Data, Data Everywhere
We work with organizations at all stages of data and analytics maturity to drive smarter decisions, enable faster actions and optimize operations.
Organize Your Data for Success
Our data management framework will enable technology departments to optimize investments in data management and will enable business users to structure data around business issues for faster contextual analytics.
Data governance includes creation of data strategy, business-driven data policies, cross functional processes, data definitions, business rules, data access and privacy policies.
]Data integration services bring together data from disparate sources to generate new insights e.g. Retail data is merged with supply chain data to provide opportunities for channel optimization.
Data transformation services generate new insights from existing data e.g. unstructured social media data can be converted to structured data for faster insights on social media trends.
Generate Actionable Insights
Data mining models are group into 3 categories based on the nature of business questions and the statistical techniques used.
Descriptive modeling identifies hidden associations in data by using statistical tools and techniques e.g. behavioral segmentation to identify customers with similar usage patterns so that marketing offers can be targeted to the right customers.
Predictive modeling identifies associations in past data to predict the likelihood of future events e.g. a logistic regression based predictive model to identify the probability that a customer will cancel their service within the next billing cycle.
Prescriptive modeling recommends a course of action based on cause and effect relationships in data e.g. a media mix optimization model aimed at minimizing advertising cost while achieving the targeted audience per channel.
DATA SCIENCE CONSULTING
Implement Best Practices
Assess the maturity of your data science capability against industry benchmarks. Identify strategies and best practices to achieve a higher maturity level.
Data Science Roadmap
Create a vision for your organization and identify the projects, dependencies, resources and skillset to create business impact and achieve data science leadership.
Industry Use Cases
Identify and manage results driven initiatives to demonstrate business value of data science and gain stakeholder support for investments in data science capabilities.