Data Science & Analytics
At Pushti, we run-throughprofessional Data Science practice in transforming large / small volume of business data into useful business insights.It empowersour customers to improve business processes and decision support systems.
Succeeding this professional Data Science practice, we understand the business problems, develop appropriate algorithms and delivering key decision makings to stakeholders that improve their decision making capabilities.
The Pushti team is capable to create visualizations of complex & unstructured data in high quality data, having following characteristics:
- Consistency of the data
- Accuracy of the data
- No Noisy data
- Replacing missing data with appropriate data
- Managing Outliers (data that lies an abnormal distance from other value)
- No Bias data
- Handling Variance in the data
This approach helps us in delivering following benefits to the customer.
An example of Data Science practice using AWS SageMaker.
Customer was having large volume of data with varied format and the challenge was to integrate and analyse the data of different formats to create the database schema for further ML processing.
We applied AWS SageMaker with its following utilities to prepare the clean and unbiased data, followed by creating Dataset Schema.
- Amazon SageMaker Clarify
- Amazon SageMaker Data Wrangler
- Amazon SageMaker Model Monitor
Rendered the following dataset schema with attributes from different sources and applying feature engineering.
Dataset Schema
