Continuous SQL is using Structured Query Language (SQL) to create computations against unbounded streams of data, and show the results in a persistent storage. The result stored in a persistent storage can be connected to other applications to have an analytical visualization of your data. Compared to traditional SQL, in Continuous SQL the data has a start, but no end. This means that queries continuously process results to a sink or other target types. When you define your job in SQL, the SQL statement is interpreted and validated against a schema. After the statement is executed, the results that match the criteria are continuously returned.

In this meetup, we’re going to once again put ourselves in the shoes of an electric car manufacturer that is deploying a recently developed electric motor out into their new cars. We’re going to show how to explore some data that has been previously collected through various different sources and stored into Apache Hive within a data warehouse, with the goal of tracking down a specific set of potentially defective parts. We’ll then take the results of this data exploration and create an interactive dashboard that presents our results in a visually appealing way using a BI tool that’s integrated right into the same data warehouse.

Join us for this month's Machine Learning research discussion with Cloudera Fast Forward Labs. We will discuss few-shot text classification - including a live demo and Q&A. This is an applied research report by Cloudera Fast Forward. We write reports about emerging technologies. Accompanying each report are working prototypes or code that exhibits the capabilities of the algorithm and offer detailed technical advice on its practical application.

Learn how Cloudera and Red Hat help enterprise companies securely manage the complete data lifecycle, putting data to work faster and reducing time to value. Cloudera Data Platform (CDP) Private Cloud on Red Hat® OpenShift® aggregates and visualizes data to derive actionable insights in a secure, hybrid, and open-source environment.

You asked for and we are delivering the third in our “Hello:“ series of introductory “Big Data” topics. Our next meetup covers using Apache NiFi. Lots of people want to be a data scientist... but what good is machine learning, artificial intelligence or advanced analytics if you don’t have data? Getting data is incredibly important, but getting data in real time or near real time helps you give near real time insight.

A complete overview of Cloudera Machine Learning (CML) on Cloudera Data Platform. This video covers all CML features for data science workflows.