Altexsoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data 87

Data Data Engineering Big Data Architecture 87

CIO

FEBRUARY 14, 2023

Streaming data technologies unlock the ability to capture insights and take instant action on data that’s flowing into your organization; they’re a building block for developing applications that can respond in real-time to user actions, security threats, or other events. report they have established a data culture 26.5%

Artificial Inteligence 278

Artificial Inteligence Strategy Data Machine Learning 278

Capgemini

MARCH 16, 2022

makes it possible to consider obstacles as key elements to unlock scalability and initiate the Factory of the Future. technologies (AI & analytics, cloud and edge computing, cybersecurity, 5G, IoT, and data engineering) are converging at speed. Bring the potential of DATA to the factory floor. Industry 4.0

Industry 98

Industry IoT Technical Review Automotive 98

Mobilunity

MAY 8, 2023

Governance zone is used for managing data access, ensuring data quality, and enforcing data security policies. It includes tools for data lineage, metadata management, and access control. Data Transformation. Data Security. With enterprise data lake services, you can keep your data secure.

Engineering 52

Engineering Data Storage AWS 52

Cloudera

JUNE 7, 2022

Big data is cool again. As the company who taught the world the value of big data, we always knew it would be. But this is not your grandfather’s big data. It has evolved into something new – hybrid data. For Cloudera this is a back to the future moment.

Data 109

Data Architecture Analytics Government 109

Mobilunity

MAY 3, 2024

When it comes to financial technology, data engineers are the most important architects. As fintech continues to change the way standard financial services are done, the data engineer’s job becomes more and more important in shaping the future of the industry. Knowledge of Scala or R can also be advantageous.

Data Engineering 52

Data Engineering Fintech Engineering Data 52

Apiumhub

NOVEMBER 17, 2022

Francesco Cesarini – Founder, & Technical Director at Erland Solutions, Co-author of “Erlang Programming“ and “Designing for Scalability with Erlang/OTP“. Jeff Williams – CTO & co-founder of Contrast Security. Jesse Anderson – Data Engineer, Creative Engineer, and Managing Director of Big Data Institute.

Technical Review 80

Technical Review Software Review Fractional CTO CTO Coach 80

The Citus Data

MARCH 31, 2023

(on-demand talk, Citus open source user, Django, Python, django-multitenant, pgBackRest) Practical approach to building real-time analytics for cybersecurity applications , by Slava Moudry. (on-demand on-demand talk, security, roles, privileges, PostgreSQL) How to copy a Postgres database? ,

Azure 85

Azure Open Source Virtualization Software Engineering 85

O'Reilly Media - Ideas

JUNE 4, 2019

Programming with Data: Advanced Python and Pandas , July 9. Understanding Data Science Algorithms in R: Regression , July 12. Cleaning Data at Scale , July 15. Scalable Data Science with Apache Hadoop and Spark , July 16. Effective Data Center Design Techniques: Data Center Topologies and Control Planes , July 19.

Course 67

Course Training Artificial Inteligence Software Review 67

Altexsoft

MARCH 16, 2021

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. What is Big Data and its sources in healthcare? So, what is Big Data, and what actually makes it Big? Let’s see where it can come from.

Big Data 116

Big Data Healthcare Applications Data 116

O'Reilly Media - Ideas

JUNE 5, 2019

Programming with Data: Advanced Python and Pandas , July 9. Understanding Data Science Algorithms in R: Regression , July 12. Cleaning Data at Scale , July 15. Scalable Data Science with Apache Hadoop and Spark , July 16. Effective Data Center Design Techniques: Data Center Topologies and Control Planes , July 19.

Course 50

Course Training Artificial Inteligence Software Review 50

d2iq

FEBRUARY 19, 2021

Components that are unique to data engineering and machine learning (red) surround the model, with more common elements (gray) in support of the entire infrastructure on the periphery. Before you can build a model, you need to ingest and verify data, after which you can extract features that power the model.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

Kentik

JANUARY 3, 2018

New data streams, protocols, security guidelines, and backup procedures challenge network and security operations staff. Also, IoT devices with inadequate security safeguards are easy targets to hijack with malware that weaponizes them for DDoS attacks. Kentik’s Scalable and Flexible IoT Analytics.

IoT 40

IoT Network Tools Big Data 40

Mobilunity

DECEMBER 21, 2022

Tech companies use data science to enhance user experience, create personalized recommendation systems, develop innovative solutions, and more. Data science in agriculture can help businesses develop data pipelines specifically for automation and fast scalability. Cybersecurity. Agriculture.

Data 52

Data How To Machine Learning Artificial Inteligence 52

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. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

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

Altexsoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics.

