Xebia

MAY 16, 2023

Data Engineers were tempted by the pressure of the moment to give up on testing all together. There was no need for generating your own data; just take a percentage of production data. In many cases, these tasks ended up on the shoulders of the Data Engineers themselves. Overly restrictive governance.

Testing 130

Testing How To Data Engineering Engineering 130

CIO

JUNE 14, 2023

CDP Generalist The Cloudera Data Platform (CDP) Generalist certification verifies proficiency with the Cloudera CDP platform. The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect.

Big Data 314

Big Data Analytics Data eLearning 314

CIO

JANUARY 19, 2024

The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect. The exam consists of 60 questions and the candidate has 90 minutes to complete it.

Artificial Inteligence 316

Artificial Inteligence Data Machine Learning Azure 316

Altexsoft

JANUARY 14, 2021

Snowflake, Redshift, BigQuery, and Others: Cloud Data Warehouse Tools Compared. 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. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

MARCH 18, 2021

ETL and ELT are the most widely applied approaches to deliver data from one or many sources to a centralized system for easy access and analysis. With ETL, data is transformed in a temporary staging area before it gets to a target repository (e.g ETL made its way to meet that need and became the standard data integration method.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Cloudera

DECEMBER 10, 2020

Some data warehousing solutions such as appliances and engineered systems have attempted to overcome these problems, but with limited success. . Recently, cloud-native data warehouses changed the data warehousing and business intelligence landscape. These costs impede the adoption of cloud-native data warehouses.

Data 98

Data Technical Review Storage Systems Review 98

Hu's Place - HitachiVantara

APRIL 11, 2019

According to the Harvard Business Review , " Cross-industry studies show that on average, less than half of an organization’s structured data is actively used in making decisions—and less than 1% of its unstructured data is analyzed or used at all.

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

AWS Machine Learning - AI

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

Artificial Inteligence 115

Artificial Inteligence Generative AI Security Applications 115

Hu's Place - HitachiVantara

MAY 24, 2019

The latest International Data Corporation ( IDC ) Worldwide Quarterly Enterprise Storage Systems Tracker , was published on March 4, 2019. It showed vendor revenue in the worldwide enterprise storage systems market is still increasing: 7.4% billion due to significant existing capacity. year over year to $14.5

Marketing 75

Marketing Storage Systems Review Enterprise 75

Mobilunity

NOVEMBER 24, 2021

In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. In this article, we’ll discuss the role of an ETL engineer in data processing and why businesses need such experts nowadays. Who Is an ETL Engineer?

Development 52

Development Storage Recruiting Architecture 52

d2iq

FEBRUARY 19, 2021

As little as 5% of the code of production machine learning systems is the model itself. 2015): Hidden Technical Debt in Machine Learning Systems. The model itself (purple) accounts for as little as 5% of the code of a machine learning system. The data engineer’s main focus is on ETL: extracting, transforming, and loading data.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

Hu's Place - HitachiVantara

MAY 10, 2019

Rule-based fraud detection software is being replaced or augmented by machine-learning algorithms that do a better job of recognizing fraud patterns that can be correlated across several data sources. DataOps is required to engineer and prepare the data so that the machine learning algorithms can be efficient and effective.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90

O'Reilly Media - Ideas

APRIL 9, 2019

Or, why science and engineering are still different disciplines. "A He would have to ask an engineer to do it for him.". A few months ago, I wrote about the differences between data engineers and data scientists. That was interesting because the data engineers didn’t push back saying they’re data scientists.

Data Engineering 111

Data Engineering Engineering Data Technical Review 111

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. This is no small feat and can lead to significant overhead and resource consumption.

Network 52

Network Cloud Load Balancer Firewall 52

Altexsoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. 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. Who needs a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

CIO

JULY 15, 2022

Over the years, DTN has bought up several niche data service providers, each with its own IT systems — an environment that challenged DTN IT’s ability to innovate. “We Very little innovation was happening because most of the energy was going towards having those five systems run in parallel.”. The merger playbook.

Systems Review 273

Systems Review Fractional CTO System Development Team Review 273

Apps Associates

JULY 28, 2022

This blog introduces you to Oracle Cloud Infrastructure (OCI) Data Integration service and reviews how to setup Data Integration workspace in OCI. I love Data Integration in OCI and hope to get you excited about this great product as well. Use Case 1: Data integration for big data, data lakes, and data science.

Infrastructure 52

Infrastructure Cloud Data Linux 52

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

Altexsoft

DECEMBER 4, 2020

Here, we’ll focus on tools that can save you the lion’s share of tedious tasks — namely, key types of data migration software, selection criteria, and some popular options available in the market. Types of data migration tools. There are three major types of data migration software to choose from. Data sources and destinations.

Software Review 69

Software Review Software Data Technical Review 69

Altexsoft

DECEMBER 9, 2020

In many cases, there is even no desire to put effort and resources into developing analytical capabilities, mostly due to the lack of knowledge. Sometimes, a data or business analyst is employed to interpret available data, or a part-time data engineer is involved to manage the data architecture and customize the purchased software.

