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.

Architecture 52

Architecture Data Storage Machine Learning 52

Xebia

JUNE 9, 2023

This worked out great until I tried to follow a tutorial written by a colleague which used the Azure Python SDK to create a dataset and upload it to an Azure storage account. I assumed it was already done since it was referenced in the pyproject.toml file but naively went ahead and tried to install the library.

Azure 130

Azure Architecture Software Storage 130

Erik Bernhardsson

DECEMBER 15, 2020

Decades ago, software engineering was hard because you had to build everything from scratch and solve all these foundational problems. You need storage to build something to serve 1M concurrent users? For instance: internet first created DVD-by-mail, but the real internet-native innovation was streaming video.).

Software Engineering 304

Software Engineering Engineering Tools Software 304

Altexsoft

MARCH 31, 2020

It means you must collect transactional data and move it from the database that supports transactions to another system that can handle large volumes of data. And, as is common, to transform it before loading to another storage system. But how do you move data? The simplest illustration for a data pipeline.

Data 76

Data Storage Analytics Data Center 76

Apps Associates

JULY 28, 2022

Use Case 1: Data integration for big data, data lakes, and data science. Efficiently load and transform data at scale into Data Lakes for data science and analytics. Load the data into object storage and create high-quality models more quickly using OCI data science. OCPU hours.

Infrastructure 52

Infrastructure Cloud Data Linux 52

Erik Bernhardsson

DECEMBER 6, 2022

We build it super fast — the above example in a couple of seconds, since we built our own container builder and have fast machines in the cloud with super fast internet. I'm deliberately vague about what exact role I mean here: take it to mean data engineers, data scientists, ML engineers, analytics engineers, and maybe more roles.

CTO Coach 242

CTO Coach Fractional CTO Software Engineering Serverless 242

O'Reilly Media - Ideas

JANUARY 8, 2019

The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. LinkedIn recently found that demand for data scientists in the US is “off the charts,” and our survey indicated that the demand for data scientists and data engineers is strong not just in the US but globally.

Trends 89

Trends Data Machine Learning Artificial Inteligence 89

Altexsoft

JULY 29, 2022

The biggest star of the Big Data world, Hadoop was named after a yellow stuffed elephant that belonged to the 2-year son of computer scientist Doug Cutting. The toy became the official logo of the technology, used by the major Internet players — such as Twitter, LinkedIn, eBay, and Amazon. The Hadoop toy. What is Hadoop?

Big Data 59

Big Data Data Google Cloud Storage 59

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

JUNE 26, 2023

All successful companies do it: constantly collect data. They track people’s behavior on the Internet, initiate surveys, monitor feedback, listen to signals from smart devices, derive meaningful words from emails, and take other steps to amass facts and figures that will help them make business decisions. Find sources of relevant data.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Kentik

MAY 10, 2023

A unified data repository (UDR) is a centralized storage system that consolidates, organizes, and manages data from different sources. It serves as a single point of access for various types of data, which could be a significant volume of very diverse data formats in an extensive network. Why do we need a UDR?

Analytics 59

Analytics Network Data Machine Learning 59

Cloudera

FEBRUARY 16, 2022

While it is a little dated, one amusing example that has been the source of countless internet memes is the famous, “is this a chihuahua or a muffin?” Each project consists of a declarative series of steps or operations that define the data science workflow. classification problem. Figure 01: Is this a chihuahua or a muffin?

Machine Learning 83

Machine Learning Artificial Inteligence Weak Development Team Construction 83

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

Kentik

MAY 31, 2023

In this case, region-wide disruptions of the internet or your cloud provider affect only a portion of traffic and provide safe destinations to re-route this affected traffic. As this data moves to and from highly durable storage services, NetOps must guarantee that the data remains secure and accurate.

Network 52

Network Cloud Load Balancer Firewall 52

Cloudera

OCTOBER 25, 2022

“They combine the best of both worlds: flexibility, cost effectiveness of data lakes and performance, and reliability of data warehouses.”. It allows users to rapidly ingest data and run self-service analytics and machine learning. Make sure you have encryption for data in motion as well as at rest. Data loss prevention.

Cloud 52

Cloud Data Firewall AWS 52

Altexsoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. And most of this data has to be handled in real-time or near real-time.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

JULY 19, 2022

As the picture above clearly shows, organizations have data producers and operational data on the left side and data consumers and analytical data on the right side. Data producers lack ownership over the information they generate which means they are not in charge of its quality. It works like this.

Architecture 52

Architecture Data Analytics Data Engineering 52

Cloudera

JANUARY 20, 2021

Consider that Manufacturing’s Industry Internet of Things (IIOT) was valued at $161b with an impressive 25% growth rate, the Connected Car market will be valued at $225b by 2027 with a 17% growth rate, or that in the first three months of 2020, retailers realized ten years of digital sales penetration in just three months.

Data 107

Data Artificial Inteligence Analytics Machine Learning 107

Altexsoft

DECEMBER 9, 2020

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. At this stage, data is siloed, not accessible for most employees, and decisions are mostly not data-driven.

