Team Data Science
MAY 20, 2020
Should companies go full blowing big data/data science platform right away? In my opinion, you should first look at the different stages you are in. Are you in the Proof-of-Concept phase, where you are just working with offline data, where you are proving your concepts? Or are you in the MVP phase or in the creation of an MVP, where you are bringing in the first users, the first customers?
Confluent
MAY 18, 2020
What is stopping you from using Kafka Streams as your data layer for building applications? After all, it comes with fast, embedded RocksDB storage, takes care of redundancy for you, […].
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Teradata
MAY 21, 2020
Operationalizing world class analytics into day-to-day processes can help solve some of the greatest challenges in the telecommunications industry. Find out more.
Data Engineering Podcast
MAY 18, 2020
Summary The PostgreSQL database is massively popular due to its flexibility and extensive ecosystem of extensions, but it is still not the first choice for high performance analytics. Swarm64 aims to change that by adding support for advanced hardware capabilities like FPGAs and optimized usage of modern SSDs. In this episode CEO and co-founder Thomas Richter discusses his motivation for creating an extension to optimize Postgres hardware usage, the benefits of running your analytics on the same
Speaker: Tamara Fingerlin, Developer Advocate
Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
Team Data Science
MAY 20, 2020
What are the job opportunities in the field of Data Science? Several, of course! Based on the 4 phases of a Data Science project, the possibilities can be worked out well. In this blog post only two of the four phases will be discussed. But now from the beginning. The four phases are: Proof-of-Concept, MVP, Validation and Scaling. The Proof of Concept Phase (PoC) Starting at the PoC phase, you could say: okay, I'm getting a research data scientist here.
Confluent
MAY 20, 2020
Confluent Cloud supports Schema Registry as a fully managed service that allows you to easily manage schemas used across topics, with Apache Kafka® as a central nervous system that connects […].
Data Engineering Digest brings together the best content for data engineering professionals from the widest variety of industry thought leaders.
Grouparoo
MAY 21, 2020
There’s an underlying pattern prevalent today in many digital marketing tools that is causing problems. Wasted time, overpaying, slow velocity, and privacy issues for your customers are some of the results of this pattern. The problem is the over-reliance on Events. Specifically, the problem is that many marketing tools live in a world where they expect to be “pushed” data, when it would be so much better if they were “pulling” data when they needed it.
Dataquest
MAY 21, 2020
Python programming is a critical skill for data engineers. When it comes to working with data, there’s a powerful library that can increase your code’s efficiency dramatically, especially when you’re working with large datasets: NumPy. That’s why we’ve added a NumPy for Data Engineers course to our Data Engineering path !
Rock the JVM
MAY 20, 2020
Scala is an incredibly expressive language: discover hidden features that even experienced developers might miss!
Advancing Analytics: Data Engineering
MAY 19, 2020
Today’s the day! There’s much buzz & excitement as we FINALLY get to see Azure Synapse Analytics in public preview, ready for us all to get our hands on it. There’s a raft of other announcements that come hand & hand with it too. What’s that? You thought Azure Synapse Analytics was already available? You’ve been using all year and don’t see what the fuss is about??
Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
Teradata
MAY 19, 2020
As stakeholder demand for corporate accountability prompts change in the business world, opportunities for companies to capitalize on being sustainable are bigger than ever.
Preset
MAY 17, 2020
Now that you have Apache Superset installed locally, here's how to hook it up to your favorite database.
Rockset
MAY 19, 2020
Rockset has teamed up with MongoDB so you can build real-time apps with data across MongoDB and other sources. If you haven’t heard of Rockset or know what Rockset does, you will by the end of this guide! We’ll create an API to determine air quality using ClimaCell data on the weather and air pollutants. Air quality has been documented to effect human health (resources at the bottom).
Preset
MAY 20, 2020
This blob provides a summary of Apache Superset's first virtual community meetup event in May 2020.
Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives
Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri
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