Data Engineering Podcast

JUNE 14, 2021

Summary When you build a machine learning model, the first step is always to load your data. Typically this means downloading files from object storage, or querying a database. To speed up the process, why not build the model inside the database so that you don’t have to move the information? In this episode Paige Roberts explains the benefits of pushing the machine learning processing into the database layer and the approach that Vertica has taken for their implementation.

Machine Learning 100

Machine Learning Database Data Warehouse Hadoop 100

Uber Engineering

JUNE 15, 2021

Introduction to Flaky Tests. Unit testing forms the bedrock of any Continuous Integration (CI) system. It warns software engineers of bugs in newly-implemented code and regressions in existing code, before it is merged. This ensures increased software reliability. It also … The post Handling Flaky Unit Tests in Java appeared first on Uber Engineering Blog.

Java 120

Java Software Engineer Software Engineering Coding 120

AltexSoft

JUNE 14, 2021

In today’s society, insurers can no longer ignore the mounting expectations of customers. Clients now expect insurers to provide different levels of personalization that are fast, adaptable, and up to date. That is why some insurers have gone further to provide insurance and risk management services that can be adjusted and rewritten in real-time depending on the changing risk in the consumer’s life.

Insurance 88

Insurance Medical Machine Learning Algorithm 88

Cloudera

JUNE 15, 2021

At Cloudera, we have long believed that automation is key to delivering secure, ready-to-use, and well-configured platforms. Hence, we were pleased to announce the public release of Ansible-based automation to deploy CDP Private Cloud Base. By automating cluster deployment this way, you reduce the risk of misconfiguration, promote consistent deployments across multiple clusters in your environment, and help to deliver business value more quickly. .

Cloud 83

Cloud AWS Kafka Management 83

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Data Science

Confluent

JUNE 18, 2021

Stream processing has become an important part of the big data landscape, a new programming paradigm bringing asynchronous, long-lived computations to unbounded data in motion. But many people still think […].

Process 80

Process Kafka Big Data Programming 80

Teradata

JUNE 14, 2021

To achieve the personalisation demanded by today’s customers, banks must look to automation. The only way to replace 1:1 branch relationships is to automate conversations with every customer.

Banking 59

Banking 59

Uber Engineering

JUNE 15, 2021

Introduction to Flaky Tests. Unit testing forms the bedrock of any Continuous Integration (CI) system. It warns software engineers of bugs in newly-implemented code and regressions in existing code, before it is merged. This ensures increased software reliability. It also … The post Handling flaky unit tests in Java appeared first on Uber Engineering Blog.

Java 52

Java Software Engineer Software Engineering Coding 52

Confluent

JUNE 17, 2021

This blog post is the fourth in a four-part series that discusses a few new Confluent Control Center features that are introduced with Confluent Platform 6.2.0. It focuses on removing […].

Kafka 62

Kafka Management Data IT 62

Teradata

JUNE 16, 2021

The cloud is the design model for the Retail & CPG of the future. Simply getting to the cloud is not enough to be successful. It’s about both how you get there & what you do once you arrive.

Cloud 52

Cloud Retail Designing 52

DataKitchen

JUNE 14, 2021

Learn about DataOps from data leaders Jim Tyo, Invesco CDO; Kurt Zimmer, AstraZeneca Head of Engineering for Data Enablement & Ryan Chapin, former GE exec. The post Using DataOps to Drive Agility & Business Value first appeared on DataKitchen.

Engineering 52

Engineering Data 52

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

Engineering

Rockset

JUNE 17, 2021

We experience real-time analytics everyday. The content displayed in the Instagram newsfeed, the personalized recommendations on Amazon, the promotional offers from Uber Eats are all examples of real-time analytics. The emergence of real-time analytics encourages consumers to take desired actions from reading more content, to adding items to our cart to using takeout and delivery services for more of our meals.

Data Lake 40

Data Lake Architecture Data Preparation Database 40

Confluent

JUNE 16, 2021

This blog post is the third in a four-part series that discusses a few new Confluent Control Center features that are introduced with Confluent Platform 6.2.0. It focuses on inspecting […].

Kafka 62

Kafka Management IT 62

Monte Carlo

JUNE 17, 2021

Today, I’m excited to announce the availability of Monte Carlo’s integration partnership with PagerDuty to bring greater visibility to data pipelines and foster greater collaboration across data teams. With Monte Carlo joining PagerDuty’s Integration Partner Program, PagerDuty customers can now achieve Data Observability across every stage of the data lifecycle, from ingestion to analytics.

Data Pipeline 40

Data Pipeline Data Programming Technology 40

DataKitchen

JUNE 15, 2021

The post Recipes for DataOps Success: The Complete Guide to an Enterprise DataOps Transformation first appeared on DataKitchen.

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62

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

Building

RudderStack

JUNE 15, 2021

This blog talks about RudderStack's journey to date from inception to becoming a well-funded Customer Data Platform (CDP) for developers.

