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

JUNE 17, 2023

Sign up free at dataengineeringpodcast.com/rudderstack - Your host is Tobias Macey and today I'm interviewing Satish Jayanthi about the practice and promise of building a column-aware data architecture through intentional modeling Interview Introduction How did you get involved in the area of data management?

Data Lake 130

Data Lake Metadata Machine Learning Data Architecture 130

Knowledge Hut

MARCH 28, 2024

Job Role 1: Azure Data Engineer Azure Data Engineers develop, deploy, and manage data solutions with Microsoft Azure data services. They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Data Engineering Podcast

JULY 3, 2022

Go to dataengineeringpodcast.com/atlan today to learn more about how Atlan’s active metadata platform is helping pioneering data teams like Postman, Plaid, WeWork & Unilever achieve extraordinary things with metadata and escape the chaos. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Architecture 100

Architecture Metadata MongoDB MySQL 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

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. Delta Live Tables : Released by Databricks in 2022, Delta Live Tables extend the capabilities of Delta Lake by focusing on automating and simplifying data pipeline constructions.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Data Engineering Podcast

APRIL 3, 2022

Summary The flexibility of software oriented data workflows is useful for fulfilling complex requirements, but for simple and repetitious use cases it adds significant complexity. Coalesce is a platform designed to reduce repetitive work for common workflows by adopting a visual pipeline builder to support your data warehouse transformations.

Data Warehouse 100

Data Warehouse Data Workflow Data Architecture SQL 100

Knowledge Hut

DECEMBER 21, 2023

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? Data engineering is the method to collect, process, validate and store data. It involves building and maintaining data pipelines, databases, and data warehouses.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Towards Data Science

APRIL 3, 2023

The most prominent, recent examples are Snowflake and Databricks disrupting the concept of the database and ushering in the modern data stack era. As part of this movement, Fivetran and dbt fundamentally altered the data pipeline from ETL to ELT. Zero-ETL What it is : A misnomer for one thing; the data pipeline still exists.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Data Engineering Podcast

OCTOBER 2, 2021

If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. What are the driving factors for building a real-time data platform?

Building 100

Building BI Data Architecture Architecture 100

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Monte Carlo

AUGUST 31, 2023

As the data analyst or engineer responsible for managing this data and making it usable, accessible, and trustworthy, rarely a day goes by without having to field some request from your stakeholders. But what happens when the data is wrong? In our opinion, data quality frequently gets a bad rep.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

JUNE 30, 2023

The essential theories, procedures, and equipment for creating trustworthy and effective data systems are covered in this book. It explores subjects including data modeling, data pipelines, data integration, and data quality, offering helpful advice on organizing and implementing reliable data solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. The past decades of enterprise data platform architectures can be summarized in 69 words. Introduction to Data Mesh. The product includes data and operations.

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Scala 98

Knowledge Hut

NOVEMBER 17, 2023

They work with various stakeholders to provide real-time data analytics, maintain data quality and integrity, and deliver insightful data to the business. The main duties of an Azure Data Engineer are planning, developing, deploying, and managing the data pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Databand.ai

JULY 19, 2023

This capability is useful for businesses, as it provides a clear and comprehensive view of their data’s history and transformations. Data lineage tools are not a new concept. In this article: Why Are Data Lineage Tools Important?

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Monte Carlo

JANUARY 24, 2024

More data, more access to data, and more regulations mean data governance has become a higher-stakes game. As you prepare to roll out a successful data governance strategy at your organization, keep an eye on the following four trends that will shape the future of data governance.

Data Governance 52

Data Governance Government Data Lake Data Architecture 52

Airbnb Tech

NOVEMBER 3, 2020

During this transformation, Airbnb experienced the typical growth challenges that most companies do, including those that affect the data warehouse. This post explores the data challenges Airbnb faced during hyper growth and the steps we took to overcome these challenges.

Data Warehouse 52

Data Warehouse Scala Datasets Data Engineering 52

Knowledge Hut

NOVEMBER 28, 2023

Technical Data Engineer Skills 1.Python Python Python is one of the most looked upon and popular programming languages, using which data engineers can create integrations, data pipelines, integrations, automation, and data cleansing and analysis.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Monte Carlo

FEBRUARY 9, 2023

Over the past several years, data warehouses have evolved dramatically, but that doesn’t mean the fundamentals underpinning sound data architecture needs to be thrown out the window. What is a Data Vault model? How do you implement a data vault architecture?

Architecture 52

Architecture Raw Data Metadata Data Warehouse 52

Ascend.io

FEBRUARY 28, 2024

Engineers ensure the availability of clean, structured data, a necessity for AI systems to learn from patterns, make accurate predictions, and automate decision-making processes. Through the design and maintenance of efficient data pipelines , data engineers facilitate the seamless flow and accessibility of data for AI processing.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Cloudera

FEBRUARY 14, 2022

It’s no longer driven by data volumes, but containerization, separation of storage and compute, and democratization of analytics. The same key tenants powering DE in the public clouds are now available in the data center. Data Engineering should not be limited by one cloud vendor or data locality.

