Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 90

Data Lake Data Warehouse BI SQL 90

Cloudera

DECEMBER 19, 2018

Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Business intelligence (BI), an umbrella term coined in 1989 by Howard Dresner, Chief Research Officer at Dresner Advisory Services, refers to the ability of end-users to access and analyze enterprise data.

BI 52

BI Cloud Computing Data Warehouse Big Data 52

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Deploying modern data architectures. Lack of sharing hinders the elimination of fraud, waste, and abuse. Forrester ).

Data Architecture 76

Data Architecture Architecture Data Lake NoSQL 76

Knowledge Hut

DECEMBER 21, 2023

Senior Data Engineer A senior data engineer is a more advanced position that involves leading the design, building, and data infrastructure maintenance. They are accountable for managing a team of junior data engineers and ensuring the data architecture meets the organization's needs.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Knowledge Hut

MAY 3, 2024

A new breed of ‘Fast Data’ architectures has evolved to be stream-oriented, where data is processed as it arrives, providing businesses with a competitive advantage. Dean Wampler (Renowned author of many big data technology-related books) Dean Wampler makes an important point in one of his webinars.

Kafka 98

Kafka Scala Java Amazon Web Services 98

Monte Carlo

JUNE 14, 2023

While it might be tempting to continue using custom code to transform your data, it does increase the chances of errors being made as the code is not easily replicable and must be rewritten every time a process takes place. Learn more by checking out the webinar they did with Snowflake. Now Go Build Some Data Pipelines!

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. To learn more about DataOps Engineering, watch our webinar on this topic, A Day In the Life of A DataOps Engineer. A DataOps implementation project consists of three steps. About the Author.

Engineering 60

Engineering BI Business Analyst Metadata 60