Here is our Azure Data Analysis Project.
Project will help to analze the intepretive data related to weather & data from the Mood-Metric to show analysis of stress. and we settup the Azure Achitercht for data facility which considered to used ETL Framework for this project. Such as future to connect with multiple ring of data and being possible to land them into one data source on the cloud.
The azure architect cloud is our data facility mainly help the data working through different method from processing data to making the right connect for data flow. The user product will land will be the Power-Bi and Azure is the backend behind our data facility as high level of infrastructure keep the pipeline running and processing the data from multiple rings. This architect will support a lot of ring user will be able to store their data in cloud and future assist the computer people / other software dev who want to improve and collaborate to make a different level of this data project can be used and ability to connect with another project is highly consider. This part is our main deep tech development progress behind all those data processing.
Describe the main analysis of data relates to multiple USER_ID and Weather. Client can access multiple ring according to the slide in right side and adjust to see the detail with USER_ID. This page will help client understand the data insight in weather and MM_Level which mean the stress level of each user.
Data scientist have the overview relate with Activities, this page shows a data trend interpretive with activist whether they are going do activities. Big category such as Work, Sleep, Travel, Dinning, Fitness is our main activities to see how stress is relate and also compare them in general overview. In depth the analysis of Python will explain them detail.
Dashboard 3 describe the multiple graphics relate more on SCL and Weather. It will be a boxplot and the SCL comparison with another factor. We also add the Average of SCL, and Sum of all Precipitation affect to the walking number of user. The Time Strip meanwhile is the hour from 1 to 24 hour per day and show the appearance of data in there. Future: Dashboard can be iterated depend on the demand of client, and the more grow data-set might make the granular impact to the data quality it-self however graph will stable for long-term which doesn’t need to change. Dashboard was made for scientist with the vision possible to observe many user_id data performance.