Analytics 102

Analytics Technical Review Technology Applications 102

Altexsoft

APRIL 26, 2022

Semi-structured data is somewhere in the middle, meaning it is partially structured but doesn’t fit the tabular models of relational databases. The data journey from different source systems to a warehouse commonly happens in two ways — ETL and ELT. BTW, we have an engaging video explaining how data engineering works.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

O'Reilly Media - Ideas

JANUARY 25, 2024

And the real question that will change our industry is “How do we design systems in which generative AI and humans collaborate effectively?” Domain-driven design is particularly useful for understanding the behavior of complex enterprise systems; it’s down, but only 2.0%. So the software development world is changing. We also saw 9.8%

Trends 116

Trends Technical Review Technology Artificial Inteligence 116

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data 82

Data Analytics Cloud Technical Review 82

Hu's Place - HitachiVantara

MARCH 18, 2019

Smart cities also offer great opportunities for transformation and optimization of the urban economy with production systems based on information and technology. The requirement was to centralize and archive the data collected from these endpoint devices while keeping with regulation requirements.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

Altexsoft

SEPTEMBER 9, 2022

These are important for SEO purposes because search engines use them to “understand” what the page is about and how it has to be displayed and ranked in search results. Metadata management is a set of activities, technologies, and policies that target metadata collection, storage, and organizing. Metadata storage.

Tools 59

Tools Technical Review Software Review Systems Review 59

Existek

JANUARY 11, 2022

In 2010, they launched Windows Azure, the PaaS, positioning it as an alternative to Google App Engine and Amazon EC2. They provided a few services like computing, Azure Bob storage, SQL Azure, and Azure Service Bus. The new structure enabled the opportunity to meet such customer needs in computing as storage, networking, and services.

Azure 52

Azure AWS Cloud How To 52

Altexsoft

OCTOBER 2, 2020

Data is a valuable source that needs management. 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.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

FEBRUARY 22, 2022

And breakdowns are just too expensive, especially at a fleet-wide scale (not to mention risking drivers’ lives, losses due to unfulfilled contracts and related downtime, and customer dissatisfaction). You can adopt a comprehensive fleet management system that has vehicle maintenance as one of its modules. So, what’s the alternative?

Software Review 52

Software Review Technical Review Software Technology 52

Altexsoft

APRIL 13, 2023

Leading executives focus on building resilient and intelligent supply chains that can withstand the turmoil due to data-based proactive decisions. The ultimate goal of an SCCT is to support efficient, data-based decision-making, planning, and risk management, as well as quick and effective reactions to disruption.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Kentik

FEBRUARY 7, 2023

They do, however, represent an architectural response to the central problem of data gravity. All systems go The lift and shift, re-deploying an existing code base “as is” into the cloud, is many organizations’ first step into cloud networking. San Diego was where all of our customer data was stored.

Network 59

Network Cloud Data Data Center 59

Altexsoft

MARCH 16, 2021

It’s referred to as big data, since, for example, just a single complete human genome sequence produces about 200 Gb of raw data. Now, we know where big data in healthcare originates. Let’s take a quick look at the big data infrastructure. Big Data infrastructure in healthcare.

Big Data 116

Big Data Healthcare Applications Data 116

Abhishek Tiwari

DECEMBER 27, 2017

A unified data management (UDM) system combines the best of data warehouses, data lakes, and streaming without expensive and error-prone ETL. It offers reliability and performance of a data warehouse, real-time and low-latency characteristics of a streaming system, and scale and cost-efficiency of a data lake.

Trends 49

Trends Artificial Inteligence Data Big Data 49

Altexsoft

NOVEMBER 5, 2021

Main coding systems in healthcare. Among the most widespread coding systems are. Recorded with codes or as plain text, 85 percent of health information is now kept in digital form across various health information systems. Health information systems. radiology information systems (RISs). Main Healthcare APIs.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Altexsoft

OCTOBER 29, 2020

When data is subjective and accurate, it gives us a better understanding than we can fathom with our human brains. Because as any system, data processing is subject to mistakes. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

Cloudera

DECEMBER 20, 2022

This is due to an improvement in plant uptime, supported by predictive maintenance applications, coupled with optimization of the fuel consumption that powers these plants, as well as fine-grained performance monitoring that eliminates over-production. . These actors are at both ends of the chain, as they produce and consume at the same time.

Energy 81

Energy Analytics Data Machine Learning 81

Hu's Place - HitachiVantara

JANUARY 3, 2019

” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared. More focus will be on the operational aspects of data rather than the fundamentals of capturing, storing and protecting data. Building an AI or machine learning model is not a one-time effort.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Openxcell

MAY 8, 2023

If you’re still in doubt about how to prevent data leakage, hire a big data engineer. Types of Data Leakage In the World of Data Security, there are many types of data leakage; it is crucial to understand that it can stem from internal or external sources.

Data 52

Data Software Review Technical Review ChatGPT 52