1. Data science Consultancy Services
We help businesses achieve their objectives using machine learning and statistical modelling techniques. Also, we help clients to realise the powerful potential from their extensive databases. We work with our clients to solve their most complex data handling issues via delivering strategy and implementation solutions from a business and technology perspective.
Our customer analytics services will help you gain a single customer view and make business decisions about customer acquisition and retention.
2. Data assessment
Understanding the status of your customer data opens new possibilities for data-driven decisions that can dramatically improve the customer experience.
We can use data and statistical models to make inferences about the past.
We use the scientific method to answer hypotheses, enabling you to understand your decisions' impact and learn more about your market and customers.
3. Data curation
In today's competitive environment, businesses seek innovative and powerful ways to use the technology to meet today's modern business requirements. Our Data Science team members can help clients to realise the powerful potential from their extensive databases. However, all the tasks from reading, validating, cleansing, and correcting data to integration and reporting are wrapped up in separate processes.
4. Analytics and data science
We assist our clients to confidently navigate business goals to increase revenues, reduce customer churn, and helping them to use their customer data. Our Data Scientist team using descriptive, predictive, and prescriptive analytics and machine learning to ensure our clients meet their KPIs.
Machine learning models identify patterns and trends concealed in data. The signal in the noise. We can use these models to make predictions about the present and forecasts of the future.
We can use this knowledge to optimise decision making and simulate scenarios.
Predictive models can save time, improve customer satisfaction, boost demand for your products and services and make your organisation more efficient.
The Data Science project cycle : -
- Understand the client requirements and the challenges
- Setting an expectation with a client on what success looks like
- Assess the data from respective processes/systems and understand the technical infrastructure
- Explore and visualize the data to get a high-level overview of the data.
- Frame the problem as a mathematical/statistical model.
- Iteratively build models, improving performance and ensuring client understanding and trust.
- Deploy the model on the cloud
- Build a secure, user-tested web-based application the client can use to generate model results and simulate decision scenarios.
- Write documentation.