Data Engineering Podcast

NOVEMBER 6, 2022

Summary A lot of the work that goes into data engineering is trying to make sense of the "data exhaust" from other applications and services. Trusted by thousands of organizations and supported by over 20,000 community members, Prefect powers over 100MM business critical tasks a month.

Building 130

Building IT Metadata MongoDB 130

Data Engineering Podcast

JUNE 19, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Metadata 130

Metadata Unstructured Data MongoDB MySQL 130

Data Engineering Podcast

OCTOBER 16, 2022

In this episode Adrian Kosowski explains how the Pathway product got started, how its design simplifies the creation of data products that support supply chain operations, and how developers can help to build an ecosystem of applications that allow businesses to accelerate their time to insight.

Database 100

Database Metadata MongoDB MySQL 100

Data Engineering Podcast

OCTOBER 2, 2022

In this episode Roambee CEO, Sanjay Sharma, shares the types of questions that companies are asking about their logistics, the technical work that they do to provide ways to answer those questions, and how they approach the challenge of data quality in its many forms. For more information on Prefect, visit dataengineeringpodcast.com/prefect.

Metadata 100

Metadata Electronics MongoDB MySQL 100

Data Engineering Podcast

SEPTEMBER 25, 2022

In this episode Tom Baeyens explains their reasons for creating a new syntax for expressing and validating checks for data assets and processes, as well as how to incorporate it into your own projects. Data engineers don’t enjoy writing, maintaining, and modifying ETL pipelines all day, every day.

Building 100

Building Metadata MongoDB MySQL 100

Data Engineering Podcast

AUGUST 21, 2022

In this episode Tracy Daniels, CDO of Truist, shares her journey into the position, her responsibilities, and her relationship to the data professionals in her organization. Sign up free… or just get the free t-shirt for being a listener of the Data Engineering Podcast at dataengineeringpodcast.com/rudder.

Metadata 100

Metadata MongoDB MySQL Data Lake 100

Data Engineering Podcast

JULY 17, 2022

In this episode Crux CTO Mark Etherington discusses the different costs involved in managing external data, how to think about the total return on investment for your data, and how the Crux platform is architected to reduce the toil involved in managing third party data. Tired of deploying bad data?

Data Management 130

Data Management Management Metadata MongoDB 130

Data Engineering Podcast

JULY 10, 2022

In this episode Inbar Yogev and Lior Winner share the journey that they and their teams at Riskified have been on for their data platform. They also discuss how they have established a guild system for training and supporting data professionals in the organization. Tired of deploying bad data?

Metadata 100

Metadata MongoDB MySQL Data Pipeline 100

Data Engineering Podcast

OCTOBER 9, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Metadata 100

Metadata AWS MongoDB MySQL 100

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

DECEMBER 26, 2023

Data Science is a combination of several disciplines including Mathematics and Statistics, Data Analysis, Machine Learning, and Computer Science. Data Science is a huge umbrella with a plethora of roles available in the field such as a Data Scientist, Data Engineer, BI Developer, Data and Analytics Manager, etc.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Data Engineering Podcast

JUNE 12, 2022

Trupti Natu has been the first data hire multiple times and gone through the process of building teams across the different stages of growth. In this episode she shares her thoughts and insights on how to be intentional about establishing your own data team.

Metadata 100

Metadata Unstructured Data Business Intelligence MongoDB 100

Data Engineering Podcast

JULY 3, 2022

She also discusses her views on the role of the data lakehouse as a building block for these architectures and the ongoing influence that it will have as the technology matures. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Tired of deploying bad data?

Architecture 100

Architecture Metadata MongoDB MySQL 100

Databand.ai

DECEMBER 13, 2022

The Top 25 Data Engineering Influencers and Content Creators on LinkedIn Ryan Yackel 2022-12-13 10:23:19 Interested in data engineering? LinkedIn is full of influencers sharing new ideas and sparking conversations on all kinds of topics, and data engineering is no exception. You’ve come to the right place.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Data Engineering Podcast

SEPTEMBER 4, 2022

In this episode founders Barr Moses and Lior Gavish rejoin the show to reflect on the evolution and adoption of data observability technologies and the capabilities that are being introduced as the broader ecosystem adopts the practices. The only thing worse than having bad data is not knowing that you have it.

IT 100

IT Metadata MongoDB MySQL 100

Data Engineering Podcast

JUNE 5, 2022

In this episode Sean Falconer explains the idea of a data privacy vault and how this new architectural element can drastically reduce the potential for making a mistake with how you manage regulated or personally identifiable information. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Data Security 100

Data Security Metadata MongoDB Scala 100

Data Engineering Podcast

AUGUST 6, 2022

In this episode Paolo Platter shares the lessons they have learned in that process, the Data Mesh Boost platform that they have built to reduce some of the boilerplate required to make it successful, and some of the considerations to make when deciding if a data mesh is the right choice for you.

