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

TechCrunch

OCTOBER 7, 2021

If your customers are data engineers, it probably won’t make sense to discuss front-end web technologies. EveryDeveloper focuses on content, which I believe is the most scalable way to reach developers. Blog articles are certainly core, but you want to make sure you’re covering the right topics in the right way.

Weak Development Team 231

Weak Development Team Software Development Marketing Technical Advisors 231

Cloudera

FEBRUARY 16, 2021

Cloudera Operational Database (COD) plays the crucial role of a data store in the enterprise data lifecycle. You can use COD with: Cloudera DataFlow to ingest and aggregate data from various sources. Cloudera Data Engineering to ingest bulk data and data from mainframes. Cloudera Data Engineering.

Machine Learning 83

Machine Learning Artificial Inteligence Data Engineering Policies 83

Netflix Tech

MARCH 7, 2024

Instead, we provide a robust foundational layer with integrations to our company-wide data, compute, and orchestration platform, as well as various paths to deploy applications to production smoothly. In this article, we cover a few key integrations that we provide for various layers of the Metaflow stack at Netflix, as illustrated above.

System 90

System Machine Learning Artificial Inteligence Training 90

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

CIO

JULY 18, 2023

“If we’re looking to build, train, and run models at scale to run in parallel to each of our products, we need talent who can help us unbundle the data by refactoring apps and data, and building a scalable data fabric that is flexible to feed to a generative AI platform,” says Kocherlakota, who is seeking AI experience and generative AI knowledge.

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Technical Advisors Artificial Inteligence Generative AI How To 246

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

High Scalability

JUNE 15, 2020

This is a guest post by Eunice Do , Data Engineer at TripleLift , a technology company leading the next generation of programmatic advertising. The system is the data pipeline at TripleLift. TripleLift is an adtech company, and like most companies in this industry, we deal with high volumes of data on a daily basis.

Part-Time VPE 82

Part-Time VPE Data Advertising Data Engineering 82

Capgemini

JANUARY 17, 2023

By creating a lakehouse, a company gives every employee the ability to access and employ data and artificial intelligence to make better business decisions. Many organizations that implement a lakehouse as their key data strategy are seeing lightning-speed data insights with horizontally scalable data-engineering pipelines.

Strategy 52

Strategy Technical Review Data Artificial Inteligence 52

Altexsoft

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. Big data processing. maintaining data pipeline.

Big Data 75

Big Data Data Engineering Engineering Data 75

KitelyTech

FEBRUARY 3, 2021

How companies handle big data and data science is changing so they are beginning to rely on the services of specialized companies. In this article, we discussed the most popular big data and data science development services that your company can take advantage of. User Data Collection.

Big Data 52

Big Data Data Development Business Intelligence 52

Confluent

JUNE 18, 2019

Software projects of all sizes and complexities have a common challenge: building a scalable solution for search. For this reason and others as well, many projects start using their database for everything, and over time they might move to a search engine like Elasticsearch or Solr. You might be wondering, is this a good solution?

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Scalability Architecture Machine Learning Artificial Inteligence 96

CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. As data and analytics are embedded into the fabric of business and society –from popular apps to the Internet of Things (IoT) –Spark brings essential advances to large-scale data processing. Related articles.

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Open Source Big Data Machine Learning Artificial Inteligence 117

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 Machine Learning 52

Kentik

APRIL 3, 2018

This allows non-technical stakeholders from product, marketing, sales, management, and executives to understand the data and gain insight in terms that are relevant to their roles. To learn more about Custom Dimensions, check out our Knowledge Base article. For more information, check out our Dashboards Knowledge Base article.

Network 40

Network WAN LAN Policies 40

The Citus Data

MARCH 31, 2023

on-demand talk, Citus open source user) 6 Citus engineering talks Citus & Patroni: The Key to Scalable and Fault-Tolerant PostgreSQL , by Alexander Kukushkin who is a principal engineer at Microsoft and lead engineer for Patroni. This article was originally published on citusdata.com.

Azure 84

Azure Open Source Virtualization Software Engineering 84

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Native frameworks.

Big Data 63

Big Data Data Storage Microservices 63

Altexsoft

APRIL 13, 2023

To store all this diverse information, you’ll have to utilize a centralized data repository such as a data warehouse or data lake. To get a better picture, check out a short explainer of what data engineering is about Data analytics Now that we have all this data, we can finally work on the actual witchcraft.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Existek

JANUARY 11, 2022

And companies that have completed it emphasize gained advantages like accessibility, scalability, cost-effectiveness, etc. . Read the article. In 2010, they launched Windows Azure, the PaaS, positioning it as an alternative to Google App Engine and Amazon EC2. Read the article.

