the problem here is there a huge time series list over 5 years or so time span (Ex transaction data)
If I wanna show it to a bank user how do u prefer to show it ?
#Managing Excess list of data
potent bone
thick ravineBOT
<@&987246841693360200> please have a look, thanks.
Here is an AI assisted attempt to answer your question 🤖. Maybe it helps! In any case, a human is on the way 👍. To continue talking to the AI, you can use </chatgpt:1108714622413963314>.
There are several ways to effectively present a large time series list of data, such as transaction data, to a bank user. Here are a few options:
-
Data Visualization: Use charts or graphs to visually represent the data over time. Line charts or area charts can be used to show the trend of transactions over the 5-year period. This allows users to quickly grasp patterns and identify any anomalies.
-
Filtering and Sorting: Provide options for users to filter and sort the data based on different criteria like transaction type, amount, date range, etc. This allows users to focus on specific subsets of data and analyze them more effectively.
-
Aggregated Summaries: Instead of showing every single transaction, provide aggregated summaries at different levels of granularity (e.g., monthly, quarterly, yearly). This can help users get an overview of their transactions without overwhelming them with excessive details.
-
Drill-down Capability: Allow users to drill down into specific time periods or transaction categories for more detailed information. This can be achieved by providing clickable elements in the visualization or using interactive features that allow users to explore the data at different levels.
-
Search Functionality: Implement a search feature that enables users to search for specific transactions based on keywords, amounts, dates, etc. This can be useful when users want to locate specific transactions within the large dataset.
-
Performance Optimization: As handling a large dataset can impact performance, ensure that your application is optimized for efficient loading and processing of the data. Consider implementing pagination or lazy loading techniques to load only a subset of data initially and fetch more as needed.
Ultimately, it's important to consider the specific needs and preferences of bank users when deciding how to present such a large time series list of data. User testing and feedback can help refine the presentation approach further.
potent bone
@trim rover
@obtuse plaza
obtuse plaza
Fetch a limited number of records from a backend, in the UI just show a table layout with:
date - vendor - amount.
And tap on it to see details.
potent bone
if we see on a cellular network UI/UX will detiorate
trim rover
Then cache it
potent bone
Fetch a limited number of records from a backend, in the UI just show a table la...
thats a coll solution
trim rover
Not store it
potent bone
Then cache it
data security is lost when i store in local db
trim rover
Ram
potent bone
Not store it
cache it in server?
obtuse plaza
It won't degrade, and no local caching. A small call like that takes no time.
potent bone
It won't degrade, and no local caching. A small call like that takes no time.
ok take a Intra day stock broker he does 20 to 30 put and call in a single daay thats massive 10k+ records a year
obtuse plaza
so?
potent bone
do u wanna cut it to last 100 ?
potent bone
on a mobile device? I'd say 10 tops
thats a better one If we see
like a 10 or previous weeks data which ever is higher?
obtuse plaza
last week or 10 whichever is fewer
potent bone
last week or 10 whichever is fewer
Y fewer?
obtuse plaza
because if there are 20 transactions in the last week, and only 10 fit on a page why fetch 20? If they go to the next page just fetch the next 10.
obtuse plaza
you're welcome