We live in a connected world, and our digital experiences are formed by thousands of services acting as building blocks. As the world becomes more decentralized and services take over, cloud connectivity becomes the key differentiating factor of digital experiences for any organization.

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.

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.

Join Moataz Nabil for his talk about scale-up mobile UI tests with Firebase Test Lab, Cloud Function and Bitrise! 🚀 This presentation was watched live by attendees at Google Cloud Budapest 2021. At this meetup, attendees talk about interesting case studies and share some tips and tricks on infrastructure, app dev, data engineering, and machine learning. Presenter: Moataz Nabil | Developer Advocate at Bitrise ‎ Thank you for watching! Please feel free to comment your thoughts below.

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

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.

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.