Analytics 102

Analytics Technical Review Technology Applications 102

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. Data and analytics. Internet of Things. Cloud migration and modernization. Hybrid cloud and infrastructure.

Azure 52

Azure AWS Cloud How To 52

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Hybrid clouds must bond together the two clouds through fundamental technology, which will enable the transfer of data and applications. REAN Cloud is a global cloud systems integrator, managed services provider and solutions developer of cloud-native applications across big data, machine learning and emerging internet of things (IoT) spaces.

Cloud 78

Cloud Google Cloud Azure AWS 78

Altexsoft

MARCH 16, 2021

Medical equipment and other Internet of Medical Things (IoMT) devices such as bedside monitors and under-the-mattress sensors stream billions of various measurements per day, providing a real-time picture of a patient’s condition and warnings of the slightest changes. Big data infrastructure in a nutshell. Staffing problems.

Big Data 116

Big Data Healthcare Applications Data 116

TIBCO - Connected Intelligence

MARCH 5, 2020

Time-to-solution expectations for new data-driven solutions are even faster – With better data-driven solutions often the competitive battlefield, victory goes to the swift. Data Is The Wisest Bet for 2020.

Technology 42

Technology Games Trends IoT 42

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. IoT Engineer.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Altexsoft

OCTOBER 21, 2022

We describe information search on the Internet with just one word — ‘google’. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. A topic, in turn, is divided into partitions — the smallest units of storage space, hosting an ordered sequence of messages.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Kentik

MAY 23, 2017

Internet Service Providers (ISPs) come in varying sizes, from rural broadband and small cable MSOs to Tier 2 players and Tier 1 global giants. With the advent of open source big data engines, the power of big data network analytics has seemed tantalizingly close. Why Every ISP Needs a Robust Network Monitoring Solution.

Network 40

Network Open Source Big Data Load Balancer 40

Kentik

MAY 23, 2016

It’s common knowledge that “the Internet” is actually a set of networks belonging to a diverse range of independent organizations such as content providers, ISPs, corporations, and universities. These networks create the Internet by interconnecting. Only a big data solution can handle the required data at the required scale.

Big Data 40

Big Data Analytics Internet Network 40

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

Altexsoft

AUGUST 19, 2022

Power BI Desktop is a free, downloadable app that’s included in all Office 365 Plans, so all you need to do is sign up, connect to data sources, and start creating your interactive, customizable reports using a drag-and-drop canvas and hundreds of data visuals. You get 10GB of cloud storage and can upload 1GB of data at a time.

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Kentik

JUNE 4, 2019

By the end of this post you should have a pretty good idea of how True Origin helps network operations and engineering, particularly for Internet Service Providers. That’s why True Origin is a major step forward for every ISP carrying a significant volume of Internet-sourced content. What is True Origin?

Video 56

Video Network Internet Groups 56

Kentik

JUNE 13, 2016

Whether a local LAN, a private WAN, or the Internet, a network functions as the circulatory system for a body of knowledge. To get the data we need, we must tap into that flow. The data is not merely correlated but fully unified to create useful metadata for enhanced context.

Network 40

Network LAN Big Data Scalability 40

O'Reilly Media - Ideas

JANUARY 25, 2024

While we like to talk about how fast technology moves, internet time, and all that, in reality the last major new idea in software architecture was microservices, which dates to roughly 2015. Data analysis and databases Data engineering was by far the most heavily used topic in this category; it showed a 3.6%

Trends 119

Trends Technical Review Technology Artificial Inteligence 119

Kentik

OCTOBER 25, 2016

Though spectacular exploits against Internet infrastructure providers like Dyn are just a fraction of overall attacks, complacency is not a viable option. These issues are rooted in the inherent compute and storage limitations of scale-up detection architectures.

Scalability 40

Scalability Architecture Big Data Network 40

Strategy Driven

AUGUST 27, 2015

The Internet and cloud computing have revolutionized the nature of data capture and storage, tempting many companies to adopt a new 'Big Data' philosophy: collect all the data you can; all the time.

Big Data 34

Big Data Data Storage Journal 34

O'Reilly Media - Ideas

MARCH 31, 2020

In the best case scenario, the trained neural network accurately represents the underlying phenomenon of interest and produces the correct output even when presented with new input data the model didn’t see during training. It turns out that type of data infrastructure is also the foundation needed for building AI products.

Product Management 139

Product Management Artificial Inteligence Machine Learning Software Review 139

Cloudera

DECEMBER 12, 2018

Greg Rahn: Toward the end of that eight-year stint, I saw this thing coming up called Hadoop and an engine called Hive. It kind of was interesting to me that there were these big internet companies in the valley running this platform or a variation thereof of, based on Google research papers. There’s MongoDB for document stores.

Data 42

Data Marketing Storage Big Data 42

Kentik

NOVEMBER 16, 2015

Here at Kentik, our Kentik Detect service is powered by a multi-tenant big data datastore called Kentik Data Engine. KDE handles — on a daily basis — tens of billions of network flow records, ingestion of several TB of data, and many millions of sub-queries. Workers are processes that run on our storage nodes.

Metrics 40

Metrics Microservices Linux Architecture 40