In today’s data-driven world, businesses are constantly seeking ways to unlock deeper insights from their enterprise data. SAP, a leader in enterprise resource planning (ERP) S/4 HANA Private Cloud, Public Cloud..etc, holds vast amounts of structured business data. Databricks, a unified data analytics platform, excels at processing and analyzing large-scale data. Plotly, a powerful visualization library, brings those insights to life with interactive dashboards.
Together, these SAP Databricks and Plotly form a deadly match—not in destruction, but in delivering killer analytics.
Get Started
Go to your Workspace – Right Corner Click Create and Select Notebook
Install the required Python libraries to get working on your analytics Model
Why This Trio Works So Well
SAP: The source of truth for business operations—finance, supply chain, HR, and more.SAP Databricks: The engine that transforms raw SAP data into usable insights using Apache Spark and Delta Lake.Plotly: The artist that paints the picture, turning numbers into interactive, decision-ready visuals.
Example 1: Supply Chain Optimization
Scenario: A company wants to analyze delivery delays across regions.
SAP: Extract delivery logs and order data using SAP Data Intelligence or OData services.Databricks: Clean and join datasets, apply machine learning to predict delays.Plotly: Visualize delay trends by region, product category, and carrier.import plotly.express as px
import pandas as pd
# Sample data
df = pd.DataFrame({
“Region”: [“North”, “South”, “East”, “West”],
“Avg_Delay_Days”: [2.5, 3.1, 1.8, 4.0]
})
fig = px.bar(df, x=”Region”, y=”Avg_Delay_Days”, title=”Average Delivery Delay by Region”)
fig.show()
Example 2: Financial Forecasting
Scenario: CFO wants to forecast quarterly revenue using historical SAP financial data.
SAP: Pull GL and revenue data.Databricks: Apply time series forecasting models (e.g., Prophet).Plotly: Display forecast vs. actuals with confidence intervals.import plotly.graph_objects as go
# Sample forecast data
quarters = [“Q1”, “Q2”, “Q3”, “Q4”]
actuals = [100, 120, 130, 150]
forecast = [105, 125, 135, 160]
fig = go.Figure()
fig.add_trace(go.Scatter(x=quarters, y=actuals, mode=’lines+markers’, name=’Actual’))
fig.add_trace(go.Scatter(x=quarters, y=forecast, mode=’lines+markers’, name=’Forecast’))
fig.update_layout(title=”Quarterly Revenue Forecast”, xaxis_title=”Quarter”, yaxis_title=”Revenue (in M€)”)
fig.show()
Now it’s your turn to innovate—unlock the full potential of your data, drive smarter decisions, and shape the future of your enterprise.
The tools are in your hands—go build something extraordinary!
To build on your stack A Hint:
Use SAP Data Intelligence or SAP BW connectors to extract data.Load into Databricks Delta Lake for scalable processing.Use Plotly Dash or Plotly Express for visualization in notebooks or web apps.
Conclusion
The combination of SAP, Databricks, and Plotly empowers organizations to go from raw data to actionable insights—fast. Whether you’re optimizing operations, forecasting finances, or understanding your workforce, this trio delivers clarity, speed, and impact.
Follow me for more updates – https://profile.sap.com/u/Yogananda
In today’s data-driven world, businesses are constantly seeking ways to unlock deeper insights from their enterprise data. SAP, a leader in enterprise resource planning (ERP) S/4 HANA Private Cloud, Public Cloud..etc, holds vast amounts of structured business data. Databricks, a unified data analytics platform, excels at processing and analyzing large-scale data. Plotly, a powerful visualization library, brings those insights to life with interactive dashboards.Together, these SAP Databricks and Plotly form a deadly match—not in destruction, but in delivering killer analytics.Get StartedGo to your Workspace – Right Corner Click Create and Select NotebookInstall the required Python libraries to get working on your analytics ModelWhy This Trio Works So WellSAP: The source of truth for business operations—finance, supply chain, HR, and more.SAP Databricks: The engine that transforms raw SAP data into usable insights using Apache Spark and Delta Lake.Plotly: The artist that paints the picture, turning numbers into interactive, decision-ready visuals.Example 1: Supply Chain OptimizationScenario: A company wants to analyze delivery delays across regions.SAP: Extract delivery logs and order data using SAP Data Intelligence or OData services.Databricks: Clean and join datasets, apply machine learning to predict delays.Plotly: Visualize delay trends by region, product category, and carrier.import plotly.express as px
import pandas as pd
# Sample data
df = pd.DataFrame({
“Region”: [“North”, “South”, “East”, “West”],
“Avg_Delay_Days”: [2.5, 3.1, 1.8, 4.0]
})
fig = px.bar(df, x=”Region”, y=”Avg_Delay_Days”, title=”Average Delivery Delay by Region”)
fig.show()Example 2: Financial ForecastingScenario: CFO wants to forecast quarterly revenue using historical SAP financial data.SAP: Pull GL and revenue data.Databricks: Apply time series forecasting models (e.g., Prophet).Plotly: Display forecast vs. actuals with confidence intervals.import plotly.graph_objects as go
# Sample forecast data
quarters = [“Q1”, “Q2”, “Q3”, “Q4”]
actuals = [100, 120, 130, 150]
forecast = [105, 125, 135, 160]
fig = go.Figure()
fig.add_trace(go.Scatter(x=quarters, y=actuals, mode=’lines+markers’, name=’Actual’))
fig.add_trace(go.Scatter(x=quarters, y=forecast, mode=’lines+markers’, name=’Forecast’))
fig.update_layout(title=”Quarterly Revenue Forecast”, xaxis_title=”Quarter”, yaxis_title=”Revenue (in M€)”)
fig.show()Now it’s your turn to innovate—unlock the full potential of your data, drive smarter decisions, and shape the future of your enterprise. The tools are in your hands—go build something extraordinary!To build on your stack A Hint:Use SAP Data Intelligence or SAP BW connectors to extract data.Load into Databricks Delta Lake for scalable processing.Use Plotly Dash or Plotly Express for visualization in notebooks or web apps.ConclusionThe combination of SAP, Databricks, and Plotly empowers organizations to go from raw data to actionable insights—fast. Whether you’re optimizing operations, forecasting finances, or understanding your workforce, this trio delivers clarity, speed, and impact. Follow me for more updates – https://profile.sap.com/u/Yogananda Read More Technology Blog Posts by SAP articles
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