In this article, you are going to learn data exploration AI class 9. In the previous article, we discussed data acquisition. After acquiring data, the next stage of the AI project cycle is data exploration. So here we begin!
If you missed previous article, go through the below given link:
So let’s start Data Exploration AI Class 9.
Data Exploration AI Class 9
So the first question comes in your mind is What is Data Exploration?
Data Exploration refers to the techniques and tools used to visualize data through complex statistical methods.
Advantages of Data Visualization
- A better understanding of data
- Provides insights into data
- Allows user interaction
- Provide real-time analysis
- Help to make decisions
- Reduces complexity of data
- Provides the relationships and patterns contained within data
- Define a strategy for your data model
- Provides an effective way of communication among users
Till now you learned about problem scoping and data acquisition. Now you have set your goal for your AI project and found ways to acquire data. When you acquired data the main problem with data is – the data is very complex. Because it’s having numbers. To make use of these numbers user need a specific pattern to understand the data.
For example if you are going to reading a book. You went to library and selected a book. The first thing you try to do is, just turning the pages and take a review and then select a book of your choice. Similarly, when you are working with data or going to analyze data you need to use data visualization.
Data Visualization Tools
There are many data visualization tools available. In next section of Data Exploration AI Class 9 we will discuss about them.
Here I made a list of 20 data visualization tools for you. Although there are many more tools available and these numbers increasing day by day.
- Microsoft Excel
- MS Power BI
- Google Data Studio
- Adaptive Discovery
- Teammate Analytics
- Dundas BI
- Google Charts
Do a small research and learn how to visualize your data with above tools.
In the next section of Data Exploration AI Class 9, we will see how to select a proper graph for data visualization.
How to select a proper graph for data visualization
Now you are familiar with various chart types. Now the next step is to select an appropriate chart for data visualization. The selection of chart all depends on the data and the goal you are going to achieve through your model. Although some basic purposes of charts that let you select an appropriate chart, they are as follows:
- Comparison of Values – Show periodical changes i.e. Bar Chart
- Comparison of Trends – Show changes over a period of time i.e. Line Chart
- Distribution of Data according to categories – Show data according to category i.e. Histogram
- Highlight a portion of a whole – Highlight data according to value i.e. Pie Chart
- Show the relationship between data – Multiple charts can be used
Now in the next section of Data Exploration AI Class 9, we will discuss a few activities given in your CBSE curriculum handbook.
Activity 1 – MS Excel
- Open MS Excel
- Prepare data of results
- Prepare 5 different types of charts and make a comprehensive report with these points
- Name of the chart
- Description of the chart
- How to draw it
- Suitable for which type of data
Activity 2 – Sketchy Graphs
Materials required – Chart Paper, Sketch-pens, Ruler, Basic stationery
In this activity, you have to make a graph on chart paper. You can select any chart to plot the data and draw them. Ensure that you are able to relate this graph to the goal of your project and describe the trends or patterns you have witnessed in your chart.
Watch this video form more understanding:
That’s all from Data Exploration AI Class 9 , if you have anything for me leave your comments!!!!