Data Science

With over 30 years of experience in Data Management, Analytics we provide services to bring the business users and Data Scientists together to achieve better results.
Communication, Expectation Management, Lack of technical understanding are often the key points to failure in “Data science” projects

We help to add Business focus of Data Science matters

Focusing the data science teams on the business needs. Effectiveness goes before technical beauty
Engage Data Science teams with the business needs, constraints and risks
Defining metric for success and safety *
Data Science modules can have a direct impact on the data and process they are meant to track and improve. Cleary defining what the success of any module will be is important to measure the effectiveness. As the data/process is influenced by the module how do we validate that it is still valid and has the intended impact. How to make sure the module is safe and will not dangerous in the case of unexpected events or values beyond the accepted scope.

Business user Data Science awareness training for better understanding and communication
Data Scientist awareness training of business needs, risks, methodologies

We help design and apply processes to Test, Validate and understand the answer of the Data science projects

Clearly state the business expectation
Identify and list clearly the Data Science design considerations
Define Test and Validation scenarios to promote only accurate modules
Life-cycle of data science development. Time based revalidation identify changes in behavior
Define metrics to tracks Data Science effectiveness to avoid false results

Auditing and Data Science methodology for risks in the data quality and processes

Based on our years of experience in Regulated Life Science provide better management of the data Science processes
Audit the current process to highlight areas for improvement and risks
Define procedures and framework to manage risks associated with Data Science projects
Balance agility with risk and a structured process to manage Data Science