Data Science Course > Project

Presenting Dashboard

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A dashboard is a graphical user interface that presents data in the form of charts, graphs, and tables. The main purpose of this type of dashboard is to provide a quick overview of the data and trends.

Dashboards are often used by managers to monitor their business and employees. They can also be utilized by sales managers to track their performance, or by HR managers for employee performance.

Dashboards are a way of displaying data that is easy to interpret. They are typically used in business analytics, and they can be used to help make sense of data.

Data science dashboards provide a way for companies to get insight into their data. They can use the insights from these dashboards to make better decisions, improve performance, and drive growth.

The following are some of the uses cases of dashboards:

  • Data scientists use them to monitor and analyze their progress.
  • Marketing teams can use them to visualize marketing insights and customer behavior trends.
  • IT professionals can use them to monitor their network operations and identify network issues.

Learner's Ratings

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V
vaibhav
5

best

A
Anjali
5

Excellent explanation

A
ashif mahiboob yadwad
5

Very good

S
SHAIKH TOHEED
5

good but practical knowledge not perfect

P
PUSHPAK DILLIP MALI
4

The content and teaching style is excellent. But there is slight issue is that video quality is kind of poor the dashboard is blur on 720mp on PC.

S
Sayali Jadhav
4

Very useful all data

S
Syed Mohammad Qaiser Rizvi
5

Way of teaching is very good. I want to get PPT which he is using to teach us ?

A
Anuja Bagadi
5

It is a very interactive and useful course..

K
Kashinath Myakale
5

All courses is very useful for which are looking free courses and gaining knowledge

A
ANKiT KUMAR BAMNiYA
4

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  2. Types of Variables in Data Science
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  3. Levels of Data Measurement in Data Science
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  1. Charts and Graphs 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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  2. Kurtosis in Data Science
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  3. Box and Whisker Plots in Data Science
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  2. Statistical Hypothesis in Data Science
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  3. Errors in Statistical Hypothesis in Data Science
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  8. Residual Analysis of Model Part 3 in Data Science
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  3. Example of Hierarchial Clustering 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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