Cloudera

SEPTEMBER 6, 2022

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Why telco should consider modern data architecture. The challenges.

Telecommunications 83

Telecommunications Architecture Data Government 83

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 Open Source 59

Infinidat

MARCH 10, 2021

Re-Thinking the Storage Infrastructure for Business Intelligence. With digital transformation under way at most enterprises, IT management is pondering how to optimize storage infrastructure to best support the new big data analytics focus. Adriana Andronescu. Wed, 03/10/2021 - 12:42.

Business Intelligence 98

Business Intelligence Storage Infrastructure Artificial Inteligence 98

Datavail

AUGUST 4, 2022

‘Big Data’ is getting bigger. The second challenge requires sophisticated analysis programming that gleans the meaning of each data bit and attaches that to the meanings gleaned from other relevant data bits. Data emerges every second of every day. Capturing Big Data – Managing the Volume.

Big Data 40

Big Data Data Architecture Storage 40

CIO

MAY 10, 2024

Service-oriented architecture (SOA) Service-oriented architecture (SOA) is an architectural framework used for software development that focuses on applications and systems as independent services. Because of this, NoSQL databases allow for rapid scalability and are well-suited for large and unstructured data sets.

SOA 325

SOA Linux Video Architecture 325

Linux Academy

FEBRUARY 6, 2019

With the huge amount of data floating around your business, what you do with it is vital to your continued success. Big data has become crucial in helping businesses make decisions and stay ahead of the competition. Check out our new Big Data Course, Hadoop Quick Start to help your team’s data transformation.

Big Data 60

Big Data Training Data Linux 60

Cloudera

JULY 9, 2019

Today, much of that speed and efficiency relies on insights driven by big data. Yet big data management often serves as a stumbling block, because many businesses continue to struggle with how to best capture and analyze their data. Unorganized data presents another roadblock.

Big Data 78

Big Data Data Agile Enterprise 78

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

Altexsoft

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. Big data is tons of mixed, unstructured information that keeps piling up at high speed. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

The Accidental Successful CIO

MAY 15, 2019

CIOs need to understand what they are going to do with big data Image Credit: Merrill College of Journalism Press Releases. As a CIO, when we think about big data we are faced with a number of questions having to do with the importance of information technology that we have not had to deal with in the past.

Big Data 85

Big Data Data Machine Learning Artificial Inteligence 85

CTOvision

MAY 23, 2014

We previously wrote about the Pentaho Big Data Blueprints series, which include design packages of use to enterprise architects and other technologists seeking operational concepts and repeatable designs. Save data costs and boost analytics performance. An intuitive graphical, no-coding big data integration.

Big Data 119

Big Data Data Storage Architecture 119

CIO

JUNE 1, 2023

Analysts IDC [1] predict that the amount of global data will more than double between now and 2026. Meanwhile, F oundry’s Digital Business Research shows 38% of organizations surveyed are increasing spend on Big Data projects.

Backup 279

Backup Enterprise Data Artificial Inteligence 279

Apiumhub

MARCH 23, 2021

One way through which businesses are doing this is through the use of Data Lakes to create a centralized place management infrastructure that allows every organization to manage, store, analyze and classify data. The concept of Data lake architecture has recently become a hot topic. What is Data Lake?

Architecture 52

Architecture Artificial Inteligence Data Machine Learning 52

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. Storage provisioning.

Big Data 63

Big Data Data Storage Microservices 63

The Crazy Programmer

SEPTEMBER 28, 2022

David’s main areas of investigation are as under: Parallel computing Computer architecture Distributed computing Workload Embedded system. He is famous for research on redundant arrays of inexpensive disks (RAID) storage. Books written by David on computer architecture are extensively used in computer science education.

Software Engineering 173

Software Engineering Architecture Storage Education 173

Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

CIO

SEPTEMBER 14, 2023

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Data Engineering 338

Data Engineering Analytics Engineering Data 338

Agile Engine

FEBRUARY 20, 2019

2018 was the second consecutive year when Gartner published an obituary of Big Data. No one, including Gartner, thinks Big Data is dead. Au contraire, Big Data has grown so ubiquitous it became “just data”, argue the authors of the obituaries. Trend 1: From Big Data to “Just Data”.

Big Data 71

Big Data Data Google Cloud Azure 71

Dell EMC

MAY 28, 2020

About 20 years ago, I started my journey into data warehousing and business analytics. Over all these years, it’s been interesting to see the evolution of big data and data warehousing, driven by the rise of artificial intelligence and widespread adoption of Hadoop. READ MORE.

Big Data 87

Big Data Data Artificial Inteligence Artificial Intelligence 87

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. What is a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

KitelyTech

FEBRUARY 3, 2021

Big data and data science are important parts of a business opportunity. How companies handle big data and data science is changing so they are beginning to rely on the services of specialized companies. User data collection is data about a user who is collected for market research purposes.

