Systems | Development | Analytics | API | Testing

From 0 to Dashboard with Cloudera Data Warehouse

Today you'll see a quick demo on how to start off with any given dataset, reference it within Cloudera Data Warehouse, and then use the in house Data Visualization to create a live dashboard from the data. We'll use some example shipping data and show how you can go from 0 to dashboard in no time at all.

Future of Data Meetup: Building Automated Machine Learning Workflows in the Cloud

In this meetup, we’re going to put ourselves in the shoes of an electric car manufacturer that produces all the parts for their cars in house. First, we’ll show you an example on how this fictional car company could walk through the process of creating a prediction model based on part production data. We will then automate the creation of these models by making them depending on an upstream data collection process. To finish it off, we’ll deploy these models and make them accessible via an external API all within a native cloud environment using the Cloudera Data Platform.

Fast Forward Live: Session-based Recommender Systems

Join us live with Fast Forward Labs to discuss the recently possible in Machine Learning and AI. Being able to recommend an item of interest to a user (based on their past preferences) is a highly relevant problem in practice. A key trend over the past few years has been session-based recommendation algorithms that provide recommendations solely based on a user’s interactions in an ongoing session, and which do not require the existence of user profiles or their entire historical preferences. This report explores a simple, yet powerful, NLP-based approach (word2vec) to recommend a next item to a user. While NLP-based approaches are generally employed for linguistic tasks, here we exploit them to learn the structure induced by a user’s behavior or an item’s nature.

Future of Data Meetup: The Power of "Yes" or: How I learned to Stop Worrying and Love Governance

Full data lifecycle projects hold tremendous potential for organizations to uncover new insights and drivers of revenue and profitability. Big Data has brought the promise of doing device data capture, data enrichment, data science, and analytics at scale to enterprises. This promise also comes with challenges for developers, admins, and consumers to continuously access new data and collaborate.

Future of Data Meetup: Collect, Curate, Predict & Visualise your Streaming Data

How do you get your data from A to B? We take you on a journey with your data through: Join us to find out more about managing your data lifecycle, and see it in action during our demo. AGENDA 18:00 - Welcome 18:05 - Best Practice: Streaming Data & Analytics 18:20 - Demo: Collect, Curate, Predict & Visualise your Streaming Data 19:00 - Open Networking 19:30 - END

Future of Data Meetup: Continuous SQL With SQL Stream Builder

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.