Existek

JANUARY 11, 2022

It eliminated the need to get back to the traditional environment when teams struggled with complex and costly in-house hardware and software. . At some point, cloud computing has changed how to streamline business processes and deal with data in general.

Azure 52

Azure AWS Cloud How To 52

Altexsoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Which Big Data tasks does Spark solve most effectively? How does it work?

Big Data 98

Big Data Tools Data Storage 98

Kentik

APRIL 11, 2016

Clustered computing for real-time Big Data analytics. It has since gone on to become a key technology for running many web-scale services and products, and has also landed in traditional enterprise and government IT organizations for solving big data problems in finance, demographics, intelligence, and more.

Big Data 40

Big Data Analytics Network Architecture 40

Altexsoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

CIO

JUNE 14, 2023

Big data exploded onto the scene in the mid-2000s and has continued to grow ever since. Today, the data is even bigger, and managing these massive volumes of data presents a new challenge for many organizations. Even if you live and breathe tech every day, it’s difficult to conceptualize how big “big” really is.

Data 162

Data Scalability Storage Big Data 162

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. Stream processing.

Analytics 20

Analytics Data IoT Analysis 20

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Supports Disaggregation of compute and storage.

Data 98

Data Storage Architecture Big Data 98

Altexsoft

MARCH 18, 2021

As data keeps growing in volumes and types, the use of ETL becomes quite ineffective, costly, and time-consuming. Basically, ELT inverts the last two stages of the ETL process, meaning that after being extracted from databases data is loaded straight into a central repository where all transformations occur. Data size and type.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

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. Is it still so? Scalability opportunities.

Backup 115

Backup Azure Software Review Systems Review 115

Abhishek Tiwari

DECEMBER 27, 2017

More importantly, UDM utilizes a single storage backend with benefits of multiple storage systems which avoids moving data across systems hence data duplication, and data consistency issues. In contrast, Alluxio a middleware for data access - think Alluxio storage layer as fast cache.

Trends 49

Trends Artificial Inteligence Data Big Data 49

Altexsoft

APRIL 26, 2022

Not long ago setting up a data warehouse — a central information repository enabling business intelligence and analytics — meant purchasing expensive, purpose-built hardware appliances and running a local data center. By the type of deployment, data warehouses can be categorized into. Each node has its own disk storage.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Cloudera

NOVEMBER 2, 2020

Having a live view of all aspects of their network lets them identify potentially faulty hardware in real time so they can avoid impact to customer call/data service. Ingest 100s of TB of network event data per day . Correlations across data domains, even if they are not traditionally stored together (e.g. DataViz.

Data 90

Data Analytics Storage Big Data 90

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. But for high availability and data loss prevention, it’s recommended that you have at least three brokers.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Altexsoft

OCTOBER 24, 2019

Similar to humans companies generate and collect tons of data about the past. And this data can be used to support decision making. While our brain is both the processor and the storage, companies need multiple tools to work with data. And one of the most important ones is a data warehouse. Subject-oriented data.

Architecture 50

Architecture Enterprise Data Technical Review 50

Altexsoft

DECEMBER 14, 2022

What’s more, this software may run either partly or completely on top of different hardware – from a developer’s computer to a production cloud provider. Thus, the guest operating system can be installed on this virtual hardware, and from there, applications can be installed and run in the same way as in the host operating system.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

ParkMyCloud

MAY 29, 2019

As more and more enterprises drive value from container platforms, infrastructure-as-code solutions, software-defined networking, storage, continuous integration/delivery, and AI, they need people and skills on board with ever more niche expertise and deep technological understanding.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Altexsoft

FEBRUARY 22, 2022

As we mentioned above, PdM is a complex project that requires significant investment to build a custom hardware and software infrastructure that will collect data from connected IoT devices, analyze it, and trigger relevant maintenance events. It’s an awful lot of data, so it has to be processed with special tools.

Software Review 52

Software Review Technical Review Software Technology 52

Altexsoft

OCTOBER 8, 2021

But more often than not data is scattered across a myriad of disparate platforms, databases, and file systems. What’s more, that data comes in different forms and its volumes keep growing rapidly every day — hence the name of Big Data. Data integration process. Also, solutions provide automated data mapping.

Tools 52

Tools Data Software Review Open Source 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

TIBCO - Connected Intelligence

AUGUST 10, 2020

Taking action to leverage your data is a multi-step journey, outlined below: First, you have to recognize that sticking to the status quo is not an option. Your data demands, like your data itself, are outpacing your data engineering methods and teams.

Virtualization 69

Virtualization Data How To Data Engineering 69

Altexsoft

NOVEMBER 5, 2021

To avoid errors that may threaten patient safety, AHIMA introduced the data quality management model which covers. Application, or the reason for data collection, Collection, or the process of data gathering, Warehousing, or systems and activities related to data storage and archiving, and. Supported data formats.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Altexsoft

NOVEMBER 9, 2021

Digitization has already greatly improved this business aspect, facilitating contract creation and editing, introducing e-signatures, increasing security, tracking expiration dates, and enabling convenient search and storage functionalities. Meanwhile, we’ll describe the process of turning raw data around you into actionable insights.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Coforge

AUGUST 20, 2019

In the digital communities that we live in, storage is virtually free and our garrulous species is generating and storing data like never before. Outsourcing: Some of the work related to data engineering and DevOps/SRE may be outsourced to concentrate resources towards achieving the business goals. #2

Machine Learning 8

Machine Learning Artificial Inteligence Enterprise Software Review 8

Cloudera

AUGUST 26, 2020

Informatica’s comprehensive suite of Data Engineering solutions is designed to run natively on Cloudera Data Platform — taking full advantage of the scalable computing platform. The presentation of data from Cloudera within proprietary database systems is also supported. Certified Kubernetes Shared Storage Partner.

Data 79

Data Machine Learning Artificial Inteligence Disaster Recovery 79

Altexsoft

DECEMBER 9, 2020

Diagnostic analytics identifies patterns and dependencies in available data, explaining why something happened. Predictive analytics creates probable forecasts of what will happen in the future, using machine learning techniques to operate big data volumes. Introducing data engineering and data science expertise.

Analytics 102

Analytics Technical Review Technology Applications 102

Altexsoft

MARCH 14, 2023

Modern data stack vs traditional data stack Traditional data stacks are typically on-premises solutions based on hardware and software infrastructure managed by the organization itself. This means that companies don’t necessarily need a large data engineering team. Data democratization.

Data 59

Data Technical Review Software Review Artificial Inteligence 59

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.” Cloud deployments aren’t top-down.

Trends 109

Trends Technical Review Technology Artificial Inteligence 109