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No Code • Automated Deep Pattern Recognition • Conversational AI Voice Assistant • Plug & Play
DS
C

Report

Live Stream
LIVE STREAM
205 rows
4 features
45 ms
Throughput
260.8MB/s
Latency
13ms
Quality
99.8%
Data Quality
Before → After Cleaning
BeforeAfter45%98%
Outlier Detection
8 Anomalies Found
⚠ 3 outliers flagged
Pattern Discovery
Hidden Clusters Found
3 distinct patterns identified
Model Accuracy
Training Progress
100%75%50%96%Epochs →

Data Cleaning

Ready
customer_id
transaction_date
amount
currency
region
referral_code
device_type
session_duration
Drop (1)

Univariate

Ready
Mean
32.45
Median
33.53
Std Dev
4.12
Transaction_ValueNumeric
Peak: 33.5
0.00500.001000.00

Distribution Analysis

Ready

Gaussian Fit Test

Column: Age_Demographic

Passed (p > 0.05)
μ = 45
184580+

Outlier Detection

Ready
Mean
425.20
Std Dev
12.5
Anomaly
3
IDValueZ-Score
Row 8429,203.4+4.2σ
Row 10512.1-3.8σ

Bivariate Analysis

Ready
X-AXISMarketing_Spend
vs
Y-AXISRevenue_Q4
Pearson Correlation
+0.87

Customer Segmentation

Ready
3
Groups
High Value
Freq > 5/mo
45%
Loyalists
Tenure > 2yr
30%
At Risk
No Activity 30d
25%

Time Series Analysis

Ready
Decomposition: Multiplicative
Original
Trend
Seasonality

K-Means Clustering

Ready
Inertia: 452.1

Classification

Ready
Model
Accuracy
98.2%
F1 Score
0.97

Confusion Matrix

850True Positive
24False Positive
12False Negative
114True Negative

Predictive Forecasting

Ready
ARIMA
PROPHET
Forecast (30d)
+24.5%
High Confidence

Deep Chat Assistant

Ready
Agent Online

I've analyzed your forecasting model. The ARIMA parameters suggest a strong seasonal component in Q4. Would you like to adjust the seasonality prior?

You

Yes, set seasonality to 12 months and run the simulation again.

Running Simulation...
Type a message...
Highly abstracted and simplified demonstration of the actual application