project
8. Milestones
8.1. MS1- Week 1: Meet and greet
8.1.1. Initial Meeting with client to introduce the team and understand the problem
8.2. MS2- Week 3: Preliminary final report and client meeting
8.2.1. Present initial finding to the client
8.2.2. Receive feedback on progress
8.2.3. refine solution based on feedback
8.3. MS3- Week 6: Final executive report and client presentation
8.3.1. Present final executive report to client
8.3.2. Discuss future consulting opportunities
8.3.3. Close project