Cloudera

FEBRUARY 9, 2021

A typical approach that we have seen in customers’ environments is that ETL applications pull data with a frequency of minutes and land it into HDFS storage as an extra Hive table partition file. In this way, the analytic applications are able to turn the latest data into instant business insights. Design Detail.

Data Warehouse 72

Data Warehouse Cloud Kafka Cloud Storage 72

Towards Data Science

NOVEMBER 4, 2023

Back in October, I wrote about the rise of the Data Engineer, the role, its challenges, responsibilities, daily routine and how to become successful in this field. The data engineering landscape is constantly changing but major trends seem to remain the same. So here are a few things to consider that can help us answer these questions.

Data Engineering 79

Data Engineering Data Engineer Engineering BI 79

Netflix Tech

DECEMBER 14, 2018

data access semantics that guarantee repeatable data read behavior for client applications. The following section enumerates the key traits of NMDB and how the design aims to address them. key value stores generally allow storing any data under a key). However unlike the media data schema, MID schema is immutable.

Media 94

Media Database Metadata Data Schemas 94

Monte Carlo

FEBRUARY 6, 2023

In this post, we’ll examine some best practices for migrating your data to a cloud solution, show you how to develop your own migration strategy, and take a closer look at some popular cloud warehouse solutions that you might consider for your platform. First, start by defining how you’ll utilize your cloud solution.

Data Warehouse 52

Data Warehouse AWS Data Validation Data 52