Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

Altexsoft

JUNE 29, 2021

In a world fueled by disruptive technologies, no wonder businesses heavily rely on machine learning. Google, in turn, uses the Google Neural Machine Translation (GNMT) system, powered by ML, reducing error rates by up to 60 percent. But no technology can work efficiently without human experts behind it.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Cloudera

DECEMBER 15, 2022

With CDP, customers can deploy storage, compute, and access, all with the freedom offered by the cloud, avoiding vendor lock-in and taking advantage of best-of-breed solutions. The new capabilities of Apache Iceberg in CDP enable you to accelerate multi-cloud open lakehouse implementations. Performance and scalability.

Cloud 78

Cloud Data Analytics Machine Learning 78

Altexsoft

MARCH 30, 2023

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. How data engineering works in 14 minutes. Who makes data useful?

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Altexsoft

JANUARY 14, 2021

From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. For over 30 years, data warehouses have been a rich business-insights source. Scalability opportunities. Scalability.

Backup 115

Backup Azure Software Review Systems Review 115

Exadel

FEBRUARY 20, 2023

The technological landscape has evolved to include AI assistants, self-driving cars, and machine learning solutions that process data in a blink of an eye. AI is by far the technology that can drive innovation forward, and you should keep up. Cloud-based AI services make this possible.

Artificial Inteligence 52

Artificial Inteligence Cloud Machine Learning Azure 52

Altexsoft

JULY 29, 2022

The biggest star of the Big Data world, Hadoop was named after a yellow stuffed elephant that belonged to the 2-year son of computer scientist Doug Cutting. The toy became the official logo of the technology, used by the major Internet players — such as Twitter, LinkedIn, eBay, and Amazon. Scalability. The Hadoop toy.

Big Data 59

Big Data Data Google Cloud Storage 59

Perficient

FEBRUARY 16, 2024

In the world of big data processing, efficient and scalable file systems play a crucial role. It abstracts away the complexities of dealing with different storage backends, making it easier for data engineers and data scientists to focus on their analysis and machine learning tasks. What is DBFS?

System 52

System Storage Azure Big Data 52

Altexsoft

DECEMBER 4, 2020

Businesses can no longer count on using the same technologies for decades. So data migration is an unavoidable challenge each company faces once in a while. Transferring data from one computer environment to another is a time-consuming, multi-step process involving such activities as planning, data profiling, testing, to name a few.

Software Review 69

Software Review Software Data Technical Review 69

Capgemini

MARCH 31, 2024

Generative AI (GenAI) has catapulted data science, machine learning, and AI into the limelight, sparking conversations and at all levels of business and democratizing access to the power of AI. Among the many impacts of GenAI, one of the greatest transformations underway is that of Software & Platform Engineering.

Software Engineering 52

Software Engineering Engineering Software Generative AI 52

Capgemini

JANUARY 17, 2023

For the second year in a row, Databricks recently partnered with MIT Technology Review Insights to survey 600 CIOs, CTOs, and CDOs from large enterprises. The key result: CxOs and boards recognize that their organizations’ ability to generate actionable insights from data, often in real-time, is of the highest strategic importance.

Strategy 52

Strategy Technical Review Data Artificial Inteligence 52

Altexsoft

APRIL 26, 2022

This demand gave birth to cloud data warehouses that offer flexibility, scalability, and high performance. For everyone who is considering Snowflake as a part of their technology stack, this article is a great place to start the journey. Data warehousing in a nutshell. As such, it is considered cloud-agnostic.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

OCTOBER 21, 2022

Kafka can continue the list of brand names that became generic terms for the entire type of technology. Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. Scalability. If only Jay had different tastes.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

O'Reilly Media - Ideas

JUNE 4, 2019

Programming with Data: Advanced Python and Pandas , July 9. Understanding Data Science Algorithms in R: Regression , July 12. Cleaning Data at Scale , July 15. Scalable Data Science with Apache Hadoop and Spark , July 16. Effective Data Center Design Techniques: Data Center Topologies and Control Planes , July 19.

Course 68

Course Training Artificial Inteligence Software Review 68

ParkMyCloud

JANUARY 17, 2020

Individuals in an associate solutions architect role have 1+ years of experience designing available, fault-tolerant, scalable, and most importantly cost-efficient, distributed systems on AWS. Must prove knowledge of deploying, operating and managing highly available, scalable and fault-tolerant systems on AWS.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Altexsoft

JULY 19, 2022

No matter how ridiculous it may sound, the famous quote is applicable to the technology world in many ways. In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. What data mesh is and is not.

Architecture 52

Architecture Data Analytics Data Engineering 52

O'Reilly Media - Ideas

JUNE 5, 2019

Programming with Data: Advanced Python and Pandas , July 9. Understanding Data Science Algorithms in R: Regression , July 12. Cleaning Data at Scale , July 15. Scalable Data Science with Apache Hadoop and Spark , July 16. Effective Data Center Design Techniques: Data Center Topologies and Control Planes , July 19.

Course 51

Course Training Artificial Inteligence Software Review 51

Altexsoft

NOVEMBER 7, 2022

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. What is Apache Airflow?

Weak Development Team 52

Weak Development Team Technical Review Software Review Systems Review 52

Cloudera

DECEMBER 12, 2018

I would like to start off by asking you to tell us about your background and what kicked off your 20-year career in relational database technology? Greg Rahn: So, folks like Mike Stonebraker made comments that Hive, and this MapReduce approach, was already outdated and there’s better technology that the RDBMS community can help drive.

Data 42

Data Marketing Storage Big Data 42

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview.

Analytics 20

Analytics Data IoT Analysis 20