Data Analysis and Artificial Intelligence
Artificial Intelligence (AI) plays a crucial role in data analysis by providing a simple interface to extract insights from large and complex data sets. With its ability to process natural language quickly, AI helps people make better-informed decisions, identify patterns and trends, and uncover hidden insights that might otherwise go unnoticed. In DvSum users have the ability to talk to their data using Conversational AI for Data-Driven Insights (CADDI). DvSum CADDI makes it effortless to interact with your data, understand it, and extract reliable insights.
How to talk to the data in DvSum Data Catalog:
Before we start chatting with data, first we need to create a topic and share it with some users. Here I have a chat topic shown below which I have shared with the user. Go to the chat topic detail page and follow the steps below to see how we can share the topic with some other users.
Once the chat topic is shared, click on "Talk to Your Data" from the left Nav. It will open the Conversational page on a new tab.
Now in the Conversational tab, all the analyses that are shared with some users will appear as topics. So we need to select some topic in order to start the conversation. I'm selecting the topic which I shared above.
Once the topic is selected, an About section of that chat will appear on the new chat which will contain details of the topic i.e. that chat topic is created for which dataset, who are the owners of that dataset, etc.
Click on the "Sample Data" button and it will show the sample data of that data set.
From the sample data user can have some basic insights of what data is about and how it looks like. Users can select different columns and apply filters to check the results.
Once sample data is explored generically, now users can move forward by asking different questions to have more to-the-point insights into the data. In the current example I have selected the Order History table so I will try asking questions to explore data further as shown below.
Here is the result that I got.
The result shown above shows a line chart of the insights for which the question was asked. It shows the insights in graphical form of all the orders that were placed recently in the current month. In order to see the results in the form of a grid then click on the "Toggle View" button as shown below and it will also show a grid view of the results.
The type of chart depends on what query is generated from the question and what results are fetched. If datetime column and metric count in results is greater than or equal to 1 then the line chart will show up as shown in the case above. Whereas if datetime column count is 0 and the attribute and the metric count are greater than or equal to 1 then the Bar chart will show up as shown in the example below.
Whereas if results just show one row and column then the Tile chart will show up as shown below.
Users can also change the topic within the chat. Click on the topics button and it will show up all the topics. Select any and it will show its About section.
How to set a context for a question:
When some question is asked and results show up, click on "Saving the context" button on the top right as shown below.
Once the context is saved, "Using this context" button will appear with the question field as shown below which will show all the contexts which are saved. Multiple contexts can be saved.
In order to remove the context, click on the "Clear Context" button. It will remove all the added contexts.
How Summarize Chat works:
The "Summarize Chat" button appears with the question field. Click on it and it will summarize the whole chat. It summarizes on the basis of questions that were asked earlier. Summarize chat depends on the questions which involve sum, average, maximum, or minimum values. It summarizes those questions and shows some recommendations.
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