Data Science Course > Project

Slicers in Dashboard

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A slicer is a type of chart that displays data in a range of values. It can be used to compare different types of data and find the best way to visualize it.

Slice is a data visualization tool that enables users to extract information from a single chart. The tool allows the user to select a range of time and date values and then gets the slice of data for them.

Dashboard comes with a wide range of different types of slicers. Some are used for filtering based on specific fields, some are used for grouping data, and others are used for comparing two sets of data.

Some benefits of using a slicer in the dashboard are:

  • Quickly find relevant information from a large amount of data
  • Easily filter out irrelevant information
  • Save time by not having to search through the whole data set

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Nishant Saxena
5

great content

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Aditya Purohit
5

Very good course & amazing cocepts & detailed explaination of each and every thing . Thanku soo much Learn Vern ...

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Abinash prusty
5

Good

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Shivendra Shahi
5

Amazing

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Ashmit Raj
5

Very good course for begineers.

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NAGASWETHA
5

good explanation

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Bharkha Bhambhani
4

excellent

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Umesh Kumar Pandey
5

nice

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Luckyrani Sahu
5

best

R
Ragini Reddy
5

can explain more about level of management would help of more understanding

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  3. Levels of Data Measurement in Data Science
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  2. Frequency Distribution in Data Science
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  3. Bar Graphs and Pie Charts in Data Science
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  4. Summarizing Quantitative Data in Data Science
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  5. Cummulative Distribution in Data science
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  6. Histogram and Scatter Plot in Data Science
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  7. Cross Tabulation in Data Science
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  1. Measures of Central Tendency and Variability in Data Science
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  2. Mean and Percentiles in Data Science
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  3. Quartiles in Data Science
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  4. Measures of Variability in Data Science
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  5. Variance and Standard Deviation in Data Science
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  6. Application of Standard Deviation in Data Science
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  7. Z-score and Co-efficient of Variation in Data Science
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  8. Measures of Central Tendency for Grouped Data in Data Science
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  2. Kurtosis in Data Science
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  1. Hypothesis Testing in Data Science
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  3. Errors in Statistical Hypothesis in Data Science
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  4. Statistical Inference for Single Population in Data Science
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  1. R Programming in Data Science
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  5. Example of K Means Clustering in Data Science
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  1. Theoretical Concepts of Dashboard
    5m 41s
  2. Creating Pivots and Preparing Charts
    5m 36s
  3. Slicers in Dashboard
    3m 27s
  4. Preparing Final Dashboard
    8m 20s
  5. Presenting Dashboard
    3m 2s
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