Building Machine Learning Pipelines with Real-Time Feature Engineering

Real-time feature engineering is valuable for a variety of use cases, from service personalization to trade optimization to operational efficiency. It can also be helpful for risk mitigation through fraud prediction, by enabling data scientists and ML engineers to harness real-time data, perform complex calculations in real time and make fast decisions based on fresh data, for example to predict credit card fraud before it occurs.

Migrate to CDP Private Cloud Base - A Step by Step Guide

Our recent blog discussed the four paths to get from legacy platforms to CDP Private Cloud Base. In this blog and accompanying video, we will deep dive into the mechanics of running an in-place upgrade from CDH5 or CDH6 to CDP Private Cloud Base. The overall upgrade follows a seven-step process illustrated below. In the video below we walk through a complete end to end upgrade of CDH to CDP Private Cloud Base.

Future of Data Meetup: CDP on Azure - Industrial Strength Data Engineering

Data Engineering is undergoing a huge evolution requiring faster and more reliable data pipelines. Apache Spark and Python are core foundational components of this new architecture enabling data engineers to quickly develop these pipelines. They also introduce challenges when moving to production. Come join us as we: Ask questions and learn. We will also have a raffle of Cloudera swag.

How to Turn on Change Data Capture (CDC)

2.5 quintillion bytes of data are produced every day, and those numbers are continually increasing. With such astronomical volumes of data, businesses have to understand and interpret data faster than ever before. However, data transfers must occur for businesses with millions of data entry points to properly store and interpret their data.

7 Tips to Improve ETL Performance

Consider for a moment, if you will, plastic patio furniture. Plastic Fantastic is a global manufacturer with several factories, warehouses, and plenty of stores. One can only imagine the sheer amount of data resulting from sales, production, suppliers, and finances. Everything that happens, from purchase and onward, to these chairs, tables, and cupboards in all corners of the world is measured.

Serving the Public Through Data

Digital transformation has been talked about for many years, but the pandemic has accelerated the digital transformation journeys for many enterprises. Forced to adapt to changes in the business landscape and customer behavior, businesses have adopted more digital tools and technologies to drive innovation and increase resilience.

Closing the Gap Between the Digital Haves and Have-Nots

The digital race is on. To pull ahead of the pack, a company needs to know what to do with its data. Without a data-driven strategy, you’re bound to lose ground to competitors who apply their data to operational improvements, product development, go-to-market strategies, and the customer experience. It isn’t enough to collect, interpret, and act on the data. You have to do it fast.