Data Engineering Podcast

NOVEMBER 26, 2019

In this episode James Cunningham and Ted Kaemming describe the process of rearchitecting a production system, what they learned in the process, and some useful tips for anyone else evaluating Clickhouse. And for your machine learning workloads, they just announced dedicated CPU instances.

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Data Warehouse Building PostgreSQL Kafka 100

Cloudera

SEPTEMBER 28, 2020

Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. Navigator to atlas migration, Improved performance and scalability. Background: .

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Cloud Kafka Professional Services Metadata 131

ProjectPro

DECEMBER 7, 2021

This blog will give you an in-depth knowledge of what is a data pipeline and also explore other aspects such as data pipeline architecture, data pipeline tools, use cases, and so much more. Features of a Data Pipeline Data Pipeline Architecture How to Build an End-to-End Data Pipeline from Scratch? What is a Big Data Pipeline?

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Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

DECEMBER 27, 2023

These skills can be learned with any Software Developer Training program. They whisk their magic by testing, writing codes, helping build new software, and managing a team of coders. Usually, CSS and HTML are learned at the same time. They are highly skilled programmers who solve complex problems in websites, applications, etc.

Medical 98

Medical Programming Language Amazon Web Services Entertainment 98

Data Engineering Podcast

OCTOBER 7, 2019

In this episode CEO Venkat Venkataramani and SVP of Product Shruti Bhat explain the origins of Rockset, how it is architected to allow for fast and flexible SQL analytics on your data, and how their serverless platform can save you the time and effort of implementing portions of your own infrastructure.

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Structured Data Cloud SQL Programming Language 100

Confluent

APRIL 18, 2019

While the current hype around the Internet of Things (IoT) focuses on smart “things”—smart homes, smart cars, smart watches—the first known IoT device was a simple Coca-Cola vending machine at Carnegie Mellon University in Pittsburgh. And Confluent Cloud and Apache Kafka ® are at the center of this transformation.

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Food Cloud Retail Kafka 82

Lyft Engineering

OCTOBER 3, 2023

It enables everything from reliable business logic to insightful decision-making and robust machine learning modeling. We will then introduce our in-house product, Verity, and showcase how it serves as a central platform for ensuring data quality in our Hive Data Warehouse. Yet this has come at the cost of quality.

Big Data 84

Big Data Metadata Data Warehouse Data 84

Databand.ai

DECEMBER 13, 2022

Whether you’re a data engineering pro looking to stay up to date on the latest trends or new to the space and want to learn more, following the right leaders and joining the right conversations can make all the difference when it comes to plugging into the data engineering community. You’ve come to the right place.

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Data Engineering Data Engineer Engineering AWS 52

AltexSoft

FEBRUARY 11, 2023

What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority. machine learning and deep learning models; and business intelligence tools. This privacy law must be kept in mind when building data architecture. Feel free to enjoy it.

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Data Architect Certification Generalist Big Data 87

ProjectPro

JUNE 18, 2021

This blog aims to answer all questions on how Java vs Python compare for data science and which should be the programming language of your choice for doing data science in 2021. Java for Data Science - Should data scientists learn Java? Java for Data Science - Should data scientists learn Java? renamed to Java.

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Java Data Science Python Programming Language 52

Cloudera

SEPTEMBER 11, 2018

Last week Cloudera introduced an open end-to-end architecture for IoT and the different components needed to help satisfy today’s enterprise needs regarding operational technology (OT), information technology (IT), data analytics and machine learning (ML), along with modern and traditional application development, deployment, and integration.

Data Process 40

Data Process Process Building Machine Learning 40

ProjectPro

FEBRUARY 21, 2023

Whether you are just starting your career as a Data Engineer or looking to take the next step, this blog will walk you through the most valuable data engineering certifications and help you make an informed decision about which one to pursue. The answer is- by earning professional data engineering certifications! Don’t worry!

