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

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?

Big Data 116

Big Data Healthcare Applications Data 116

CIO

JANUARY 19, 2024

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Check out our list of top big data and data analytics certifications.)

Artificial Inteligence 317

Artificial Inteligence Data Machine Learning Azure 317

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

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics.

Weak Development Team 52

Weak Development Team Big Data Data Artificial Inteligence 52

TechCrunch

FEBRUARY 23, 2022

Portland, Oregon-based startup thatDot , which focuses on streaming event processing, today announced the launch of Quine , a new MIT-licensed open source project for data engineers that combines event streaming with graph data to create what the company calls a “streaming graph.”

Engineering 190

Engineering Open Source Big Data Fintech 190

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

CIO

JUNE 7, 2022

Data analysts and others who work with analytics use a range of tools to aid them in their roles. Data analytics and data science are closely related. Data analytics is a component of data science, used to understand what an organization’s data looks like.

Analytics 338

Analytics Data Analysis Business Analytics 338

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

OpenCredo

JANUARY 26, 2023

I’m excited to try out this method, as I’m already a big fan of Apache Beam , the now open-sourced framework which backs Dataflow. Data Modelling This is the rough technique we normally use when modelling graph data: Start with a blank canvas, and draw the obvious node types, and the relationships between them.

Big Data 52

Big Data Data Software Engineering Data Engineering 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. Key challenges.

Big Data 63

Big Data Data Storage Microservices 63

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Many companies are just beginning to address the interplay between their suite of AI, big data, and cloud technologies. I’ll also highlight some interesting uses cases and applications of data, analytics, and machine learning. Data Platforms. Data Integration and Data Pipelines. Model lifecycle management.

Big Data 86

Big Data Technology Tools Cloud 86

Cloudera

AUGUST 22, 2024

Established in 2014, this center has become a cornerstone of Cloudera’s global strategy, playing a pivotal role in driving the company’s three growth pillars: accelerating enterprise AI, delivering a truly hybrid platform, and enabling modern data architectures.

Innovation 67

Innovation Artificial Inteligence Machine Learning Technical Review 67

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

CIO

JULY 14, 2023

A general LLM won’t be calibrated for that, but you can recalibrate it—a process known as fine-tuning—to your own data. Fine-tuning applies to both hosted cloud LLMs and open source LLM models you run yourself, so this level of ‘shaping’ doesn’t commit you to one approach.

Generative AI 246

Generative AI Artificial Inteligence Open Source ChatGPT 246

Battery Ventures

OCTOBER 7, 2020

The research pinpointed some of the mega-trends—including cloud computing and the rise of open-source technology—that are upending today’s huge enterprise-IT market as organizations across industries push to digitize their operations by modernizing their technology stacks.

Open Source 144

Open Source Cloud Google Cloud Azure 144

TechCrunch

DECEMBER 1, 2020

That will include more remediation once problems are identified: that is, in addition to identifying issues, engineers will be able to start automatically fixing them, too. The company is also used by data teams from large Fortune 500 enterprises to smaller startups. ” Not a great scenario.

Tools 214

Tools Data Weak Development Team Big Data 214

TechCrunch

MARCH 22, 2021

Like similar startups, y42 extends the idea data warehouse, which was traditionally used for analytics, and helps businesses operationalize this data. At the core of the service is a lot of open source and the company, for example, contributes to GitLabs’ Meltano platform for building data pipelines.

Business Intelligence 244

Business Intelligence Software Review B2B Analytics 244

Kentik

JULY 19, 2017

Because “package tracking” in a large network is a big data problem, and traditional network management tools weren’t built for that volume of data. Of course just opening one’s mind to the dream isn’t the same as having the solution. Act 3: Big Data SaaS to the Rescue. How do we start to automate?

Big Data 40

Big Data Network Data Systems Review 40

CTOvision

JUNE 15, 2015

You know Spark, the free and open source complement to Apache Hadoop that gives enterprises better ability to field fast, unified applications that combine multiple workloads, including streaming over all your data. They also launched a plan to train over a million data scientists and data engineers on Spark.

Open Source 117

Open Source Big Data Artificial Inteligence Machine Learning 117

CIO

AUGUST 18, 2022

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). You can intuitively query the data from the data lake.