Data Engineering 112

Data Engineering Data Engineer Engineering Data Pipeline 112

Monte Carlo

JULY 27, 2023

The most common use case data quality engineers support are: Analytical dashboards : Mentioned in 56% of job postings Machine learning or data science teams : Mentioned in 34% of postings Gen AI : Mentioned in one job posting (but really emphatically).

Engineering 52

Engineering Healthcare Scala Data Warehouse 52

AltexSoft

FEBRUARY 11, 2023

To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. What is the main difference between a data architect and a data engineer?

Data Architect 87

Data Architect Certification Generalist Big Data 87

Airbnb Tech

NOVEMBER 24, 2020

During this transformation, Airbnb experienced the typical growth challenges that most companies do, including those that affect the data warehouse. In the first post of this series, we shared an overview of how we evolved our organization and technology standards to address the data quality challenges faced during hyper growth.

Data Warehouse 52

Data Warehouse Certification Data Pipeline Data 52

Data Engineering Podcast

JUNE 3, 2019

He also discusses how the abstractions provided by DataCoral allows his data scientists to remain productive without requiring dedicated data engineers. If you are either considering how to build a data pipeline or debating whether to migrate your existing ETL to a service this is definitely worth listening to for some perspective.

Media 100

Media Data Pipeline Machine Learning Data Science 100

Data Engineering Podcast

NOVEMBER 18, 2019

Summary With the constant evolution of technology for data management it can seem impossible to make an informed decision about whether to build a data warehouse, or a data lake, or just leave your data wherever it currently rests. Raghu Murthy, founder and CEO of Datacoral built data infrastructures at Yahoo!

Data Lake 100

Data Lake Scala Data Warehouse Hadoop 100

Ascend.io

JULY 17, 2023

The core tenet of the data mesh is to distribute responsibility and governance of your data across different business “domains”. This is the opposite of having a single, monolithic data architecture managed by a centralized data team. There’s no return to the old days of siloed data warehouses.

Datasets 52

Datasets Telecommunication Architecture Government 52

Silectis

JANUARY 22, 2021

In this demo, we’ll show you how native tools in the Magpie data engineering platform play well with Snowflake, ultimately, allowing your team to do more in a centralized data engineering environment. This is an important piece of a modern and reliable data architecture.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Cloudera

FEBRUARY 22, 2021

The Cloudera Data Platform (CDP) represents a paradigm shift in modern data architecture by addressing all existing and future analytical needs. without integration delays or having to deal with fragmented data silos that result in operational inefficiencies. . Technology cost reduction / avoidance.

Data Warehouse 79

Data Warehouse Data Governance Government Cloud 79

Silectis

JANUARY 3, 2021

Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse. Data Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Monte Carlo

NOVEMBER 21, 2022

That gives a lot of credence to the idea you can look at Snowflake’s revenues as a proxy for what’s happening in the larger data ecosystem. billion in four years, which underscores the terrific demand there is for cloud data warehouses. Snowflake went from a hundred million in revenue to about 1.2

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

AltexSoft

OCTOBER 30, 2021

They’re integral specialists in data science projects and cooperate with data scientists by backing up their algorithms with solid data pipelines. Juxtaposing data scientist vs engineer tasks. One data scientist usually needs two or three data engineers. Managing data and metadata. Programming.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

Monte Carlo

AUGUST 31, 2023

Below, we share an excerpt from Data Quality Fundamentals: A Practical Guide to Building Trustworthy Data Pipelines , written by Barr Moses, Lior Gavish, and Molly Vorwerck. On the surface, it may seem like Data Quality Fundamentals is a manual about how to clean, wrangle, and generally make sense of data – and it does.

Data Pipeline 40

Data Pipeline Data Lake Data Data Warehouse 40

phData: Data Engineering

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Monte Carlo

NOVEMBER 10, 2022

Cookies unfortunately also enabled more nefarious actors to capture and share customer data that didn’t have consumers’ best interests in mind. Instead, it’s the enterprise data warehouse /lakehouse, and enriched first-party data, not the CDP nor the CRM, that must occupy the center of our marketing analytics kingdom.

Pipeline-centric 52

Pipeline-centric Data Warehouse Data Data Ingestion 52

Knowledge Hut

MARCH 13, 2024

While working as a big data engineer, there are some roles and responsibilities one has to do: Designing large data systems starts with designing a capable system that can handle large workloads. Develop the algorithms: Once the database is ready, the next thing is to analyze the data to obtain valuable insights.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52