• Business process and application design for both B2B and B2C applications

• Ensure the process and applications are in GDPR, HIPAA compliant

• Extract and load into the data lake from ERP, Portal applications and third party data sources with tools including but not limited to AWS glue, Xplent, Talend,,Stitch, Informatica Power Center, Oracle Data Integrator, Skyvia, Fivetran, SAP Business object data integrator, mulesoft

Design to Data Collection

Uncover data value and equip the organization with data asset

• Strategy and goal setting of the data projects

• Design the data architecture that cater collection, analysis and modelling processes

• Integrate with the ERP systems to capture the key features with Extract, Load, Transform

Features Engineering

Discover, re-engineer and test the features that drive better predictions

• Data mining to extract features with domain knowledge

• Study relevancy of the features

• Transform the data optimal for machine learning

• Design the methodology for features learning

• Develop Model with Python, R and others data studio tools like google ML studio, AWS sagemaker, Azure ML, IBM Watson, Datarobot, Rapidminer

• Develop processes that accumulate train and test data set

• Generate more data set using different algorithms

• Optimize the performance using different models, hyper-parameters

Data model training & testing

Creating resilient models that empower decision under dynamic business environment

• Build data model to fit the business scenario

• Train the data model and validate the model using test dataset

• Optimize the modal to improve machine learning performance

Visualize the result & connect the digital ecosystem

Unleashing the power of the insight

Visualize both the data model training performance with different metrics like classification Accuracy, logarithmic Loss, confusion Matrix, area under Curve, F1 Score, mean Absolute Error, mean Squared Error

and the project it the business performance

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• Connect the predictions to the operation system and hence the business processes.

• Design operation, business and technical dashboards for business implications & technical fine tune.

• Set up the processes to enable follow-up on the insight

Automate the machine learning process

Machine learning with ease

• Automate the process from data feed, training to generate prediction

• Set up the configuration interface to adjust the business 

• Build up capability for the business and analytic team to master the data journey