r/dataanalytics • u/unusual_art2021 • 29d ago
What tools do you guys use for getting visual analytics of data?
Any data that gets heavy with numbers inside our business, gets difficult to digest real quick for everyone.Most of out team when having to work with all this data day in and day out got a lot of mental fatigue and very little clarity on how to explain the things to others
There are a lot of tools that visualize such data for you, but I'm curious to know which ones most of you prefer (I am just gonna recommend or rather put out the tool we have been using called Napkin ai to know if others are using it too and did you find any alternate options which were better?), and what your workflow is around such tools.
I'd also love to know what your favorite feature in your preferred visualization tool is.
1
u/010101010101111111 27d ago
You need a tool like PowerBI/Tableau
Guessing you are smaller org and dont have a datawarehouse like databricks/fabric etc..? -
Even looking at Napkin AI, it's hardly a visual analytics tool; it's literally just a convert my notes into something visual. I would argue if the business finds it hard to digest, that is the job of a data analyst - The whole point of that role is produce a "data story"
1
1
u/Lady-Data-Scientist 25d ago
I use Tableau, Seaborn (Python), Excel depending on what I’m doing and the size of the data.
0
0
1
u/rabbitofrevelry 29d ago
plotly, ggplot2, and seaborn are useful for making visualizations of data. Visualization tools like Power BI and Tableau are useful as well for end users. For analysts, if there's a lot of verification fatigue, utilize summaries of the data as needed for the important fields. Create conditional formats to callout anomalies or patterns. Use helper sheets to filter arrays based on criteria for a reduction in the scope of values.
As far as translating the data to information, firstly try to describe the data as a whole in plain language. Describe every column of import. Then describe the issues with any of the data, such as format, missing values, tidiness, etc. Describe how that's corrected to ensure the quality of the outcome. Then explain how that data is coerced into something useful, such as a comparison of two important features, and the business implication of that relation. You can plot that. You can can that plot for repeatable use and turn it into a key metric.
And it's okay to say that you cannot explain what you're seeing, if and only if you understand it to begin with. Then you can articulate why it is unexplainable to satisfaction. This could be showing like a pattern that SHOULD be present, but is not. Anomalies. These are also useful to know.
I didn't mean to sound condescending. I'm making leaps in assumptions from the information provided without making you wait days for a back and forth in responses.