InfoWorld

FEBRUARY 9, 2024

It is built around a data lake called OneLake, and brings together new and existing components from Microsoft Power BI, Azure Synapse, and Azure Data Factory into a single integrated environment. To read this article in full, please click here In many ways, Fabric is Microsoft’s answer to Google Cloud Dataplex.

Big Data 78

Big Data Data Azure Google Cloud 78

InfoQ Culture Methods

DECEMBER 28, 2020

As 2020 is coming to an end, we created this article listing some of the best posts published this year. This collection was hand-picked by nine InfoQ Editors recommending the greatest posts in their domain. It's a great piece to make sure you don't miss out on some of the InfoQ's best content.

Continuous Delivery 85

Continuous Delivery Google Cloud Data Engineering Microservices 85

Altexsoft

JUNE 29, 2021

This article will focus on the role of a machine learning engineer, their skills and responsibilities, and how they contribute to an AI project’s success. The role of a machine learning engineer in the data science team. Who does what in a data science team. Machine learning engineer vs. data scientist.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Altexsoft

JULY 23, 2020

This article. It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development. Data validation. Data preparation.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

Altexsoft

JANUARY 14, 2021

Though there are countless options for storing, analyzing, and indexing data, data warehouses have remained to the point. When reviewing BI tools , we described several data warehouse tools. In this article, we’ll take a closer look at the top cloud warehouse software, including Snowflake, BigQuery, and Redshift.

Backup 115

Backup Azure Software Review Architecture 115

Existek

JANUARY 11, 2022

We suggest drawing a detailed comparison of Azure vs AWS to answer these questions. Azure vs AWS market share. What is Microsoft Azure used for? Azure vs AWS features. Azure vs AWS comparison: other practical aspects. Azure vs AWS comparison: other practical aspects. Azure vs AWS: which is better?

Azure 52

Azure AWS Cloud How To 52

Altexsoft

FEBRUARY 11, 2023

This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. Hiring a well-skilled data architect can be very helpful for that purpose. What is a data architect? What is the main difference between a data architect and a data engineer?

Data 87

Data Data Engineering Big Data Architecture 87

The Citus Data

MARCH 31, 2023

(EMEA livestream, Citus team, Citus performance, benchmarking, HammerDB, PostgreSQL) 2 Azure Cosmos DB for PostgreSQL talks (aka Citus on Azure) Auto scaling Azure Cosmos DB for PostgreSQL with Citus, Grafana, & Azure Serverless , by Lucas Borges Fernandes, a software engineer at Microsoft. (on-demand

Azure 84

Azure Open Source Virtualization Software Engineering 84

Altexsoft

MARCH 30, 2023

Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions. In this article, we’ll highlight the reasoning behind this choice and the challenges related to it. How data engineering works in 14 minutes.

Weak Development Team 64

Weak Development Team Artificial Inteligence Machine Learning Software Review 64

Altexsoft

APRIL 16, 2021

However, when it comes to analyzing large volumes of data from different angles, the logic of OLTP has serious limitations. So, we need a solution that’s capable of representing data from multiple dimensions. In this article, we’ll talk about such a solution —- Online Analytical Processing , or OLAP technology. Building a cube.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

UruIT

JULY 23, 2019

.” Microsoft’s Azure Machine Learning Studio. Microsoft’s set of tools for machine learning includes Azure Machine Learning (which also covers Azure Machine Learning Studio), Power BI, Azure Data Lake, Azure HDInsight, Azure Stream Analytics and Azure Data Factory.

Artificial Inteligence 81

Artificial Inteligence Machine Learning Azure Software Review 81

Cloudera

MAY 18, 2021

Finally, IaaS deployments required substantial manual effort for configuration and ongoing management that, in a way, accentuated the complexities that clients faced deploying legacy Hadoop implementations in the data center. Experience configuration / use case deployment: At the data lifecycle experience level (e.g., 1 Year Reserved

Cloud 86

Cloud Technical Review Storage Backup 86

UruIT

APRIL 27, 2020

Microsoft’s Azure Machine Learning Studio . Microsoft’s set of tools for ML includes Azure Machine Learning (including Azure Machine Learning Studio), Power BI, Azure Data Lake, Azure HDInsight, Azure Stream Analytics and Azure Data Factory. Pricing: try it out free for 12-months.

