ParkMyCloud

JANUARY 17, 2020

Can demonstrate how to build and deploy applications on AWS. Azure Data Engineer Associate. For individuals that design and implement the management, security, monitoring, and privacy of data – using the full stack of Azure data services – to satisfy business needs. . Azure IoT Developer Specialty.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Confluent

FEBRUARY 6, 2019

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

O'Reilly Media - Ideas

JUNE 4, 2019

Spotlight on Cloud: Mitigating Cloud Complexity to Ensure Your Organization Thrives with David Linthicum , August 1. How to Be a Better Mentor , August 5. How to Give Great Presentations , August 13. Systems engineering and operations. Google Cloud Platform – Professional Cloud Developer Crash Course , June 6-7.

Course 65

Course Training Artificial Inteligence Software Review 65

O'Reilly Media - Ideas

JUNE 5, 2019

Spotlight on Cloud: Mitigating Cloud Complexity to Ensure Your Organization Thrives with David Linthicum , August 1. How to Be a Better Mentor , August 5. How to Give Great Presentations , August 13. Systems engineering and operations. Google Cloud Platform – Professional Cloud Developer Crash Course , June 6-7.

Course 49

Course Training Artificial Inteligence Software Review 49

CIO

JULY 14, 2023

But you want to adopt them to avoid competitive disadvantage, especially as they often arrive as new features in applications that staff already know how to use. In the shaper model, you’re leveraging existing foundational models, off the shelf, but retraining them with your own data.” Every company will be doing that,” he adds. “In

Generative AI 209

Generative AI Artificial Inteligence Open Source ChatGPT 209

Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Apiumhub

AUGUST 12, 2021

His main work is software development consulting, which combines actually writing code with advising clients on how to do that better. Launching 24/7 digital platforms made him appreciate how much cloud technologies are developer superpowers. Currently, he is the T. Rex of Codosaurus, LLC in Fairfax, Virginia, USA. Twitter: ??

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Apiumhub

APRIL 18, 2019

How to split your software into microservices by Linda van der Pal Joanne Boerstoel Régina ten Bruggencate. & Alex Soto – Java Champion, Engineer @ Red Hat. David Gageot – Developer Advocate at Google Cloud. Oscar Sacristán Agulló – Data Engineer at Zara. & & many others.

Technical Review 57

Technical Review Microservices Software Review CTO Coach 57

Altexsoft

AUGUST 25, 2021

Specifics of data used in NLP. And finally, what stands in the way of NLP adoption and how to overcome it. Sentiment analysis results by Google Cloud Natural Language API. What should it be like and how to prepare a great one? Great training data is a key to NLP success. But what makes data great?

Tools 139

Tools Artificial Inteligence Technical Review Systems Review 139

O'Reilly Media - Ideas

MAY 1, 2019

Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , May 20. First Steps in Data Analysis , May 20. Data Analysis Paradigms in the Tidyverse , May 30. Data Visualization with Matplotlib and Seaborn , June 4. Systems engineering and operations.

Course 46

Course Training Artificial Inteligence Machine Learning 46

Xebia

FEBRUARY 25, 2024

This post is based on a tutorial given at EuroPython 2023 in Prague: How to MLOps: Experiment tracking & deployment and a Code Breakfast given at Xebia Data together with Jeroen Overschie. Data science is generally not operationalized Consider a data flow from a machine or process, all the way to an end-user.

Applications 130

Applications Technical Review Software Review Azure 130

O'Reilly Media - Ideas

SEPTEMBER 15, 2021

Google Cloud is an obvious omission from this story. While Google is the third-most-important cloud provider, only 26 respondents (roughly 1%) claimed any Google certification, all under the “Other” category. Average salary change by certification. Average salary change vs. type of training. The Last Word.

Survey 145

Survey Data Technical Review Training 145

O'Reilly Media - Ideas

MARCH 6, 2019

How to Be a Better Mentor , April 3. Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , March 13. Data Modelling with Qlik Sense , March 19-20. Foundational Data Science with R , March 26-27. What You Need to Know About Data Science , April 1.

Course 10

Course Artificial Inteligence Training Microservices 10

Perficient

FEBRUARY 28, 2023

Once data is in the Data Lake, the data can be made available to anyone. You don’t need an understanding of how data is related when it is ingested; rather, it relies on the data engineers and end-users to define those relationships as they consume it.

Data 110

Data Analytics Google Cloud Cloud 110

Cloudera

MAY 13, 2021

Fixed Reports / Data Engineering jobs . Often mission-critical to the various lines of business (risk analytics, platform support, or data engineering), which hydrate critical data pipelines for downstream consumption. Fixed Reports / Data Engineering Jobs. Data Engineering jobs only.

Data Engineering 73

Data Engineering Cloud Weak Development Team Resources 73

Altexsoft

JULY 29, 2022

But to understand why Hadoop is so lucrative we need to look at how the framework works from the inside. What happens, when a data scientist, BI developer , or data engineer feeds a huge file to Hadoop? How data engineering works under the hood. So, how to tame the elephant? Robust community.

Big Data 59

Big Data Data Google Cloud Storage 59

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

O'Reilly Media - Ideas

JANUARY 25, 2024

The kind of fluency that you need to look at a problem and understand how to solve it doesn’t come from asking simple “How do I do this?” Nor does it preclude asking lots of “I forgot how this function works” questions. Data engineering deals with the problem of storing data at scale and delivering that data to applications.

