We Work in Your Environment
Planning the framework
We Work in Your Data World
An adjunct to your staff
We Build Your Data Story
Adding value by building the analytics production pipeline
We have the right solutions
Analytics Planning, Modeling and Data Architecture
Customized and Enduring Analytics Production
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Managing Planned Results, Predictive Analytics, Governance and Implementation
Transform Data Into Insight
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Our Main Services
Our success is built on customer satisfaction and partnership with our clients. We have served in roles such as data scientist, analytics manager, statistical scientist, SAS developer, strategic guide, predictive and prescriptive modeler, trainer and presenter.
Strategic Planning
Strategic management of study and analytics production system.
Planning of pipeline to target data mart, data lake and business intelligence framework.
Analytics Data Architecture
Plan data architecture and pipeline with team within business process on premises or in the cloud. Check and evaluate best practices for short and long-term company or institutional goals.
Predictive, Exploratory and Prescriptive models
Build and render Insights for Business Intelligence users and customers. Build needed Predictive models including visualizations, model fit, evaluate study results against plans, diagnostics, socialization and training customer analysts. Deliver Time Series Forecasting, Diagnostic Models,Text Mining, Experiment Design, Machine Learning and Classical Statistical Models as needed.
Set-up Analytics and Demo Methods and Tools
Implement plans for Data Integration, Data Base, and Analytics Data Mart framework or dataset environment. Test R, SAS, Python code to evaluate Statistical Analysis, Data Mining, Machine Learning, against study objectives to ensure objectives, measurements and metrics will reflect desired outcomes. Test, demonstrate to ensure data science suite will deliver and tell the right story.
Data Management, Analytics Data Architecture and Pipeline
Load, Clean, design, engineer data management, statistical computing, transformations, dev ops, data quality control, data wrangling, pipeline repositories are as planned to ensure production objectives. Code, demonstrate or innovate needed tool sets, albeit on-premise or cloud services. Develop R, Python or SAS development environment(s) in pipeline to specifications.
Evaluate Model Results and Final Statistical Inference
Deliver insights, coach users to take action based on data analyses and predictive modeling results; empower customers to use results to close the loop. Transfer knowledge and best practices of Forecasting, Text mining, Machine Learning, Causal Models and other methods.