Artificial Inteligence 78

Artificial Inteligence Machine Learning Azure Software Review 78

Apiumhub

NOVEMBER 20, 2023

Andrea Tosato – Software Architect at Open Job Metis Andrea is a green software speaker, Microsoft MVP in Azure, and Developer Technologies, recognized for outstanding contributions. Paola Annis – Engineering Manager at Microsoft With more than 25 years of experience in the IT industry, Paola E.

Fractional CTO 83

Fractional CTO Software CTO Sustainability 83

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Temporal data and time-series analytics. Forecasting Financial Time Series with Deep Learning on Azure”. Foundational data technologies. Machine learning and AI require data—specifically, labeled data for training models. Text and Language processing and analysis. Graph technologies and analytics.

Big Data 108

Big Data Technology Tools Cloud 108

Exadel

FEBRUARY 20, 2023

In this article, we’ll look at AI in the cloud and three major providers who are blazing a trail in the world of AI cloud technologies. Major Players for AI in the Cloud For the scope of this article, AI is defined as machine learning, since ML is the biggest constituent of the technology. Previous article

Artificial Inteligence 52

Artificial Inteligence Cloud Machine Learning Azure 52

Cloudera

DECEMBER 15, 2022

You can leverage Kubernetes (K8s) and containerization technologies to consistently deploy your applications across multiple clouds including AWS, Azure, and Google Cloud, with portability to write once, run anywhere, and move from cloud to cloud with ease. Enhanced multi-function analytics.

Cloud 80

Cloud Data Analytics Artificial Inteligence 80

Altexsoft

JANUARY 22, 2020

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. Data visualization as a part of data representation and analytics. Azure Stream Analytics.

Analytics 20

Analytics Data IoT Analysis 20

Invid Group

AUGUST 28, 2024

AWS, Azure, and Google provide fully managed platforms, tools, training, and certifications to prototype and deploy AI solutions at scale. For instance, AWS Sagemaker, AWS Bedrock, Azure AI Search, Azure Open AI, and Google Vertex AI [3,4,5,6,7].

Technical Review 52

Technical Review Artificial Inteligence Performance Azure 52

Cloudera

FEBRUARY 22, 2021

It builds on a foundation of technologies from CDH (Cloudera Data Hub) and HDP (Hortonworks Data Platform) technologies and delivers a holistic, integrated data platform from Edge to AI helping clients to accelerate complex data pipelines and democratize data assets.

Data 82

Data Analytics Government Technical Review 82

Prisma Clud

JANUARY 15, 2025

With offerings spanning the many ways organizations can extract value from data from data pipelines to machine learning and even LLM training Databricks is often a critical component of modern data infrastructure. It operates on a cloud-native architecture , leveraging distributed computing to process large-scale data.

Artificial Inteligence 52

Artificial Inteligence Cloud Data Storage 52

Altexsoft

OCTOBER 2, 2020

If your business generates tons of data and you’re looking for ways to organize it for storage and further use, you’re at the right place. Read the article to learn what components data management consists of and how to implement a data management strategy in your business. Key disciplines and roles in data management.

Strategy 64

Strategy Database Administration Data Technical Review 64

Altexsoft

AUGUST 29, 2023

The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. This article explains what a data lake is, its architecture, and diverse use cases. Make sure to check out our dedicated article.

Architecture 52

Architecture Data Storage Artificial Inteligence 52

Altexsoft

DECEMBER 4, 2020

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. You can read more about it in our previous article Data Migration: Process, Types, and Golden Rules to Follow. Data sources and destinations.

