Last week, Mr Peter explained a new feature that will be developed that will enhance the data integrity of the data. It was created from the essence of the previous report feature but with more new data calculations included in details. The upcoming feature was definitely a complex one but Mr Peter easily explained it to me and made me understand it very easily. The upcoming feature involved and required a thorough logic, encompassing everything from data input to output in all directions. However, due to its complexity, Mr. Peter advised me to prioritize the current report task for now.
So, I got back to working on the current task, which involved plotting a chart to visualize a dataset over a specific time range. The idea was to provide users with a broad overview or a big picture of their data. For this task, I’m calling data using the API that I’ve created previous week. My initial goal was to create a simple graph to gauge my next steps effectively. However, after producing several graphs, I realized I wasn’t quite confident in their relevance. I started questioning whether the graphs I was making were even suitable. What puzzled me the most was determining the appropriate timeline to retrieve and display the data, considering certain data types correlate with specific timelines.
After deliberation, I sought Mr. Peter’s guidance, specifically regarding the timeline, graph type, and pertinent data for display. Mr. Peter provided a sample timeline for reference and elucidated the preferred graph type for data analysis purposes. Approaching the week’s end, I developed a comparative bar graph representing two datasets. Users can adjust the timeline and specify a time range, facilitating sorting between the two datasets within the bar graph.