Databand.ai

AUGUST 30, 2023

Here are some of the reasons why DataOps tools are important: Improved Collaboration DataOps tools enable better collaboration between data teams, including data engineers, data scientists, and data analysts. This enables data teams to quickly and easily find the data they need for their analytics projects.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

AltexSoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. The ELT workflow. Aggregation. Please note!

Process 52

Process Building Raw Data Data Lake 52

Netflix Tech

MARCH 25, 2019

Our data ingestion approach, in a nutshell, is classified broadly into two buckets?—?push In this model, we scan system logs and metadata generated by various compute engines to collect corresponding lineage data. push or pull. Today, we are operating using a pull-heavy model.

Building 87

Building Metadata Transportation Data Ingestion 87

phData: Data Engineering

AUGUST 4, 2023

Snowflake hides user data objects and makes them accessible only through SQL queries through the compute layer. It handles the metadata related to these objects, access control configurations, and query optimization statistics. This includes tasks such as data cleansing, enrichment, and aggregation.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

ProjectPro

JANUARY 31, 2023

Big Data Interview Questions and Answers Based on Job Role With the help of ProjectPro experts, we have compiled a list of interview questions on big data based on several job roles, including big data tester, big data developer, big data architect, and big data engineer.

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Big Data Hadoop AWS Relational Database 52

RandomTrees

FEBRUARY 6, 2024

Data engineering, the practice of collecting, transforming, and organizing data for analysis, is poised for a significant transformation with the advent of Generative Artificial Intelligence (Gen AI). Generative AI with ETL Pipelines: Generative AI can be used to automate the creation of ETL pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

OCTOBER 20, 2021

Having multiple data integration routes helps optimize the operational as well as analytical use of data. Experimentation in production Big Data Data Warehouse for core ETL tasks Direct data pipelines Tiered Data Lake 4. If Data Science were a linear activity, it would be called Data Engineering.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

Rockset

SEPTEMBER 6, 2019

I could be describing either the VR space or Data Engineering, but in fact this post is about the intersection of both. Virtual Reality – The Next Frontier in Media I work as a Data Engineer at a leading company in the VR space, with a mission to capture and transmit reality in perfect fidelity.

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Metadata Kafka Data Cleanse SQL 40

DataKitchen

JUNE 24, 2021

In May 2021 at the CDO & Data Leaders Global Summit, DataKitchen sat down with the following data leaders to learn how to use DataOps to drive agility and business value. Kurt Zimmer, Head of Data Engineering for Data Enablement at AstraZeneca. Jim Tyo, Chief Data Officer, Invesco.

Pipeline-centric 84

Pipeline-centric Manufacturing Education Data Cleanse 84

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.

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Data Warehouse Pipeline-centric Government Data 52