Notebook / Advanced Analytics
Advanced Analytics
on Contextualized Industrial Data
Tier0 Notebook gives engineers and analysts a powerful workspace to explore, calculate, and visualize, and operationalize industrial data directly on top of the Unified Namespace. From root cause analysis to predictive models, insights no longer stay in spreadsheets or isolated scripts.
Not just dashboards. Real industrial analysis that can be reused in operations.
0
10
20
30
40
50
60
70
80
90
100
Temperature (°C)
0
5
10
15
20
Vibration
0
5
10
15
20
25
30
35
40
0
10
20
30
40
50
60
Signal
0
10
20
30
40
50
60
70
80
90
Var A
0
10
20
30
40
50
60
70
Var B
−1
0
1
Sample
// Scatter + regression · smooth series
"pts = alt.Chart(df).mark_circle(color="#c8ea5f", size=50).encode(
x="temp_c:Q", y="vibration:Q",
)
reg_line = alt.Chart(df).transform_regression(
"temp_c", "vibration"
).mark_line(color="#8ab52d", strokeWidth=2).encode(
x="temp_c:Q", y="vibration:Q",
)
smooth = alt.Chart(series_df).mark_line(
point=True, color="#c8ea5f", interpolate="monotone"
).encode(x="t:Q", y="y:Q")
scatter_reg = pts + reg_line
Live Analysis
Connected to UNS
Notebook / Advanced Analytics
Advanced Analytics
on Contextualized Industrial Data
Tier0 Notebook gives engineers and analysts a powerful workspace to explore, calculate, and visualize, and operationalize industrial data directly on top of the Unified Namespace. From root cause analysis to predictive models, insights no longer stay in spreadsheets or isolated scripts.
Not just dashboards. Real industrial analysis that can be reused in operations.
0
10
20
30
40
50
60
70
80
90
100
Temperature (°C)
0
5
10
15
20
Vibration
0
5
10
15
20
25
30
35
40
0
10
20
30
40
50
60
Signal
0
10
20
30
40
50
60
70
80
90
Var A
0
10
20
30
40
50
60
70
Var B
−1
0
1
Sample
// Scatter + regression · smooth series
"pts = alt.Chart(df).mark_circle(color="#c8ea5f", size=50).encode(
x="temp_c:Q", y="vibration:Q",
)
reg_line = alt.Chart(df).transform_regression(
"temp_c", "vibration"
).mark_line(color="#8ab52d", strokeWidth=2).encode(
x="temp_c:Q", y="vibration:Q",
)
smooth = alt.Chart(series_df).mark_line(
point=True, color="#c8ea5f", interpolate="monotone"
).encode(x="t:Q", y="y:Q")
scatter_reg = pts + reg_line
Live Analysis
Connected to UNS
What it is
A notebook built for industrial data work
Traditional analytics often start with exporting data, cleaning it manually, and rebuilding context outside the factory system.
Tier0 Notebook works directly on structured industrial data inside the platform. Built on the same Unified Namespace and application foundation as the rest of Tier0, it helps engineers and analysts analyze faster and turn results into reusable operational capability.
RAW DATA SOURCES
EDGE
MES
HISTORIAN
...
Tier0 platform
Contextualized UNS
CONTEXTUALIZED
DATA LAYER
NOTEBOOK ANALYSIS
tag
μ
σ
Line1.Temp
41.2
0.31
Batch.Vib_rms
2.04
0.12
Group by asset and time window, join historian tags with MES context, and plot drift in one cell.
Code
df.groupby(["asset","shift"])
.agg({"v": ["mean","std"]})
Charts
ALERTS
APPS
AI MODELS
DASHBOARDS
...
Work on UNS based
industrial data
No exports, no rebuilt context. Start from structured, live industrial data.
Combine code, charts, logic,
and explanation
A unified notebook environment for analysis, visualization, and decision logic.
From analysis
to app
Insights can directly feed operational apps, workflows, or decision support.
Turn analysis into
operational capability
Results can feed apps, alerts,
workflows, and AI models.
What it is
A notebook built for industrial data work
Traditional analytics often start with exporting data, cleaning it manually, and rebuilding context outside the factory system.
Tier0 Notebook works directly on structured industrial data inside the platform. Built on the same Unified Namespace and application foundation as the rest of Tier0, it helps engineers and analysts analyze faster and turn results into reusable operational capability.