Big Data 59

Big Data Data Google Cloud Storage 59

Existek

JANUARY 11, 2022

The cloud computing market covers many areas like business processes, infrastructure, platform, security, management, analytics supported by cloud providers. And companies that have completed it emphasize gained advantages like accessibility, scalability, cost-effectiveness, etc. . Data and analytics. Security and governance.

Azure 52

Azure AWS Cloud How To 52

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

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. The truth is, there’s more to this term than just the size of information generated. This post will draw a full picture of what Big Data analytics is and how it works.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

APRIL 13, 2023

You can read the details on them in the linked articles, but in short, data warehouses are mostly used to store structured data and enable business intelligence , while data lakes support all types of data and fuel big data analytics and machine learning. Data security. Scalability.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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. But which one of the celebrities should you entrust your information assets to?

Big Data 98

Big Data Tools Data Storage 98

ParkMyCloud

JANUARY 17, 2020

Individuals in an associate solutions architect role have 1+ years of experience designing available, fault-tolerant, scalable, and most importantly cost-efficient, distributed systems on AWS. Must prove knowledge of deploying, operating and managing highly available, scalable and fault-tolerant systems on AWS.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Kentik

SEPTEMBER 11, 2015

FDW backends can be a surprisingly powerful tool when your data model isn’t classically relational but you still want all the nice things that come with PostgreSQL (aggregates, client libraries, authentication, group by, etc.). The above primer is just a small taste of how Foreign Data Wrappers can be applied to extend a PostgreSQL datastore.

Data 40

Data Authentication Data Engineering Scalability 40

Datavail

JUNE 8, 2023

Data Summit 2023 was filled with thought-provoking sessions and presentations that explored the ever-evolving world of data. From the technical possibilities and challenges of new and emerging technologies to using Big Data for business intelligence, analytics, and other business strategies, this event had something for everyone.

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

Cloudera

FEBRUARY 22, 2022

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists.

Data 106

Data Analytics Disaster Recovery Travel 106

Altexsoft

SEPTEMBER 9, 2022

In data science , metadata is one of the central aspects: It describes data (including unstructured data streams) fed into a big data analytical platform, capturing, for example, formats, file sizes, source of information, permission details, etc. Data governance. Data analytics.

Tools 59

Tools Technical Review Software Review Systems Review 59

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. A Robust Security Framework.

Strategy 95

Strategy Data Technical Review Weak Development Team 95

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

Kentik

JUNE 13, 2016

The typical pat answers — “use better security” or “patch your vulnerabilities” or “practice least privilege” — may be sound pieces of advice, but they are clearly not getting us where we need to be. Because they focus on the preventative aspects of security which, though valuable, are inherently imperfect.

Network 40

Network LAN Big Data Scalability 40

Altexsoft

JANUARY 14, 2021

The variety of data explodes and on-premises options fail to handle it. Apart from the lack of scalability and flexibility offered by modern databases, the traditional ones are costly to implement and maintain. At the moment, cloud-based data warehouse architectures provide the most effective employment of data warehousing resources.

Backup 115

Backup Azure Software Review Systems Review 115

Abhishek Tiwari

JULY 7, 2023

In the era of big data and complex data processing, data pipelines have emerged as a popular solution for managing and manipulating data. They provide a systematic approach to extract, transform, and load (ETL) data from various sources, enabling organizations to derive valuable insights.

Data 52

Data Transportation Scalability Systems Review 52

Kentik

OCTOBER 25, 2016

How Scalable Architecture Boosts Accuracy in Detection. Since there are so few of these, and because it is so difficult to manually change them, most network security teams end up configuring large pools of IP addresses into these objects. Big data to the rescue. Monitor against multiple data dimensions.

Scalability 40

Scalability Architecture Big Data Analytics 40

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. ELT comes to the rescue.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

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. ELT process steps.

Tools 52

Tools Software Review Systems Review Testing 52

Cloudera

DECEMBER 14, 2020

One trend that we’ve seen this year, is that enterprises are leveraging streaming data as a way to traverse through unplanned disruptions, as a way to make the best business decisions for their stakeholders. . Today, a new modern data platform is here to transform how businesses take advantage of real-time analytics.

Analytics 69

Analytics Big Data Government Cloud 69

Cloudera

NOVEMBER 19, 2020

Too often, though, legacy systems cannot deliver the needed speed and scalability to make these analytic defenses usable across disparate sources and systems. For many agencies, 80 percent of the work in support of anomaly detection and fraud prevention goes into routine tasks around data management.

Government 117

Government Artificial Inteligence Machine Learning Data 117