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

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

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 Machine Learning 52

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

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 333

Analytics Data Analysis Business Analytics 333

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 85

Big Data Technology Tools Cloud 85

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 235

Generative AI Artificial Inteligence Open Source ChatGPT 235

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

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

Xebia

MAY 16, 2023

Data Engineers were tempted by the pressure of the moment to give up on testing all together. There was no need for generating your own data; just take a percentage of production data. In many cases, these tasks ended up on the shoulders of the Data Engineers themselves. Overly restrictive governance.

Testing 130

Testing How To Data Engineering Engineering 130

Altexsoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

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 Machine Learning Artificial Inteligence 117

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

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 87

Enterprise Cloud Data Machine Learning 87

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 89

Data Analytics Open Source Architecture 89

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 85

Azure Open Source Virtualization Software Engineering 85

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 60

Telecommunications Data Architecture Big Data 60

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

Apiumhub

APRIL 8, 2021

Adrian specializes in mapping the Database Management System (DBMS), Big Data and NoSQL product landscapes and opportunities. Ronald van Loon has been recognized among the top 10 global influencers in Big Data, analytics, IoT, BI, and data science. Ronald van Loon. Kirk Borne. Marcus Borba. Cindi Howson.

Artificial Inteligence 109

Artificial Inteligence Technical Advisors Data Machine Learning 109

Altexsoft

APRIL 16, 2021

An overview of data warehouse types. Optionally, you may study some basic terminology on data engineering or watch our short video on the topic: What is data engineering. What is data pipeline. Creating a cube is a custom process each time, because data can’t be updated once it was modeled in a cube.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

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 106

Data Architecture Analytics Government 106

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

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 Software Review 93

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

Altexsoft

NOVEMBER 7, 2022

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. Source: Apache Airflow.

Weak Development Team 52

Weak Development Team Technical Review Software Review Systems Review 52

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 Machine Learning Artificial Inteligence Weak Development Team 90

Erik Bernhardsson

OCTOBER 27, 2015

I was featured in Peadar Coyle’s interview series interviewing various “data scientists” – which is kind of arguable since (a) all the other ppl in that series are much cooler than me (b) I’m not really a data scientist. So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

I was featured in Peadar Coyle’s interview series interviewing various “data scientists” – which is kind of arguable since (a) all the other ppl in that series are much cooler than me (b) I’m not really a data scientist. So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

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