Software Review 69

Software Review Software Data Technical Review 69

Altexsoft

DECEMBER 15, 2021

The rest is done by data engineers, data scientists , machine learning engineers , and other high-trained (and high-paid) specialists. To grasp how DevOps principles can be integrated into machine learning, read our article on MLOps methods and tools. How Microsoft Azure AutoMl works. MLOps cycle.

Artificial Inteligence 59

Artificial Inteligence Machine Learning How To Open Source 59

Mobilunity

MARCH 19, 2025

In this article, we’ll discuss the benefits and challenges of working with remote teams and teach you how to integrate off-site developers effectively into your environment. Developers gather and preprocess data to build and train algorithms with libraries like Keras, TensorFlow, and PyTorch. Data engineering.

Trends 40

Trends Technical Review Development Software Review 40

InnovationM

MAY 14, 2023

Introduction As someone who has hands-on experience in constructing and leveraging data lakes, I can attest to the transformative power these repositories hold for organizations grappling with vast amounts of data. These systems ensure high availability and facilitate the storage of massive data volumes.

Data 52

Data Storage Construction Business Intelligence 52

Mobilunity

DECEMBER 9, 2024

A more detailed description is covered in our article on AI engineers roles and responsibilities. Key skills for AI engineers The following is a teeny-tiny list of skills crucial for AI engineers. It includes subjects like data engineering, model optimization, and deployment in real-world conditions.

Engineering 52

Engineering Artificial Inteligence Machine Learning Artificial Intelligence 52

Confluent

OCTOBER 16, 2019

Using this data, Apache Kafka ® and Confluent Platform can provide the foundations for both event-driven applications as well as an analytical platform. With tools like KSQL and Kafka Connect, the concept of streaming ETL is made accessible to a much wider audience of developers and data engineers.

Data 19

Data Training Analytics Storage 19

Altexsoft

AUGUST 19, 2022

So, in this article, we’ll talk about the current BI market leader – Microsoft Power BI – and discuss its functionality, pros and cons, and alternatives. Microsoft Power BI is an interactive data visualization software suite developed by Microsoft that helps businesses aggregate, organize, and analyze data. What is Power BI?

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Altexsoft

JULY 19, 2022

She formulated the thesis in 2018 and published her first article “How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh” in 2019. Since that time, the data mesh concept has received a lot of attention and appreciation from companies pioneering this idea. And it’s their job to guarantee data quality.

Architecture 52

Architecture Data Analytics Data Engineering 52

Altexsoft

OCTOBER 21, 2022

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. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. This article is a part of our “The Good and the Bad” series.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Altexsoft

NOVEMBER 5, 2021

Here, HIM is short for health information management, the discipline too broad to be covered in one article. So, we’ll only touch on its most vital aspects, instruments, and areas of interest — namely, data quality, patient identity, database administration, and compliance with privacy regulations. This will eliminate human errors.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Altexsoft

APRIL 26, 2022

For everyone who is considering Snowflake as a part of their technology stack, this article is a great place to start the journey. We’ll dive deeper into Snowflake’s pros and cons, its unique architecture, and its features to help you decide whether this data warehouse is the right choice for your company. Source: Snowflake.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Tools to build an ELT pipeline.

Tools 52

Tools Software Review Systems Review Testing 52

John Snow Labs

MAY 24, 2023

Therefore, the data needs to be properly labeled/categorized for a particular use case. Companies can use high-quality human-powered data annotation services to enhance ML and AI implementations. In this article, we will discuss the top Text Annotation tools for Natural Language Processing along with their characteristic features.

Tools 52

Tools Artificial Inteligence Machine Learning Software Review 52

Existek

SEPTEMBER 28, 2023

In this article, we’ve focused on the AI developer job and some efficient approaches to engage with the best specialists on the market. Responsibilities of AI engineers Requirements to hire AI developers Where to find AI developers? AI-related skills are highly valued in the market and adopted in various industries.

Artificial Inteligence 52

Artificial Inteligence Development How To Technical Review 52