Today, I will be giving you an overview about Team Data Science Process (TDSP), which is flexible data science methodology that can effectively provide predictive analytical solutions and intelligence applications.
For easy to understand Team data Science Process (TDSP) is a flexible, iterative, data-driven methodology for improving teamwork and team training. It comprises the following key components:
- Data science lifecycle
- Standardized project structure
- Infrastructure and resources
- Tools and utilities
So, Let’s discuss the following components one by one to know more in detail.
Data Science Lifecycle:
The life cycle of data science is a series of systematic steps that begin with a deep understanding of business issues or emerging issues. This also includes developing predictive analytics models and deploying them as predictions in smart applications.
The life cycle outlines the main phases of a project that are usually executed repeatedly:
- Business Understanding
- Data Acquisition and Understanding
- Customer Acceptance
Standardized Project Structure:
Standardized project structure is there for managing data, code, and documents for a data science projects and enables tracking of these artifacts using a version control system such as Git which allows your team to collaborate easily.
Infrastructure and Resources:
Team Data Science Process (TDSP) provides you a guidance on managing shared analytics and storage infrastructure, including cloud-based file systems for storing datasets, databases, big data clusters (such as Hadoop, Spark) and machine learning services etc. In the cloud and locally.
Tools and Utilities:
Implementing new processes in an organization can be a difficult task. But if you provide specific tools for aspects of the process life cycle, we are not only benefit from additional productivity, but also consistency in accepting and joining new processes.
I hope this blog post gives you an overview about Team Data Science Process (TDSP). If you have any questions, please feel free to check this link.