RAW DATA SOURCES
EDGE
MES
HISTORIAN
...
Tier0 platform
Contextualized UNS
CONTEXTUALIZED
DATA LAYER
NOTEBOOK ANALYSIS
tag
μ
σ
Line1.Temp
41.2
0.31
Batch.Vib_rms
2.04
0.12
Group by asset and time window, join historian tags with MES context, and plot drift in one cell.
Code
df.groupby(["asset","shift"])
.agg({"v": ["mean","std"]})
Charts
ALERTS
APPS
AI MODELS
DASHBOARDS
...
Work on UNS based
industrial data
No exports, no rebuilt context. Start from structured, live industrial data.
Combine code, charts, logic,
and explanation
A unified notebook environment for analysis, visualization, and decision logic.
From analysis
to app
Insights can directly feed operational apps, workflows, or decision support.
Turn analysis into
operational capability
Results can feed apps, alerts,
workflows, and AI models.
Why it matters
From data visibility to actionable intelligence
Seeing data is not the same as understanding it.
Most factories already have reports and dashboards, but when teams need to answer deeper questions-why yield dropped, what changed before a failure, which variables affect quality, how to optimize a process-they still rely on manual extraction, offline analysis, and fragmented tools.
Tier0 Notebook closes this gap by giving teams a native environment for advanced analytics, where industrial context, analysis logic, and business output stay connected.
Why it matters
From data visibility to actionable intelligence
Seeing data is not the same as understanding it.
Most factories already have reports and dashboards, but when teams need to answer deeper questions-why yield dropped, what changed before a failure, which variables affect quality, how to optimize a process-they still rely on manual extraction, offline analysis, and fragmented tools.
Tier0 Notebook closes this gap by giving teams a native environment for advanced analytics, where industrial context, analysis logic, and business output stay connected.
Use Cases
Typical use cases
Predictive Maintenance
Use historical and live equipment data to predict failures, detect anomalies, and support maintenance planning.
Quality Analysis
Correlate process parameters with quality outcomes to find root causes and optimize yield.
Process Optimization
Identify better operating conditions across recipes, materials, and machine settings.
Energy & Utility Analysis
Analyze consumption patterns, detect waste, and benchmark efficiency across operations.
Production Performance Analysis
Track OEE, throughput, downtime, and cycle time using contextualized production data.
Cross-System Data Investigation
Combine data across MES, SCADA, ERP, historians, and other systems to investigate complex events.
Use Cases
Typical use cases
Predictive Maintenance
Use historical and live equipment data to predict failures, detect anomalies, and support maintenance planning.
Quality Analysis
Correlate process parameters with quality outcomes to find root causes and optimize yield.
Process Optimization
Identify better operating conditions across recipes, materials, and machine settings.
Energy & Utility Analysis
Analyze consumption patterns, detect waste, and benchmark efficiency across operations.
Production Performance Analysis
Track OEE, throughput, downtime, and cycle time using contextualized production data.
Cross-System Data Investigation
Combine data across MES, SCADA, ERP, historians, and other systems to investigate complex events.
AI Ready
A stronger foundation for industrial AI
AI is only as useful as the data and context behind it. Tier0 helps teams structure industrial data, connect it to operational context, and build a stronger foundation for analytics, AI, and AI-assisted applications. Instead of treating AI as a separate experiment, Tier0 makes industrial data more reusable, analysis more reliable, and AI adoption more practical.
Contextualized Data → Advanced Analytics → AI-Ready Operations
AI Ready
A stronger foundation for industrial AI
AI is only as useful as the data and context behind it. Tier0 helps teams structure industrial data, connect it to operational context, and build a stronger foundation for analytics, AI, and AI-assisted applications. Instead of treating AI as a separate experiment, Tier0 makes industrial data more reusable, analysis more reliable, and AI adoption more practical.
Contextualized Data → Advanced Analytics → AI-Ready Operations
STAY UP TO DATE WITH PRODUCT UPDATES, LEARNING RESOURCES, AND MORE.
Singapore · Hangzhou China
About FREEZONEX
© 2026 FREEZONEX • All Rights Reserved
solutions
STAY UP TO DATE WITH PRODUCT UPDATES, LEARNING RESOURCES, AND MORE.
Singapore · Hangzhou China
About FREEZONEX
© 2026 FREEZONEX • All Rights Reserved