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Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

JULY 7, 2022

You can read more about Convoy’s approach from our blog with their Head of Product, Data Platform, Chad Sanderson, “ The modern data warehouse is broken.” Data contracts could become a key piece of the data quality puzzle, and much can be learned from Andrew’s experience implementing them at GoCardless, detailed below.

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Data Warehouse Software Engineer Software Engineering Data 52

Knowledge Hut

DECEMBER 26, 2023

Businesses benefit at large with these data collection and analysis as they allow organizations to make predictions and give insights about products so that they can make informed decisions, backed by inferences from existing data, which, in turn, helps in huge profit returns to such businesses. What is the role of a Data Engineer?

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Data Engineering Data Engineer Engineering Pipeline-centric 98

Data Engineering Weekly

DECEMBER 24, 2023

Visit rudderstack.com to learn more. No 1 rule of the product experience is “Don’t make the user think”; for me, “prompting” makes me think a lot. Your rollout can make/break the core experience of your product without showing much visual change. Read the announcement for more details.

Data Engineering 62

Data Engineering Data Engineer Engineering Deep Learning 62

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. Whether you are a seasoned professional or just starting your career in Azure Data Engineering, this blog will provide you with the tips and tricks you need to craft a winning resume.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Confluent

JUNE 26, 2019

I see this pattern coming up more and more in the field in conjunction with Apache Kafka ®. In these projects, microservice architectures use Kafka as an event streaming platform. Apache Kafka – An event streaming platform for microservices. What technology should you use to build microservice architectures?

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Kafka Designing Architecture ETL Tools 109

Cloudera

AUGUST 10, 2022

Cloudera Stream Processing (CSP), powered by Apache Flink and Apache Kafka, provides a complete stream management and stateful processing solution. In CSP, Kafka serves as the storage streaming substrate, and Flink as the core in-stream processing engine that supports SQL and REST interfaces. Apache Kafka and SMM.

Process 89

Process Kafka PostgreSQL MySQL 89

Confluent

JUNE 18, 2019

Software projects of all sizes and complexities have a common challenge: building a scalable solution for search. Building a resilient and scalable solution is not always easy. It involves many moving parts, from data preparation to building indexing and query pipelines.

Architecture 95

Architecture Building Kafka Database-centric 95

ProjectPro

JANUARY 25, 2022

Did you know that, according to Linkedin, over 24,000 Big Data jobs in the US list Apache Spark as a required skill? Learning Spark has become more of a necessity to enter the Big Data industry. Python is one of the most extensively used programming languages for Data Analysis, Machine Learning , and data science tasks.

Big Data 52

Big Data Data Process Process Kafka 52

AltexSoft

OCTOBER 21, 2022

We say ‘xerox’ speaking of any photocopy, whether or not it was created by a machine from the Xerox corporation. Kafka can continue the list of brand names that became generic terms for the entire type of technology. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it.

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Kafka Hadoop ETL Tools Big Data 93

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity. Continuous Deployment.

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Consulting Machine Learning Data Science Data Pipeline 123

Cloudera

AUGUST 20, 2021

How CDP Enables and Accelerates Data Product Ecosystems. A multi-purpose platform focused on diverse value propositions for data products. As a result, CDP-enabled data products can meet multiple and varying functional and non-functional requirements that correspond to product attributes, each fulfilling specific customer needs.

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Data Warehouse Data Architecture Cloud 97

Cloudera

DECEMBER 14, 2020

If there’s one thing enterprises have learned in 2020, it’s how to navigate through uncertain times, and in 2021, organizations will likely have to continue navigating through a shifting landscape. Apache Kafka helps data administrators and streaming app developers to buffer high volumes of streaming data for high scalability.

Process 71

Process Kafka Government Big Data 71

AltexSoft

NOVEMBER 7, 2022

But apparently, things were much more difficult before Apache Airflow appeared. What is Apache Airflow? Apache Airflow is an open-source Python -based workflow orchestrator that enables you to design, schedule, and monitor data pipelines. Source: Apache Airflow. Source: Apache Airflow. How data engineering works.