Data 40

Data 40

Confluent

JUNE 15, 2021

This blog post is the second in a four-part series that discusses a few new Confluent Control Center features that are introduced with Confluent Platform 6.2.0. This blog post focuses […].

Kafka 52

Kafka Management 52

Monte Carlo

JUNE 15, 2021

“ We have a service-level agreement (SLA) for our Key Metrics table, which powers our executive dashboards. It needs to be updated every day by 7:00 am. When we miss the SLA , we have to be proactive or else we get lots of frustrated emails. Can Monte Carlo alert us if we ever miss this deadline? ” I’ve heard versions of this story dozens of times from customers over the past year.

SQL 40

SQL Coding Data Process 40

Preset

JUNE 13, 2021

Trino unlocks new workflows for Apache Superset™, like querying NoSQL databases and joining data from multiple, but separate databases.

NoSQL 40

NoSQL Database Data 40

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Project

Domino Data Lab: Data Engineering

JUNE 14, 2021

Java 52

Java Datasets Coding Data Engineering 52

Data Engineering Podcast

JUNE 17, 2021

Summary Working with unstructured data has typically been a motivation for a data lake. The challenge is imposing enough order on the platform to make it useful. Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable.

Unstructured Data 100

Unstructured Data Data Warehouse Metadata Media 100

ProjectPro

JUNE 14, 2021

-A mostly complete chart of neural networks is here- Understand the idea behind the neural network algorithm, the definition of a neural network, the mathematics behind the neural network algorithm, and the different types of neural networks to become a neural network pro. Let's Have Some Fun Before That.Game Time! Instead of starting with a mostly complete neural network chart, let us play a fun game first.

Algorithm 52

Algorithm Datasets Machine Learning Deep Learning 52

Cloudera

JUNE 14, 2021

How to optimize an enterprise data architecture with private cloud and multiple public cloud options? As the inexorable drive to cloud continues, telecommunications service providers (CSPs) around the world – often laggards in adopting disruptive technologies – are embracing virtualization. Not only that, but service providers have been deploying their own clouds, some developing IaaS offerings, and partnering with cloud native content providers like Netflix and Spotify to enhance core telco bun

Telecommunication 94

Telecommunication Cloud Finance Government 94

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

Building

DataKitchen

JUNE 16, 2021

Cambridge, Mass. – June 16, 2021. Today, DataKitchen announced the release of the latest book in its groundbreaking DataOps series, Recipes for DataOps Success: The Complete Guide to An Enterprise DataOps Transformation. This book follows on the heels of its successful precursor, The DataOps Cookbook , which has been downloaded more than 14,000 times and counting.

Pharmaceutical 52

Pharmaceutical Data Analytics Programming Project 52

Rockset

JUNE 18, 2021

Intro I first met Rockset at the 2018 Greylock Techfair. Rockset had a unique approach for attracting interest: handing out printed copies of a C program and offering a job to anyone who could figure out what the program was doing. Though I wasn’t able to solve the code puzzle, I had more luck with the interview process. I joined Rockset after graduating from UCLA in 2019.

Software Engineer 40

Software Engineer Software Engineering Computer Science Coding 40

Monte Carlo

JUNE 17, 2021

As more companies rely on more data to drive their product development and strategic decision making, it’s never been more important for this data to be trusted and accurate. With Monte Carlo and PagerDuty’s integration , data teams can achieve reliable data through automated lineage, real-time monitoring and alerting, and, ultimately, end-to-end data observability.

Data Pipeline 40

Data Pipeline Software Engineer Software Engineering Data Lake 40

Cloudera

JUNE 16, 2021

This Pride month, we’re excited to introduce Katelynn Cusanelli. She’s a 5-year Clouderan working as a Senior Premier Support Engineer, dedicated to supporting our largest accounts. As the first openly transgender cast member of The Real World, Katelynn has spent a considerable amount of time advocating for LGBTQ rights and promoting diversity and inclusion.

Engineering 76

Engineering Certification Programming Management 76

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

Certification

ProjectPro

JUNE 16, 2021

Data Science replicates human behavior. We have designed machine learning to imitate how we behave as humans. Think of a model in Data Science as one way to learn. Human beings have a bias when they make a choice. The way one person lives their life cannot be scaled across the human race. Instead, when multiple people share their experiences and learnings, it is possible to develop a generalized approach.

Machine Learning 52

Machine Learning Data Science Datasets Python 52

Monte Carlo

JUNE 17, 2021

Leading companies are pioneering a shift into greater data democracy through decentralized data platforms—but without the right governance and visibility in place, data quality can suffer and trust in data can erode. That’s where data observability comes in. Here’s how the Data Engineering team at Auto Trader achieves automated monitoring and alerting while decentralizing responsibility and increasing data reliability with Monte Carlo.

Data 40

Data Data Engineering Data Engineer Data Pipeline 40