Difference between revisions of "IS480 Team wiki: 2018T1 analyteaka FinalWiki"

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Revision as of 16:50, 16 November 2018

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Function Status Confidence Comments
Data Upload Deployed 1 Done
Customer profile Deployed 1 Done
Store profile Deployed 1 Done
Marketing planning Client Approved 1 Client will be using it for Christmas sales planning.
Pending feedback for improvement.
Customization module In the pipeline (Added) 1 -
Geospatial Maps In the pipeline (Added) 0.9 -
Staff Profile module Dropped - Can be integrated into store profile page. Therefore, there’s no need for a separate module.
Analytics & Reporting module Dropped - Can be integrated into store and customer profile. Therefore, there’s no need for a separate module.
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Iteration Date Type Change Reason Description Issued By Decision Action Taken Request Status
2 20/6/2018 Backend Structure Machine learning cannot be done on a standard engine system due to c language requirement Client requested everything to be done on Google standard engine. However, machine learning cannot be done on standard. It would require a flexible or VM instance. Team To maintain client's request of having a standard engine as the front end. While the standard engine wll make calls to the backend (VM) to process data. Proceed with change Closed
3 22/6/2018 Schedule Changing of UT schedule due to stackholder's schedule and re-estimate of task Shifting the schedule of UT and shifting certain tasks around Team To go ahead Proceed with change Closed
7 14/8/2018 Schedule Updating of schedule for changing of modules Sponsor realize it would be useful to have marketing planning feature as well as bein able to name their categories as the cateorgies naming is ever changing. Having the system to do so would be great. Sponsor To go ahead with the change. Proceed with change Closed
9 3/9/2018 Backend Structure Datastore is too slow, we would require a faster system for pulling of data. Hence, the need to dd Mysql to contain the aggregated data. Datastore is meant for long term storage. Hence even retrival of a single record will take at least 2 seconds. Hence, there's a need to speed up the process by using aggregating of data. Data will still be uploaded to datastore and during certain period, a cron job will trigger and aggregate the data to MySQL, allowing the front end to reduce the size of the data being retrieve while increasing the processing speed by reducing the computional power needed. Team To go ahead with the change. Proceed with change Closed

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Stage Specification Links
Project Management Minutes Link Here
Metrics Link Here
Analysis Research Link Here
Architecture Diagram Link Here
Use Case Link Here
Business Process Diagram Link Here
Design ER Diagram Link Here
Class Diagram Link Here
Persona And Scenarios Link Here
Prototype Link Here
Testing User Testing 1 Link Here
User Testing 2 Link Here

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Attributes Consideration Action taken
Usability Support for different screen size and duration for average task Test on multiple screens
Scalability Ability to handle load increase without decreasing performance Google Cloud’s auto scaling
Performance Time spend loading, method execution time Google Cloud’s auto scaling
Security Ability of the system to reduce the likelihood of malicious or accidental actions as well as the possibility of theft or loss of information Hardening of server and implementation of security policies
Maintainability Ability of the system to support change Splitting into modules that’s independently
Availability Uptime of the system above 99.95% Google Cloud’s guarantee
Reliability Continue to operate due to inaccessible of external elements such as database, system and network connections Google Cloud’s guarantee

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