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

Data Engineering Weekly

JUNE 4, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Perhaps unit test the pipeline? Sign up free to test out the tool today.

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

Knowledge Hut

NOVEMBER 2, 2023

Azure Data engineering projects are complicated and require careful planning and effective team participation for a successful completion. While many technologies are available to help data engineers streamline their workflows and guarantee that each aspect meets its objectives, ensuring that everything works properly takes time.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Snowflake

OCTOBER 3, 2023

We are excited to announce the availability of data pipelines replication, which is now in public preview. In the event of an outage, this powerful new capability lets you easily replicate and failover your entire data ingestion and transformations pipelines in Snowflake with minimal downtime.

Data Pipeline 85

Data Pipeline Management Data Ingestion Data 85

Knowledge Hut

OCTOBER 3, 2023

Within the Microsoft Azure ecosystem, the role of an Azure data engineer stands out as one of the most sought-after positions. What Does an Azure Data Engineer Do? Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs to offer end customers a variety of pre-built models.

Data Engineering 52

Data Engineering Data Engineer Engineering Cloud Computing 52

Knowledge Hut

SEPTEMBER 25, 2023

This demonstrates how in-demand Microsoft Certified Data Engineers are becoming. They are moving their servers and on-premises data to Azure Cloud. What does all of this mean for Data Engineering professionals? Who is an Azure Data Engineer? Azure Data Engineers work with these and other solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Data Engineering Weekly

OCTOBER 30, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Sign up free to test out the tool today.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Data Engineering Podcast

SEPTEMBER 11, 2022

Building reliable data pipelines is a complex and costly undertaking with many layered requirements. In order to reduce the amount of time and effort required to build pipelines that power critical insights Manish Jethani co-founded Hevo Data. Data stacks are becoming more and more complex. In fact, while only 3.5%

Data Pipeline 130

Data Pipeline Building MongoDB Scala 130

Data Engineering Weekly

MARCH 5, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Editor’s Note: Who Owns the Data Contract?

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Edureka

FEBRUARY 7, 2023

An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Knowledge Hut

APRIL 25, 2023

The tremendous growth in data generation, then the rise in data engineer jobs - there’s no arguing the fact that the big data industry is at its best pace and you, as an aspiring data engineer, have a lot to learn and make out of it - including some tools! What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

ProjectPro

FEBRUARY 21, 2023

With so many data engineering certifications available , choosing the right one can be a daunting task. There are over 133K data engineer job openings in the US, but how will you stand out in such a crowded job market? The answer is- by earning professional data engineering certifications! AWS or Azure?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

JULY 3, 2023

This is where real-time data ingestion comes into the picture. Data is collected from various sources such as social media feeds, website interactions, log files and processing. This refers to Real-time data ingestion. To achieve this goal, pursuing Data Engineer certification can be highly beneficial.

Data Ingestion 52

Data Ingestion Pipeline-centric Google Cloud Media 52

Team Data Science

MAY 10, 2020

I can now begin drafting my data ingestion/ streaming pipeline without being overwhelmed. With careful consideration and learning about your market, the choices you need to make become narrower and more clear.

Data Pipeline 130

Data Pipeline Data Ingestion AWS Kafka 130

Silectis

JANUARY 3, 2021

If you’re new to data engineering or are a practitioner of a related field, such as data science, or business intelligence, we thought it might be helpful to have a handy list of commonly used terms available for you to get up to speed. Data Engineering Data engineering is a process by which data engineers make data useful.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Ascend.io

DECEMBER 19, 2022

We hope the real-time demonstrations of Ascend automating data pipelines were a real treat—a long with the special edition T-Shirt designed specifically for the show (picture of our founder and CEO rocking the t-shirt below). Thank you to the hundreds of AWS re:Invent attendees who stopped by our booth!

Data Ingestion 52

Data Ingestion Data Pipeline Metadata AWS 52

Databand.ai

JULY 19, 2023

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database. In this article: Why Is Data Ingestion Important?

Data Ingestion 52

Data Ingestion Process Data Cleanse Data Governance 52

Ascend.io

JANUARY 2, 2024

But let’s be honest, creating effective, robust, and reliable data pipelines, the ones that feed your company’s reporting and analytics, is no walk in the park. From building the connectors to ensuring that data lands smoothly in your reporting warehouse, each step requires a nuanced understanding and strategic approach.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

ProjectPro

JANUARY 19, 2022

Data Engineering is gradually becoming a popular career option for young enthusiasts. Explore this page further and learn everything about data engineers to find the answer. We will cover it all, from its definition, skills, responsibilities to the significance of data engineer in an institution.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Ascend.io

MARCH 2, 2023

It won with ease of use by our analysts, the comprehensive scope of its automation, and the speed of end-to-end pipeline development. Terry Dougal Intelligent Data Pipelines at Audacy Instead of hiring more data engineers to patch over all the tooling with more bespoke code, Terry shifted gears and looked for a new solution.

