Data Science derives meaningful insights to grow your business from the data in action!. Data Science is an iterative process, where the system needs to learn from the data iteratively to provide more valuable business insights.
We are in a data-driven world, petabytes of data are being generated daily, not all the data might be useful, but there needs to be a concrete process to derive insights useful for your business and there comes PRONIX into rescue.
The world is rapidly moving from the age of data mining to data science to derive meaningful insights from your data.
At PRONIX we transform your data to provide meaningful insights to grow your business by systematically applying the concepts of data science.
Data science unifies all the fields of data i.e, Data Engineering, Data Analytics & Artificial Intelligence.
Data Engineering- Data in any form Structured or Unstructured, Data Engineering makes your data consumable & actionable! Without data engineering, there is no data science that can be applied to your data. Data Engineering builds a scalable pipeline to engineer your data iteratively.
What do we do in Data Engineering?
- Understand your Business
- Data Collection
- Data Cleaning
- Data Enrichment
- Data Exploration
- Data Storage
Data Analytics- Data Analytics makes you understand your data & your business before making a machine understand your data. Data Analytics gives better decision-making capabilities for a business.
What do we do in Data Analytics?
- Data Inspection
- Data transformation
- Data modeling
- Data visualization
Artificial Intelligence- Artificial Intelligence in short form AI is sub branched into two Machine Learning & Deep Learning. Depending on the data any of Machine Learning or Deep Learning algorithms are applied to the data and prepare a model. Artificial Intelligence applied on consumable/actionable data makes a machine more intelligent by learning from your data and allows to provide more valuable insights & valuable predictions to grow your business.
What do we do in AI?
- Data gathering
- Feature Engineering
- Model Selection
- Model Training
- Model Evaluation
- Hyperparameter Tuning
- Predictions to derive insights