Data Science Guide

Read more about data science, business intelligence, machine learning, and artificial intelligence and the role they play in the data cloud.

Machine Learning Platforms

Discover how machine learning platforms provide users with the tools necessary to develop, deploy, and improve machine learning — specifically algorithms.

Data Science Pipeline

Learn how data science pipelines automate the processes of data validation; extract, transform, load (ETL); machine learning and modeling.

What is a CI/CD Pipeline?

Learn about CI/CD pipelines, which is an end-to-end software delivery process used to deploy new and updated software safely.

Feature Selection for Accurate Machine Learning Models

Feature selection helps machine learning models sift through data points to determine which ones are relevant and which aren’t.

Predictive Modeling for Confidence in Decision-Making

Predictive modeling is a method of identifying trends and envisioning future outcomes by using various methods of modeling data.

Python and SQL for Data Science

Python and SQL are two of the most popular programming languages. In this article, we’ll explore these two languages and how they work together in data science applications.

A Modern ETL Process

Implementing a modern ETL process has significant benefits for efficiently building data applications and empowering data-driven decision-making.

Lambda Architecture

Lambda architecture is a popular deployment model. In this post, we’ll explain how it works and the benefits and drawbacks of using this data architecture.

Internet of Things (IOT)

In this guide page we look at what is Internet of Things, how it works, as well as the different types of IoT data and its business value.