Metadata 100

Metadata MongoDB MySQL Business Intelligence 100

Data Engineering Podcast

JULY 31, 2022

In this episode Ernie Ostic shares the approach that he and his team at Manta are taking to build a complete view of data lineage across the various data systems in your organization and the useful applications of that information in the work of every data stakeholder.

IT 100

IT Metadata MongoDB MySQL 100

Knowledge Hut

DECEMBER 21, 2023

Data Science is the world's most rapidly growing sector and data engineers are at the forefront. In this article, we will understand the promising data engineer career outlook and what it takes to succeed in this role. What is Data Engineering? What are the Data Engineer Career Opportunities?

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Data Engineering Podcast

DECEMBER 29, 2022

In this episode she shares the strategic and tactical elements of how to make more effective use of the technical and organizational resources that are available to you for getting work done with data. Missing data? Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines.

Management 130

Management Metadata Business Intelligence Data Lake 130

Data Engineering Podcast

DECEMBER 18, 2022

In this episode Abe Gong brings his experiences with the Great Expectations project and community to discuss the technical and organizational considerations involved in implementing these constraints to your data workflows. Missing data? Start trusting your data with Monte Carlo today! Missing data?

Metadata 130

Metadata Business Intelligence Data Lake BI 130

Data Engineering Podcast

NOVEMBER 20, 2022

Summary The majority of blog posts and presentations about data engineering and analytics assume that the consumers of those efforts are internal business users accessing an environment controlled by the business. Data engineers don’t enjoy writing, maintaining, and modifying ETL pipelines all day, every day.

Systems 130

Systems Metadata Data Pipeline MongoDB 130

Data Engineering Podcast

DECEMBER 25, 2022

Summary Five years of hosting the Data Engineering Podcast has provided Tobias Macey with a wealth of insight into the work of building and operating data systems at a variety of scales and for myriad purposes. Missing data? Start trusting your data with Monte Carlo today!

Building 100

Building Metadata Business Intelligence Data Lake 100

Data Engineering Podcast

OCTOBER 23, 2022

In this episode Shane Gibson shares practical advice and insights from his years of experience as a consultant and engineer working in data about how to adopt agile principles in your data work so that you can move faster and provide more value to the business, while building systems that are maintainable and adaptable.

Project 130

Project Metadata MongoDB MySQL 130

Data Engineering Podcast

NOVEMBER 27, 2022

In this episode Wes McKinney shares the ways that Arrow and its related projects are improving the efficiency of data systems and driving their next stage of evolution. Missing data? Data engineers struggling with unreliable data need look no further than Monte Carlo, the leading end-to-end Data Observability Platform!

Data Process 100

Data Process Process Metadata Business Intelligence 100

Knowledge Hut

SEPTEMBER 6, 2023

Once the data is tailored to your requirements, it then should be stored in a warehouse system, where it can be easily used by applying queries. Some of the most popular database management tools in the industry are NoSql, MongoDB and oracle. Career Prospect - After completing this course you can take up a role as a Data Engineer.

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

Data Engineering Podcast

JUNE 26, 2022

In this episode Isaac Brodsky explains how the Unfolded platform is architected, their experience joining the team at Foursquare, and how you can start using it for analyzing your spatial data today. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Datasets 130

Datasets Unstructured Data Metadata MongoDB 130

ProjectPro

AUGUST 24, 2021

Nevertheless, that is not the only job in the data world. Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

SEPTEMBER 6, 2023

They highlight competence in data management, a pivotal requirement in today's business landscape, making certified individuals a sought-after asset for employers aiming to efficiently handle, safeguard, and optimize data operations. Skills acquired : Core data concepts. MongoDB aggregation. MongoDB performance.

Database 52

Database Certification MongoDB MySQL 52

Data Engineering Podcast

OCTOBER 5, 2021

This is an interesting deep dive into the internals of a high performance streaming engine and the details that are involved in building distributed systems. Data engineers struggling with unreliable data need look no further than Monte Carlo, the world’s first end-to-end, fully automated Data Observability Platform!

Engineering 100

Engineering MongoDB Kafka Data Lake 100

U-Next

SEPTEMBER 7, 2022

Built to make strategic use of data, a Data Warehouse is a combination of technologies and components. A data warehouse is a type of data management system that is designed to enable and support business intelligence (BI) activities, especially analytics. Data Warehouse in DBMS: . Athena on AWS. .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

JULY 29, 2022

Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. Helpful skills.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. A publisher (say, telematics or Internet of Medical Things system) produces data units, also called events or messages , and directs them not to consumers but to a middleware platform — a broker.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

AltexSoft

MAY 14, 2021

On top of that, new technologies are constantly being developed to store and process Big Data allowing data engineers to discover more efficient ways to integrate and use that data. You may also want to watch our video about data engineering: A short video explaining how data engineering works.

Big Data 78

Big Data Data Analytics IT NoSQL 78

AltexSoft

OCTOBER 8, 2021

Xplenty is a cloud-based , low-code data transformation and integration platform that helps users organize and prepare their data for advanced business intelligence and analytical purposes. The toolkit allows you to quickly build data pipelines , automate integration tasks, and monitor jobs. Ease of use.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52