Data Analytics ( Machine Learning and AI)

Our goal is to partner with you in your data journey and helping analyze your data so you can track what is important for your enterprise and predict your outcomes and prescribe your course of action so you can optimize your results and your bottom line. 

As part of partnering with you, we will help you identify you use cases, enable citizen data scientists within your organization and partner with you to create your data science models following the CRISP Methodology.  The ultimate goals of this is to have a model that  you can deploy to your enterprise or operational systems to help you make better decisions and what course of actions to take. 


 We follow the Cross-industry process for data mining to do our projects.  Our goal once we have a  good data model is to implement it using a PMML or deploy them to you operation systems so you  can make use of the rules produced in real time. Some of the tools, scripting languages that we have  used include:  

 Python   SAS  Statistica  SPSS 

 Some of the modeling techniques that we have used are: 

 CART Trees   Boosted Trees  CHAID Tree   Random Forest   Clustering   Link Analysis   Association Rules 


Data Integration and Engineering

Data Integration and Engineering is what makes data visualizations and data science models possible by moving data from  different source systems.  This is the process that we use when we partner with you to identify, transform and ingest your data to visualize and create your data models.

We have experience in the following: 

Our consultants have over 25+ years of experience in the following areas: 


 1) Data Management and Architecture 

Our data management process consists of a comprehensive consulting process to help identify your  use cases based on your needs, what data you have, gaps and opportunities, a comprehensive report  that includes a project plan with timelines and milestones, a cost analysis, and a schedule.  


The outputs from our data management process include:  

  Assessment , High Level project plan and Road Map    Data Architecture   Data Designs    Coding and Execution    Testing   Implementation

 2) Data Engineering and Integration using tools such as :  

 SQL   Informatica   SSIS  

3) Big Data  

 Hadoop   Vertica and other column based databases 

  Map Reduce  


Data Visualization

Part of your data journey is to have visualization to help tell your story. We can partner with you to create a visual representation of the data that tells the story of your data journey and in a visual context help you tell your story in a more efficient manner.


1) Data Visualization 

 Spotfire   Power BI   Tableau