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52

Lyft Engineering

SEPTEMBER 27, 2022

As product iteration speed increased over time, this older infrastructure became unable to support the faster development cycles, primarily because all the ML feature generation required writing custom logic which would take multiple weeks to develop. Decrease development time and increase product iteration speed.

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Kafka Aggregated Data Machine Learning Architecture 52

ProjectPro

NOVEMBER 15, 2021

.” From month-long open-source contribution programs for students to recruiters preferring candidates based on their contribution to open-source projects or tech-giants deploying open-source software in their organization, open-source projects have successfully set their mark in the industry.

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Big Data Project Metadata Programming Language 52

Cloudera

AUGUST 21, 2020

Historically these highly specialized platforms were deployed on-prem in private data centers to ensure greater control , security, and compliance. Will building on open-source remain our safest option? . Many of them are increasingly deployed outside of traditional data centers in hosted, “cloud” environments.

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Hadoop Big Data Cloud Kafka 73

Confluent

MAY 9, 2019

Event-first thinking enables us to build a new atomic unit: the event. This model is completely free form, we can build anything provided that we apply mechanical sympathy with the underlying system behavior. Building the KPay payment system. We need to build something real, such as a payment system. Deployment model.

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Kafka Pipeline-centric Architecture Database-centric 92

phData: Data Engineering

JANUARY 3, 2022

DataOps: What Is It, Core Principles, and Tools For Implementation Nick Goble January 3, 2022 When building a successful company, it’s critical to have a strategy around how you build and scale your business from a technology and data perspective. Want to Save This eBook for Later? No problem! Why is that? What’s Data Strategy?

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IT AWS Software Engineer Software Engineering 52

ProjectPro

NOVEMBER 22, 2021

Is PySpark easy to learn? How long does it take to learn PySpark? What is the best way to learn PySpark? When we build a DataFrame from a file or table, PySpark creates the DataFrame in memory with a specific number of divisions based on specified criteria. pivotDF = df.groupBy("Product").pivot("Country").sum("Amount")

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

DECEMBER 10, 2021

This blog covers the top 50 most frequently asked Azure interview questions and answers. Well, this Azure interview questions and answers blog will help you land your dream cloud computing job role! Azure Cloud Services is a Paas (platform-as-a-service) product that intends to provide robust, efficient, and cost-effective applications.

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BI Cloud Computing SQL Database 52

Confluent

SEPTEMBER 20, 2019

As a distributed system for collecting, storing, and processing data at scale, Apache Kafka ® comes with its own deployment complexities. Luckily for on-premises scenarios, a myriad of deployment options are available, such as the Confluent Platform which can be deployed on bare metal, virtual machines, containers, etc.

Kafka 21

Kafka Management Cloud AWS 21

Confluent

OCTOBER 10, 2019

A key challenge, however, is integrating devices and machines to process the data in real time and at scale. Apache Kafka ® and its surrounding ecosystem, which includes Kafka Connect, Kafka Streams, and KSQL, have become the technology of choice for integrating and processing these kinds of datasets.

Kafka 20

Kafka Google Cloud Architecture Machine Learning 20

ProjectPro

NOVEMBER 7, 2016

This blog will give you an indepth insight into the architecture of hadoop and its major components- HDFS, YARN, and MapReduce. Hadoop Architecture - The Inception Hortonworks founder predicted that by the end of 2020, 75% of Fortune 2000 companies would be running 1000 node Hadoop clusters in production. without any difficulties?

Hadoop 40

Hadoop Architecture IT Big Data 40

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry. RDBMS are usually vertically scalable.

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Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

MARCH 23, 2015

was intensive and played a significant role in processing large data sets, however it was not an ideal choice for interactive analysis and was constrained for machine learning, graph and memory intensive data analysis algorithms. In one of our previous articles we had discussed about Hadoop 2.0 Hadoop Users Expectations from Hadoop 2.0

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Hadoop Big Data Architecture Metadata 40