Azure 52

Azure AWS Cloud How To 52

Kentik

SEPTEMBER 11, 2015

In this primer we’ll show how to use FDWs to front-end your own datastores, and to allow JOINs with native PG data and data stored in other FDW-accessible systems. We use FDWs this way at Kentik as part of the Kentik Data Engine (KDE) that powers Kentik Detect, the massively scalable big data-based SaaS for network visibility.

Data 40

Data Authentication Data Engineering Scalability 40

Xebia

JULY 28, 2023

In this article, we’ll walk through the steps for setting it up for Databricks, using Multiple Databricks Workspaces with one single dbt Cloud project. You can follow the steps on how to set up your deployment pipeline in this article ( CI/CD in dbt Cloud with GitHub Actions: Automating multiple environments deployment ).

Cloud 130

Cloud Azure How To Windows 130

Cloudera

DECEMBER 10, 2020

Drawing on more than a decade of experience in building and deploying massive scale data platforms on economical budgets, Cloudera has designed and delivered a cost-cutting cloud-native solution – Cloudera Data Warehouse (CDW), part of the new Cloudera Data Platform (CDP). Watch this video to get an overview of CDW. .

Data 98

Data Technical Review Storage Systems Review 98

Cloudera

DECEMBER 15, 2022

Performance and scalability. Cloudera developed unique features in CDP for Iceberg query performance and scalability for large data sets including I/O caching, dynamic partition pruning, vectorization, Z-ordering, parquet page indexes, and manifest caching. Enhanced multi-function analytics.

Cloud 80

Cloud Data Analytics Machine Learning 80

Apiumhub

SEPTEMBER 20, 2023

In this article, we´ll be your guide to the must-attend tech conferences set to unfold in October. This tech conference is a great opportunity for all professionals and organizations working with the utilization of Data Science, Machine, and Deep Learning to innovate and improve their businesses.

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Conference Artificial Inteligence UI/UX Machine Learning 96

Abhishek Tiwari

JULY 7, 2023

They provide a systematic approach to extract, transform, and load (ETL) data from various sources, enabling organizations to derive valuable insights. However, as with any technology trend, data pipelines have not been immune to misuse and overuse.

Data 52

Data Transportation Scalability Systems Review 52

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. Scalability. Please note!

Tools 52

Tools Software Review Systems Review Testing 52

Perficient

FEBRUARY 28, 2023

This is the final blog in a series that explains how organizations can prevent their Data Lake from becoming a Data Swamp, with insights and strategy from Perficient’s Senior Data Strategist and Solutions Architect, Dr. Chuck Brooks. Once data is in the Data Lake, the data can be made available to anyone.

Data 110

Data Analytics Google Cloud Cloud 110

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

AUGUST 30, 2022

But while state and local governments seek to improve policies, decision making, and the services constituents rely upon, data silos create accessibility and sharing challenges that hinder public sector agencies from transforming their data into a strategic asset and leveraging it for the common good. .

Architecture 79

Architecture Data Artificial Inteligence Artificial Intelligence 79

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 Systems Review 115

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. How data engineering works in a nutshell.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Cloudera

AUGUST 20, 2021

The Cloudera Data Platform comprises a number of ‘data experiences’ each delivering a distinct analytical capability using one or more purposely-built Apache open source projects such as Apache Spark for Data Engineering and Apache HBase for Operational Database workloads.

Strategy 98

Strategy Data Technical Review Weak Development Team 98

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.

Analytics 20

Analytics Data IoT Analysis 20

Kentik

MAY 31, 2023

In this article, I want to underscore why NetOps has an integral role (and more responsibility) in delivering on the promise of reliability and highlight a few examples of how engineering for reliability can make networks less reliable. I wrote an article a while ago addressing latency.

Network 52

Network Cloud Load Balancer Firewall 52

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ).

Data 88

Data Analytics Machine Learning Artificial Inteligence 88

Altexsoft

MARCH 16, 2021

But what happens to all the massive amounts of data from all these wearables and other medical and non-medical devices? In this article, we will explain the concept and usage of Big Data in the healthcare industry and talk about its sources, applications, and implementation challenges. Big Data infrastructure in healthcare.

Big Data 116

Big Data Healthcare Applications Data 116

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52