Trends 115

Trends Technical Review Technology Artificial Inteligence 115

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

StubHub

AUGUST 8, 2019

Rudra Gandhi, Data Engineering intern, (San Jose State University, Mathematics and Computer Science Major): As a company, I thought that StubHub is an interactive platform for its audiences and accepts feedback very nicely. For the second project, we have been testing data and comparing it with different platforms.

Technical Review 8

Technical Review Software Review Software Engineering Sport 8

O'Reilly Media - Ideas

MARCH 1, 2023

Data Data is another very broad category, encompassing everything from traditional business analytics to artificial intelligence. Data engineering was the dominant topic by far, growing 35% year over year. Data engineering deals with the problem of storing data at scale and delivering that data to applications.

Trends 134

Trends Technical Review Technology Software Review 134

Altexsoft

JANUARY 14, 2021

Modern cloud solutions, on the other hand, cover the needs of high performance, scalability, and advanced data management and analytics. At the moment, cloud-based data warehouse architectures provide the most effective employment of data warehousing resources. Data loading. Data loading.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

JULY 19, 2022

Data mesh is another hot trend in the data industry claiming to be able to solve many issues of its predecessors. This post explains the data mesh, how it works, what organizations may benefit from its implementation, and how to approach this new data management unicorn. What is a data mesh?

Architecture 52

Architecture Data Analytics Data Engineering 52

Altexsoft

APRIL 16, 2021

We’ll cover the fundamentals of OLAP and see how it works in contrast to transactional databases. Namely, we’ll explain what functions it can perform, and how to use it for data analysis. An overview of data warehouse types. What is data pipeline. Extract, transform, load or ETL process guide. Building a cube.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

Altexsoft

APRIL 26, 2022

Initially built on top of the Amazon Web Services (AWS), Snowflake is also available on Google Cloud and Microsoft Azure. As such, it is considered cloud-agnostic. Modern data pipeline with Snowflake technology as its part. BTW, we have an engaging video explaining how data engineering works.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

DECEMBER 4, 2020

Three types of data migration tools. Automation scripts can be written by data engineers or ETL developers in charge of your migration project. This makes sense when you move a relatively small amount of data and deal with simple requirements. How to choose the right data migration solution. Functionality.

Software Review 69

Software Review Software Data Technical Review 69

Daniel Bryant

SEPTEMBER 13, 2019

What was worth noting was that (anecdotally) even engineers from large organisations were not looking for full workload portability (i.e. There were also two patterns of adoption of HashiCorp tooling I observed from engineers that I chatted to: Infrastructure-driven?—?in

Infrastructure 8

Infrastructure Azure Software Engineering Cloud 8

O'Reilly Media - Ideas

MARCH 31, 2022

Data always looks much better before you’ve tried to work with it. Finding those problems, and learning how to deal with them, is an important step toward developing a truly mature AI practice. We can rephrase these skills as core AI development, building data pipelines, and product management. Use of AutoML tools.

Enterprise 109

Enterprise Artificial Inteligence Government Budget 109

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. How Apache Kafka streams relate to Franz Kafka’s books. The pull-based approach enables apps to read data at individual rates and choose how to consume information — in real-time or in batch mode.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Altexsoft

DECEMBER 15, 2021

The rest is done by data engineers, data scientists , machine learning engineers , and other high-trained (and high-paid) specialists. The technology supports tabular, image, text, and video data, and also comes with an easy-to-use drag-and-drop tool to engage people without ML expertise. Source: Google Cloud Blog.

Machine Learning 59

Machine Learning Artificial Inteligence How To Azure 59

Altexsoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

O'Reilly Media - Ideas

JANUARY 25, 2022

A quick look at bigram usage (word pairs) doesn’t really distinguish between “data science,” “data engineering,” “data analysis,” and other terms; the most common word pair with “data” is “data governance,” followed by “data science.” That’s an important aspect of becoming cloud native.

Trends 109

Trends Technical Review Technology Artificial Inteligence 109

DataRobot

FEBRUARY 2, 2022

DataRobot enables entire teams — from data scientists to data engineers and from IT to business users — to collaborate on a unified platform. Every organization is under growing pressure to transform this sea of data into valuable insights. AI is how to turn data into insight and impact — and a competitive edge.

Cloud 52

Cloud Innovation Google Cloud Azure 52

UruIT

APRIL 27, 2020

You may recognize the ways that Machine Learning can improve your life and work but may not know how to implement it in your own company. Google Cloud . MathWork focused on the development of these tools to become experts in high-end financial use and data engineering contexts.

Artificial Inteligence 78

Artificial Inteligence Machine Learning Azure Software Review 78

O'Reilly Media - Ideas

JANUARY 25, 2021

We need programmers who are thinking about how to use functional and object-oriented features together; what practices and patterns make sense when building enterprise-scale concurrent software? It’s no surprise that the cloud is growing rapidly. Usage of content about the cloud is up 41% since last year. The result?

Programming 145

Programming Cloud Artificial Inteligence Machine Learning 145

UruIT

JULY 23, 2019

In order to plan how to train you to learn and evolve itself, an important step is to define which development and deployment platform for Machine Learning you’ll use. MathWork focused on the development of these tools in order to become experts on high-end financial use and data engineering contexts.

Artificial Inteligence 81

Artificial Inteligence Machine Learning Azure Software Review 81