Data Pipeline 52

Data Pipeline Media Portfolio Data Ingestion 52

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

Data Engineering Podcast

NOVEMBER 6, 2022

Summary Despite the best efforts of data engineers, data is as messy as the real world. Entity resolution and fuzzy matching are powerful utilities for cleaning up data from disconnected sources, but it has typically required custom development and training machine learning models. In fact, while only 3.5%

MongoDB 130

MongoDB Scala MySQL Data Lake 130

Data Engineering Podcast

AUGUST 21, 2022

In this episode Shruti Bhat gives her view on the state of the ecosystem for real-time data and the work that she and her team at Rockset is doing to make it easier for engineers to build those experiences. Data stacks are becoming more and more complex. In fact, while only 3.5% That’s where our friends at Ascend.io

Lambda Architecture 100

Lambda Architecture MongoDB Scala MySQL 100

Data Engineering Podcast

OCTOBER 30, 2022

Summary One of the most impactful technologies for data analytics in recent years has been dbt. It’s hard to have a conversation about data engineering or analysis without mentioning it. Despite its widespread adoption there are still rough edges in its workflow that cause friction for data analysts.

Engineering 100

Engineering MongoDB Scala MySQL 100

Data Engineering Podcast

JULY 3, 2022

Summary The perennial challenge of data engineers is ensuring that information is integrated reliably. In order to quickly identify if and how two data systems are out of sync Gleb Mezhanskiy and Simon Eskildsen partnered to create the open source data-diff utility. In fact, while only 3.5%

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Databand.ai

AUGUST 30, 2023

It emphasizes the importance of collaboration between different teams, such as data engineers, data scientists, and business analysts, to ensure that everyone has access to the right data at the right time. This can be achieved through the use of automated data ingestion, transformation, and analysis tools.

Data Governance 52

Data Governance Data Pipeline Government Data Cleanse 52

Data Engineering Podcast

AUGUST 13, 2022

Summary Data engineers have typically left the process of data labeling to data scientists or other roles because of its nature as a manual and process heavy undertaking, focusing instead on building automation and repeatable systems. Data stacks are becoming more and more complex. In fact, while only 3.5%

Machine Learning 100

Machine Learning Pipeline-centric Database-centric MongoDB 100

Data Engineering Podcast

NOVEMBER 13, 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. In fact, while only 3.5%

MongoDB 100

MongoDB Scala Google Cloud MySQL 100

Data Engineering Podcast

AUGUST 13, 2022

In this episode Shinji Kim discusses the challenges of data discovery and how to collect and preserve additional context about each piece of information so that you can find what you need when you don’t even know what you’re looking for yet. Data stacks are becoming more and more complex. In fact, while only 3.5%

Metadata 100

Metadata MongoDB Scala MySQL 100

Data Engineering Podcast

JUNE 26, 2022

Summary The most complicated part of data engineering is the effort involved in making the raw data fit into the narrative of the business. Your newly mimicked datasets are safe to share with developers, QA, data scientists—heck, even distributed teams around the world. In fact, while only 3.5%

Data Management 100

Data Management Management MongoDB Scala 100

Data Engineering Podcast

AUGUST 6, 2022

In this episode Frank Liu explains how the open source Milvus vector database is implemented to speed up machine learning development cycles, how to think about proper storage and scaling of these vectors, and how data engineering and machine learning teams can collaborate on the creation and maintenance of these data sets.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Data Engineering Podcast

AUGUST 28, 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. In fact, while only 3.5%

Building 100

Building MongoDB Scala MySQL 100

Monte Carlo

MAY 26, 2023

Since it is impractical and expensive to have all data refreshed on a near real-time basis, data engineers ingest and process most analytical data in batches with pipelines designed to update specific data sets at a similar frequency in which they are consumed. Data platforms are no exception.

Data Pipeline 98

Data Pipeline Data Data Warehouse Machine Learning 98

Data Engineering Podcast

SEPTEMBER 4, 2022

In this episode Gopal Erinjippurath discusses the data engineering challenges of building and serving those data sets, and how they are distilling complex climate information into consumable facts so you don’t have to be an expert to understand it. Data stacks are becoming more and more complex.

MongoDB 100

MongoDB Scala MySQL Data Ingestion 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

Databand.ai

JULY 17, 2023

By adopting a set of best practices inspired by Agile methodologies, DevOps principles, and statistical process control techniques, DataOps helps organizations deliver high-quality data insights more efficiently. Better data observability equals better data quality.

Data Pipeline 52

Data Pipeline Machine Learning High Quality Data BI 52

ProjectPro

FEBRUARY 6, 2023

Google Cloud Pub/Sub is a global, cloud-based messaging framework that has become increasingly popular among data engineers over recent years. Data engineers often use Google Cloud Pub/Sub to design asynchronous workflows, publish event notifications, and stream data from several processes or devices.

Google Cloud 52

Google Cloud Cloud Cloud Storage Data Ingestion 52