Big Data 52

Big Data Data Development Business Intelligence 52

TechCrunch

SEPTEMBER 27, 2021

As more enterprises migrate to cloud-based architectures, they are also taking on more applications (because they can) and, as a result of that, more complex workloads and storage needs. Firebolt raises $127M more for its new approach to cheaper and more efficient Big Data analytics.

Artificial Inteligence 246

Artificial Inteligence Applications Cloud Artificial Intelligence 246

Perficient

NOVEMBER 17, 2024

Datasphere empowers organizations to unify and analyze their enterprise data landscape without the need for complex extraction or rebuilding processes. This blog explores the key features of SAP Datasphere and Databricks, their complementary roles in modern data architectures, and the business value they deliver when integrated.

Artificial Inteligence 52

Artificial Inteligence Machine Learning Architecture Analytics 52

CIO

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer vs. data architect.

Data Engineering 328

Data Engineering Analytics Engineering Data 328

Netflix Tech

DECEMBER 21, 2020

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 83

Storage Data Resources Data Engineering 83

CTOvision

MAY 24, 2016

has announced the launch of the Cray® Urika®-GX system -- the first agile analytics platform that fuses supercomputing technologies with an open, enterprise-ready software framework for big data analytics. The Cray Urika-GX system is designed to eliminate challenges of big data analytics.

Big Data 64

Big Data Analytics Agile System 64

CTOvision

FEBRUARY 18, 2015

On Tuesday, January 27, 2015 CTOvision publisher and Cognitio Corp co-founder Bob Gourley hosted an event for federal big data professionals. The breakfast event focused on security for big data designs and featured the highly regarded security architect Eddie Garcia. By Katie Kennedy. Learn More about Cloudera here.

Big Data 119

Big Data Data Hardware Authentication 119

Cloudera

JUNE 13, 2024

There were thousands of attendees at the event – lining up for book signings and meetings with recruiters to fill the endless job openings for developers experienced with MapReduce and managing Big Data. This was the gold rush of the 21st century, except the gold was data.

Artificial Inteligence 102

Artificial Inteligence Big Data Technical Review Machine Learning 102

CIO

MARCH 27, 2024

For Huawei, digitally transforming manufacturing through advanced ICT including 5G technologies, cloud computing, big data and AI, is the key to reshaping industries for the future. With plans to expand, the company needed to upgrade its IT capabilities especially for storage and processing.

Automotive 130

Automotive Storage Systems Review Technical Review 130

CTOvision

DECEMBER 16, 2014

It is no secret that today’s data intensive analytics are stressing traditional storage systems. SSD) to bolster the performance of traditional storage platforms and support the ever-increasing IOPS and bandwidth requirements of their applications.

Storage 104

Storage Analytics System Data 104

Cloudera

JANUARY 12, 2018

I mentioned in an earlier blog titled, “Staffing your big data team, ” that data engineers are critical to a successful data journey. And the longer it takes to put a team in place, the likelier it is that your big data project will stall. Then this information must be executed against by the data engineers.

Data Engineering 53

Data Engineering Big Data Engineering Data 53

AWS Machine Learning - AI

AUGUST 13, 2024

Solution overview To provide a high-level understanding of how the solution works before diving deeper into the specific elements and the services used, we discuss the architectural steps required to build our solution on AWS. Figure 1: Architecture – Standard Form – Data Extraction & Storage.

Healthcare 121

Healthcare Artificial Inteligence Analysis Lambda 121

Altexsoft

SEPTEMBER 23, 2021

Evidently, common storage solutions fail to provide a unified data view and meet the needs of companies for seamless data flow. One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. What is Data Hub?

Architecture 52

Architecture Data Storage IoT 52

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 101

Data Storage Architecture Big Data 101

Data Virtualization

AUGUST 26, 2020

Recently, we have seen the rise of new technologies like big data, the Internet of things (IoT), and data lakes. But we have not seen many developments in the way that data gets delivered. Modernizing the data infrastructure is the.

Architecture 59

Architecture Data Big Data IoT 59

Cloudera

JANUARY 22, 2019

In conjunction with the evolving data ecosystem are demands by business for reliable, trustworthy, up-to-date data to enable real-time actionable insights. Big Data Fabric has emerged in response to modern data ecosystem challenges facing today’s enterprises. What is Big Data Fabric? Data access.

Big Data 44

Big Data Scalability Data Analytics 44

RapidValue

OCTOBER 12, 2020

In an effort to avoid the pitfalls that come with monolithic applications, Microservices aim to break your architecture into loosely-coupled components (or, services) that are easier to update independently, improve, scale and manage. Key Features of Microservices Architecture. Each service is known to have its own view on data models.

Microservices 53

Microservices AWS Architecture Applications 53