Understand the importance of dashboard and optimize business decisions

With the continuous development of data analysis and visualization technology, Dashboard has become one of the very important tools in enterprises. It helps companies better understand their business conditions and trends and allows managers to make decisions faster. In the process of optimizing business decisions, specific code examples are needed to implement Dashboard development and management.

Step One: Determine Indicators and Data Sources

Before creating a Dashboard, you need to clarify the indicators to be monitored and the data sources corresponding to these indicators. For example, if you want to monitor a company's sales, you need to determine whether the data source is an ERP system or other sales management tool. Only by clarifying these contents will it be possible to obtain a Dashboard that meets actual business needs.

Code example:

SQL statement: SELECT SUM(sales_amount) FROM sales WHERE date BETWEEN '20210101' AND '20211231'

Here we use the SQL statement to call Sales data for 2021 and calculate their sum.

Step 2: Choose appropriate visualization tools

Data in Dashboard is usually displayed in the form of charts, tables, etc., and different visualization tools need to be selected based on different indicators. For example, sales can be presented using bar charts, line charts, pie charts, etc., and different visualization methods can better reflect the characteristics of the data and make business decisions more accurate.

Code example:

Use Matplotlib in Python to draw a simple histogram. The code is as follows:

import matplotlib.pyplot as plt

sales_data = [...] 

plt.bar(['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'], sales_data)

plt.title('Monthly Sales in 2021')

plt.xlabel('Month')

plt.ylabel('Sales Amount')

plt.show()

Here we use Matplotlib to draw a simple histogram to show The sales volume for each month is determined and the sales trend is visually displayed.

Step Three: Add interactive functions to improve operational convenience

In the process of Dashboard development, the user’s interactive experience needs to be considered. For example, you may need to dynamically filter data, add paging functions, etc. These interactive features can greatly improve operational convenience and make it easier for users to obtain more comprehensive data dimensions.

Code example:

Use the Dash framework in Python to implement the interactive function of data filtering. The code is as follows:

import dash
import dash_html_components as html
import dash_core_components as dcc
from dash.dependencies import Input, Output

app = dash.Dash(__name__)

sales_data = [...] 

app.layout = html.Div([
   dcc.Dropdown(
       id='month-dropdown',
       options=[{'label': i, 'value': i} for i in ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']],
       value='Jan'
   ),

   html.Div(id='output-figure')
])

@app.callback(Output('output-figure', 'children'),
              Input('month-dropdown', 'value'))

def update_figures(selected_month):
   selected_month_data = sales_data[selected_month]
   figure = {
       'data': [
           {'x': ['A', 'B', 'C'], 'y': selected_month_data, 'type': 'bar'}
       ],
       'layout':{
           'title': f'Sales for {selected_month}',
           'xaxis' : {'title': 'Products'},
           'yaxis' : {'title': 'Sales Amount'}
       }
   }
   return dcc.Graph(figure=figure)

if __name__ == '__main__':
   app.run_server(debug=True)

Here we use the Dash framework to implement dynamic filtering Data functions. Users can dynamically switch between different months through selections in the drop-down menu, and can immediately see the sales data of the corresponding month.

Conclusion

The above are some basic steps and specific code examples of Dashboard development. Dashboard plays a very important role in corporate decision-making, helping companies understand the actual status of their business and make more accurate decisions. If you want to learn more about Dashboard development skills and applications, you can conduct in-depth learning through online learning platforms, communities, etc., and continuously improve your data analysis and visualization skills.

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