Data 350

Data Technical Advisors Technical Review Artificial Inteligence 350

Cloudera

OCTOBER 5, 2020

Cloudera Data Platform Powered by NVIDIA RAPIDS Software Aims to Dramatically Increase Performance of the Data Lifecycle Across Public and Private Clouds. This exciting initiative is built on our shared vision to make data-driven decision-making a reality for every business. Compared to previous CPU-based architectures, CDP 7.1

Enterprise 92

Enterprise Cloud Data Artificial Inteligence 92

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

NOVEMBER 19, 2020

Cloudera Data Platform (CDP) is a solution that integrates open-source tools with security and cloud compatibility. Governance: With a unified data platform, government agencies can apply strict and consistent enterprise-level data security, governance, and control across all environments.

Government 119

Government Artificial Inteligence Data Machine Learning 119

Cloudera

JUNE 18, 2022

Netflix, where this innovation was born, is perhaps the best example of a 100 PB scale S3 data lake that needed to be built into a data warehouse. The cloud native table format was open sourced into Apache Iceberg by its creators. At Cloudera, we are proud of our open-source roots and committed to enriching the community.

Data 93

Data Analytics Open Source Architecture 93

Cloudera

JULY 27, 2021

When it comes to Data and AI, the industry is increasingly committed to a hybrid cloud approach. Speaking to Aaron Boasman-Patel, Vice President, AI & Customer Experience at the TM Forum, he says the industry is all-in on Big Data. Big Data has long been a growth area in telecom,’ he told me.

Telecommunications 64

Telecommunications Data Architecture Big Data 64

The Citus Data

MARCH 31, 2023

Americas livestream, Citus open source user, real-time analytics, JSONB) Lessons learned: Migrating from AWS-Hosted PostgreSQL RDS to Self-Hosted Citus , by Matt Klein & Delaney Mackenzie of Jellyfish.co. (on-demand Checkpoint and WAL configs , by Samay Sharma on the Postgres open source team at Microsoft.

Azure 84

Azure Open Source Virtualization Software Engineering 84

Kentik

MARCH 7, 2023

Solving these problems for distributed cloud networks has required a big data approach, ultimately resulting in the evolution of network observability. Rich context and real-time datasets allow network engineers to dynamically filter, drill down, and map networks as queries adjust. Leverage automated insights and response flows.

Network 99

Network Cloud Data Case Study 99

Cloudera

APRIL 22, 2021

This CVD is built using Cloudera Data Platform Private Cloud Base 7.1.5 Apache Ozone is one of the major innovations introduced in CDP, which provides the next generation storage architecture for Big Data applications, where data blocks are organized in storage containers for larger scale and to handle small objects.

Data 101

Data Storage Architecture Big Data 101

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. The future is hybrid data, embrace it.

Data 112

Data Architecture Analytics Big Data 112

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

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. On-premise data integration tools. Open-source data integration tools.

Tools 52

Tools Data Software Review Open Source 52

Kentik

MAY 23, 2017

Given the advanced capabilities provided by cloud and big data technology, there’s no longer any justification for legacy monitoring appliances that summarize away all the details and force operators to swivel between siloed tools. ISPs can gain similar advantages by becoming far more data driven. Build versus Buy.

Network 40

Network Open Source Big Data Load Balancer 40

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 109

Data Analytics Travel Disaster Recovery 109

AWS Machine Learning - AI

NOVEMBER 20, 2024

Aurora MySQL-Compatible is a fully managed, MySQL-compatible, relational database engine that combines the speed and reliability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. Data Engineer at Amazon Ads. Akchhaya Sharma is a Sr.

Data 81

Data AWS Groups Knowledge Base 81

Hu's Place - HitachiVantara

MAY 10, 2019

A Big Data Analytics pipeline– from ingestion of data to embedding analytics consists of three steps Data Engineering : The first step is flexible data on-boarding that accelerates time to value. This will require another product for data governance. This is colloquially called data wrangling.

Data 90

Data Artificial Inteligence Machine Learning Weak Development Team 90

Altexsoft

OCTOBER 21, 2022

Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time. It offers high throughput, low latency, and scalability that meets the requirements of Big Data. Plus the name sounded cool for an open-source project.”.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93