1. Studying the problem
As with any project, we start by studying your product needs or business challenges, documenting requirements and your vision of a solution to connect data and value.
2. Exploratory data analysis
Then, as any data science endeavor suggests, we review your current data infrastructure and explore datasets to find anomalies, missing values, dependencies, and patterns.
3. Data preparation
Before modeling, we prepare data by cleansing it and transforming into a unified format.
4. Data modeling and evaluation
Our data scientists train numerous models to define which one of them provides the most accurate results. Then we choose the best model in terms of accuracy of results, simplicity, and performance.
5. Designing the solution
Be it a BI product, a machine learning algorithm, or a data management solution, we engineer, integrate, and test your product, as you start adjusting to your new innovative capabilities.
6. Support and maintenance
We maintain your growth by helping you release new features, introduce more tools and data sources, and integrate the product further in the workflow. We seek long-term client/vendor relationships where common progress supports our mutual development