Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. Each type of tool plays a specific role in the DataOps process, helping organizations manage and optimize their data pipelines more effectively.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Monte Carlo

MAY 14, 2024

Apache ORC (Optimized Row Columnar) : In 2013, ORC was developed for the Hadoop ecosystem to improve the efficiency of data storage and retrieval. This development was crucial for enabling both batch and streaming data workflows in dynamic environments, ensuring consistency and durability in big data processing.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Databand.ai

AUGUST 30, 2023

These experts will need to combine their expertise in data processing, storage, transformation, modeling, visualization, and machine learning algorithms, working together on a unified platform or toolset.

Data Governance 40

Data Governance Data Cleanse Government Data Pipeline 40

DataKitchen

APRIL 13, 2021

Process Analytics. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Apache Oozie — An open-source workflow scheduler system to manage Apache Hadoop jobs.

Consulting 120

Consulting Machine Learning Data Science Data Pipeline 120

phData: Data Engineering

JANUARY 3, 2022

How do I know where this data came from or how it’s being used? How do I maintain all my data pipelines? How do I recreate the environment and data sets from scratch? How do I build confidence and trust in the data products I create? How do I ensure customers aren’t impacted by changes or new functionality?

IT 52

IT AWS Software Engineer Software Engineering 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59