Causal Modelling – Expansive Solutions

Y=ax1+bx2+cx3+d

CozX : Multivariate Causal Modelling

Any target study variable (dependent) could be affected by several other variables (independent). Develop Insights into how strongly they are associated and combinations of which variables explains the target variable best.

Digital enablement

CozX : Multivariate Causal Modelling Solution

Benefits

Insights: Patterns & Associations,
Inferences: Cause & Effects,
Predictions: Certainty in Business.

Metrics

Strength of Association,
Error Reduction / Accuracy,
Reduced Bias/ Reliability.

Challenges

Too many variables,
Relationships not known,
Subsets/Segments in data,
Algorithms are complex,
Interpretation is difficult.

Study is Hard!

Data cleanliness,
Interaction between variables,
Type I/II error,

Key Features

Data preparation,
Multiple studies,
Rich Insights Data, Models, Results,
Visualizing ML Models-SHAP, LIME

Utilities

Big Data Summarizing,
Feature Engineering,
Parallel Processing,
Data Pipeline Process Queues,

The Technology

Complete studio toolkit with

Data Engineering,
Data Scientist,
End Users.

Best in Class

Integration

Easy Data Integration, Data Validation, Scheduled Jobs.

Human-System-Data

Interface Data from ERP, CRM, Weather, Social Media, Excel Import.

User Experience

Rich UI-UX, Multi-Device, Blazing Fast.

Intuitive | Performance

Visualizing Data Quality, Slicing, Dicing, Normality, Multivariate Interactive Charts, SHAP, LIME, Partial Dependencies.

On-Prem + Cloud

Deployment Options

Modular & Flexible

Cloud / On-Prem

Full Scope / Embed As Service

Flexi Licensing

By Module, User, Site or Time Subscription,

Several Options

Perpetual, Subscription, Site based, Sizing, Module Specific

Applying Technology

CozX : Use Cases

All
Marketing
Trading
Finance
Governance
Research
Maintenance
Quality
Exploration

Medical Research

Drug Studies always use Design of Experiment method to study efficacy of drug on different study groups and need fact based, accurate and reliable conclusions from these studies.

XSight Causal modelling help them to easily upload data, setup multiple study hypothesis and draw conclusions.

Price Forecasting

Price prediction study and careful modelling of several factors as it is very difficult to reliably predict price as a function of time.

Sophisticated management and curation of data, algorithms from the discipline of statistics and machine learning and experience can build robust systems.

Predictive Maintenance

OEM guidance on carrying out Preventive Maintenance can vary greatly on either side. Sooner than prescribed MTBF can result in loss time in operations and later would mean cost, waste and unnecessary loss of productive time.

Equipment's need for preventive maintenance can be determined by use of conditions data from sensors around. Image, Vibration, Sound, Material viscosity, temperature, Humidity data are captured for key equipment's, but not often put to good use.

Budgeting Governance

Budget preparation is a highly collaborative and involved process. Mutli dimensional and multiple impacts needs balancing. Such activities require right modelling and predictions.

XSight Causal Modelling helps right situation assessment, predictions for best budgeting and governance.

Quality Assurance

Measuring Quality parameters and predicting through pattern in control charts can help addressing Operational challenges proactively.

Research & Development

Ranging from simple data exploration, Hypothesis testing on efficacy of treatment to building complex causal models data science can help them all. Almost all walks of life can benefit from data insights and predictions.

Exploratory Research

Finding pattern in data and associations, impact of events on demand (or other data of interest) provides insights and helps taking right decisions.

Pandemic Research

Study of new disease, its impact on demography and economy.

Y=ax1+bx2+cx3+d

CozX : Multivariate Causal Modelling