Data Engineering Podcast

NOVEMBER 20, 2021

Summary The technology for scaling storage and processing of data has gone through massive evolution over the past decade, leaving us with the ability to work with massive datasets at the cost of massive complexity. Missing data? Start trusting your data with Monte Carlo today! Struggling with broken pipelines? Stale dashboards?

Data Warehouse 100

Data Warehouse Data Lake BI Business Intelligence 100

Knowledge Hut

NOVEMBER 2, 2023

For those aspiring to build a career within the Azure ecosystem, navigating the choices between Azure Data Engineers and Azure DevOps Engineers can be quite challenging. Azure Data Engineers and Azure DevOps Engineers are two critical components of the Azure ecosystem for different but interconnected reasons.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Cloudera

JUNE 26, 2023

Here are some tips and tricks of the trade to prevent well-intended yet inappropriate data engineering and data science activities from cluttering or crashing the cluster. For data engineering and data science teams, CDSW is highly effective as a comprehensive platform that trains, develops, and deploys machine learning models.

ETL Tools 76

ETL Tools Programming Language Datasets Data Pipeline 76

Data Engineering Podcast

APRIL 5, 2021

Summary One of the biggest obstacles to success in delivering data products is cross-team collaboration. This introduces a barrier to communication that is difficult to overcome, particularly in teams that have not reached a significant level of maturity in their data journey.

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.

Data Process 90

Data Process Process Metadata Finance 90

Data Engineering Podcast

DECEMBER 4, 2022

Summary The term "real-time data" brings with it a combination of excitement, uncertainty, and skepticism. In this episode Arjun Narayan explains how the technical barriers to adopting real-time data in your analytics and applications have become surmountable by organizations of all sizes.

Data Lake 100

Data Lake MongoDB MySQL Data Warehouse 100

Data Engineering Weekly

MARCH 19, 2023

Contribute to the Rudderstack Transformations Library, Win $1000 RudderStack Transformations lets you customize event data in real time with your own JavaScript or Python code. link] Sanjeev Mohan: What Exactly is a Data Product? Is chatGPT a data product? Is Data a product? What is Data Product, indeed?

Data Engineering 57

Data Engineering Data Engineer Engineering Media 57

Ascend.io

FEBRUARY 23, 2024

You are a data professional. Exciting, isn’t it Yet, embarking on the AI adoption journey introduces a series of challenges, with one of the most significant being the readiness of your data platform. In this article, we outline the essential prerequisites for an AI data platform.

Cloud Storage 52

Cloud Storage Data Ingestion Machine Learning Algorithm 52

Data Engineering Podcast

FEBRUARY 6, 2022

Summary There are many dimensions to the work of protecting the privacy of users in our data. When you need to share a data set with other teams, departments, or businesses then it is of utmost importance that you eliminate or obfuscate personal information. The only thing worse than having bad data is not knowing that you have it.

Data Pipeline 100

Data Pipeline Data Metadata Software Engineer 100

Data Engineering Podcast

SEPTEMBER 25, 2022

Summary Data integration from source systems to their downstream destinations is the foundational step for any data product. With the increasing expecation for information to be instantly accessible, it drives the need for reliable change data capture. Data teams are increasingly under pressure to deliver.

Food 100

Food MongoDB Scala MySQL 100

KDnuggets

AUGUST 3, 2022

10 Most Used Tableau Functions • Is Domain Knowledge Important for Machine Learning? • ETL vs ELT: Data Integration Showdown • Free MLOps Crash Course for Beginners • 90% of Today’s Code is Written to Prevent Failure, and That’s a Problem.

Machine Learning 64

Machine Learning Data Integration Coding Data 64

Data Engineering Podcast

APRIL 24, 2022

Summary There are very few tools which are equally useful for data engineers, data scientists, and machine learning engineers. WhyLogs is a powerful library for flexibly instrumenting all of your data systems to understand the entire lifecycle of your data from source to productionized model.

Machine Learning 100

Machine Learning Systems Data Lake Metadata 100

Knowledge Hut

NOVEMBER 17, 2023

The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice. Who is an Azure Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

JANUARY 30, 2024

In today's world, where data rules the roost, data extraction is the key to unlocking its hidden treasures. As someone deeply immersed in the world of data science, I know that raw data is the lifeblood of innovation, decision-making, and business progress. What is data extraction?

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Data Engineering Podcast

OCTOBER 2, 2022

Summary Data lineage is something that has grown from a convenient feature to a critical need as data systems have grown in scale, complexity, and centrality to business. Alvin is a platform that aims to provide a low effort solution for data lineage capabilities focused on simplifying the work of data engineers.

IT 100

IT Food PostgreSQL MongoDB 100

ProjectPro

FEBRUARY 8, 2023

ETL developers play a vital role in designing, implementing, and maintaining the processes that help organizations extract valuable business insights from data. What is an ETL Developer? The purpose of ETL is to provide a centralized, consistent view of the data used for reporting and analysis.

ETL Tools 52

ETL Tools Data Cleanse Data Warehouse Big Data 52

Data Engineering Podcast

FEBRUARY 22, 2021

Summary Data integration is a critical piece of every data pipeline, yet it is still far from being a solved problem. The team at Airbyte is adding a new entry to that list with the goal of making robust and easy to use data integration more accessible to teams who want or need to maintain full control of their data.

Data Integration 100

Data Integration Data Warehouse Data Pipeline BI 100

Data Engineering Podcast

MAY 1, 2022

Summary Building a data platform is an iterative and evolutionary process that requires collaboration with internal stakeholders to ensure that their needs are being met. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform.

