Our Consultants define the analytic question, Gather data using external API’s, public data sources, etc., Conduct Extensive descriptive analytics on the newly collected data, including visualization.
Our Data Scientists approach problems with this process:
- Our Consultants define the analytic question
- Gather data using external API’s, public data sources, etc.,
- Conduct Extensive descriptive analytics on the newly collected data, including visualization
- Use the right machine learning or statistical modeling techniques to produce insight and better decisions
- Operationalize these models so they can run in an automated context
We do this by working with these:
- NoSQL (Graph, Document, Columnar) database models, XML, relational and other database models and associated SQL;
- ETL tools and techniques, such as tools like Talend, Mapforce
- statistical modelling, algorithms, data mining and machine learning algorithms such as k-NN, GBM, Neural Networks Naive Bayes, SVM, and Decision Forests
- NLP and text based extraction techniques; also computer vision and signal processing
- data science packages including Spark, Pandas, SciPy, and Numpy
- Deep learning with Keras and TensorFlow
- Visualization tools such as Tableau and PowerBI
