Xebia

JANUARY 19, 2023

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

Data Engineering 130

Data Engineering Engineering Data Technical Review 130

Altexsoft

JANUARY 14, 2021

The variety of data explodes and on-premises options fail to handle it. Apart from the lack of scalability and flexibility offered by modern databases, the traditional ones are costly to implement and maintain. At the moment, cloud-based data warehouse architectures provide the most effective employment of data warehousing resources.

Backup 115

Backup Azure Software Review Architecture 115

Altexsoft

JULY 29, 2022

What happens, when a data scientist, BI developer , or data engineer feeds a huge file to Hadoop? Under the hood, the framework divides a chunk of Big Data into smaller, digestible parts and allocates them across multiple commodity machines to be processed in parallel. Scalability. Apache Hadoop architecture.

Big Data 59

Big Data Data Google Cloud Open Source 59

Altexsoft

APRIL 26, 2022

With the consistent rise in data volume, variety, and velocity, organizations started seeking special solutions to store and process the information tsunami. This demand gave birth to cloud data warehouses that offer flexibility, scalability, and high performance. As such, it is considered cloud-agnostic.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. All data goes through the middleman — in our case, Kafka — that manages messages and ensures their security.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Cloudera

DECEMBER 12, 2018

Yet, there were some limitations in MPP at the time, because some of these systems running Hive were quite large, and the database community thought that instead of the future being Hive on MapReduce or something similar, that we could extend, bend, and change the MPP engines to actually operate in a more scalable manner on such large data.

Data 42

Data Marketing Storage Big Data 42

Altexsoft

MARCH 30, 2023

Shell, Adobe, Burberry, Columbia, Bayer — you definitely know the names. The answer is simple: They use the same technology to make the most of data. Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions.

Weak Development Team 64

Weak Development Team Artificial Inteligence Machine Learning Software Review 64