Data Warehouse 100

Data Warehouse Data Lake Architecture Data 100

Databand.ai

JULY 17, 2023

DataOps vs. MLOps: Similarities, Differences, and How to Choose Joseph Arnold July 17, 2023 What Is DataOps? DataOps , short for Data Operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data management processes.

Data Pipeline 52

Data Pipeline Machine Learning High Quality Data BI 52

Data Engineering Podcast

APRIL 12, 2021

Summary "Business as usual" is changing, with more companies investing in data as a first class concern. As a result, the data team is growing and introducing more specialized roles. If you are wondering how to apply your talents and interests to working with data then this episode is a must listen.

Data Warehouse 100

Data Warehouse Data Pipeline BI Data 100

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

Data Lake 59

Data Lake Data Warehouse Hadoop Raw Data 59

Data Engineering Podcast

JANUARY 4, 2021

Summary As more organizations are gaining experience with data management and incorporating analytics into their decision making, their next move is to adopt machine learning. As a result the feature store is becoming a required piece of the data platform. Do you want to get better at Python?

Python 100

Python Data Lake Machine Learning Computer Science 100

Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Modern platforms like Redshift , Snowflake , and BigQuery have elevated the data warehouse model.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Knowledge Hut

SEPTEMBER 27, 2023

In today's business landscape, data-driven tools are essential for better decision-making, improved customer relationships, and overall growth. Our goal is to provide a thorough comparison of two key tools: Power BI vs. Salesforce. Functionality Data visualisation, trend prediction, creating reports etc.

BI 52

BI Datasets Data Security Data Analysis 52

Data Engineering Podcast

MAY 27, 2018

Summary Building an ETL pipeline is a common need across businesses and industries. In this episode CTO and co-founder of Alooma, Yair Weinberger, explains how the platform addresses the common needs of data collection, manipulation, and storage while allowing for flexible processing. What is Alooma and what is the origin story?

Data Pipeline 100

Data Pipeline MongoDB Scala Google Cloud 100

Data Engineering Podcast

JANUARY 30, 2022

Summary Pandas is a powerful tool for cleaning, transforming, manipulating, or enriching data, among many other potential uses. As a result it has become a standard tool for data engineers for a wide range of applications. Today’s episode is Sponsored by Prophecy.io – the low-code data engineering platform for the cloud.

Data Engineering 100

Data Engineering Data Engineer Engineering Data Pipeline 100

ProjectPro

JANUARY 31, 2023

Want to know who is a business intelligence engineer, what does a business intelligence engineer do, and how these BI engineers turn mountains of data into actionable insights? Join us on a thrilling exploration of the critical Business Intelligence Engineer job role and its impact on the modern business landscape in the big data world.

Business Intelligence 52

Business Intelligence Engineering BI Data Warehouse 52

Knowledge Hut

JUNE 20, 2023

A novice data scientist prepared to start a rewarding journey may need clarification on the differences between a data scientist and a machine learning engineer. Many people are learning data science for the first time and need help comprehending the two job positions.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Data Engineering Weekly

APRIL 16, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make collecting data from every application, website, and SaaS platform easy, then activating it in your warehouse and business tools. 🍒 We'll send exclusive The Data Stack Show swag just for participating!

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

SEPTEMBER 9, 2021

Apache Hive and Apache Spark are the two popular Big Data tools available for complex data processing. To effectively utilize the Big Data tools, it is essential to understand the features and capabilities of the tools. Hive is built on top of Hadoop and provides the measures to read, write, and manage the data.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Cloudera

JULY 21, 2022

Co-author: Mike Godwin, Head of Marketing, Rill Data. Cloudera has partnered with Rill Data, an expert in metrics at any scale, as Cloudera’s preferred ISV partner to provide technical expertise and support services for Apache Druid customers. Data is made queryable in real time. Figure 1: Rill and Cloudera Architecture.

BI 86

BI Digital Media Data Warehouse Kafka 86

Silectis

FEBRUARY 17, 2021

In this blog post, we’ll walk you through how data science and data engineering are complementary disciplines. We’ll also delineate a third category: data analysis. We’ll explore how both data engineering and data science should be marshaled to make better decisions. What is Data Science, Really?

Data Science 52

Data Science Data Engineering Data Engineer Engineering 52

ProjectPro

JUNE 9, 2021

This blog on Data Science vs. Data Engineering presents a detailed comparison between the two domains. vs. What does a Data Engineer do? Are you a Data Scientist or a Data Engineer? Is data engineering more important than data science? Data Engineer vs Data Scientist: Which is better?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

AltexSoft

FEBRUARY 11, 2023

Data is now one of the most valuable assets for any kind of business. The 11th annual survey of Chief Data Officers (CDOs) and Chief Data and Analytics Officers reveals 82 percent of organizations are planning to increase their investments in data modernization in 2023. What is a data architect?

Data Architect 87

Data Architect Certification Generalist Big Data 87

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. Hive-on-Tez for better ETL performance. Query Result Cache.

Cloud 131

Cloud Kafka Professional Services Metadata 131

Monte Carlo

APRIL 16, 2022

The data warehouse is the foundation of the modern data stack, so it caught our attention when we saw Convoy head of data Chad Sanderson declare, “ the data warehouse is broken ” on LinkedIn. I’ll let you decide for yourself if the “immutable data warehouse” (or active vs passive ETL) is the right path for your data team.

Data Warehouse 52

Data Warehouse Architecture Data Government 52