Dynatrace

FEBRUARY 16, 2023

Grail data lakehouse delivers massively parallel processing for answers at scale Modern cloud-native computing is constantly upping the ante on data volume, variety, and velocity. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022. Kubernetes makes spans longer,” Ortner explains.

Analytics 182

Analytics Innovation Metrics Database 182

All Things Distributed

DECEMBER 13, 2016

The British Government is also helping to drive innovation and has embraced a cloud-first policy for technology adoption. The council has deployed IoT Weather Stations in Schools across the City and is using the sensor information collated in a Data Lake to gain insights on whether the weather or pollution plays a part in learning outcomes.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

OCTOBER 7, 2015

We live in a world where massive volumes of data are generated from websites, connected devices and mobile apps. In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data.

Cloud 137

Cloud Big Data AWS Analytics 137

All Things Distributed

JUNE 26, 2016

Examples of continuous sensing are found in the managed cloud platform built by Rachio on AWS IoT to enable the secure interaction of its connected devices with cloud applications/other devices. Advanced problem solving that connects big data with machine learning. At-scale computing and visual analysis.

AWS 90

AWS Cloud Healthcare Blockchain 90

ScaleOut Software

JULY 19, 2021

Incoming data is saved into data storage (historian database or log store) for query by operational managers who must attempt to find the highest priority issues that require their attention. The following diagram illustrates a typical workflow.

IoT 78

IoT Analytics Big Data Architecture 78

ScaleOut Software

APRIL 3, 2020

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. These questions can be answered using the latest data as it streams in from the field. What are real-time digital twins and why are they useful here?

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. These questions can be answered using the latest data as it streams in from the field. What are real-time digital twins and why are they useful here?

Logistics 52

Logistics Analytics Scalability Cloud 52

Abhishek Tiwari

DECEMBER 22, 2017

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. There is a strong argument for ELT i.e. extract, load, and transform model. Classic ETL. Stateless and elastic.

Big Data 40

Big Data Retail Storage Google 40

All Things Distributed

DECEMBER 13, 2009

Expanding the Cloud - Amazon EC2 Spot Instances. These can be incidental tasks, such as the analysis of a particular dataset, or tasks where the amount of work to be done is almost never finished, such as media conversion from a Hollywoods studios movie vault, or web crawling for a search indexing company. Expanding the Cloud â??

Cloud 63

Cloud AWS Storage Innovation 63

The Morning Paper

SEPTEMBER 19, 2019

We hear a lot from Google and Microsoft about their cloud platforms, but not quite so much from the other key industry players. Autoscaling tiered cloud storage in Anna. This VLDB’19 paper describes “ how we extended a distributed key-value store called Anna into an autoscaling, multi-tier service for the cloud.”

Blockchain 46

Blockchain Hardware Google Analytics 46

All Things Distributed

DECEMBER 9, 2010

Amazon S3 has always been a scalable, durable and available data repository for almost any customer workload. However, as use of the cloud as grown, so have the file sizes customers want to store in Amazon S3 as objects. This is especially true for customers managing HD video or data-intensive instruments such as genomic sequencers.

AWS 80

AWS Big Data Scalability Storage 80

All Things Distributed

JULY 11, 2011

Spot Instances are ideal for use cases like web and data crawling, financial analysis, grid computing, media transcoding, scientific research, and batch processing. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Expanding the Cloud â?? Recent Entries.

AWS 85

AWS Storage Cloud Big Data 85

Brendan Gregg

APRIL 30, 2018

LISA originally stood for "Large Installation System Administration," where "large" meant systems with more than a gigabyte of storage, or with more than 100 users. In fact, we’d link to the first LISA conference website for reference, but this conference not only predates the Wayback Machine – it also predates the World Wide Web!

DevOps 43

DevOps Network Best Practices Programming 43

Brendan Gregg

APRIL 29, 2018

LISA originally stood for "Large Installation System Administration," where "large" meant systems with more than a gigabyte of storage, or with more than 100 users. In fact, we’d link to the first LISA conference website for reference, but this conference not only predates the Wayback Machine – it also predates the World Wide Web!

DevOps 40

DevOps Network Best Practices Programming 40

All Things Distributed

NOVEMBER 15, 2010

Expanding the Cloud - Adding the Incredible Power of the Amazon EC2 Cluster GPU Instances. Cluster GPU programming in the Cloud with the Amazon Web Services changes of all of that. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Expanding the Cloud â??

AWS 136

AWS Latency Programming Architecture 136

O'Reilly

SEPTEMBER 19, 2023

Cloud computing? It progressed from “raw compute and storage” to “reimplementing key services in push-button fashion” to “becoming the backbone of AI work”—all under the umbrella of “renting time and storage on someone else’s computers.” And, often, to giving up.

Hardware 99

Hardware Storage Big Data Blockchain 99

The Agile Manager

FEBRUARY 27, 2012

The Financial Times recently ran analysis and guest op-eds that sought to explain value in and from IT. The rise of Big Data - the ability to store and analyze large volumes of structured and unstructured, internal and external data - promises to let companies react more nimbly than ever before. Nor is cloud computing.

Ecommerce 45

Ecommerce Social Media Retail Airlines 45

ACM Sigarch

NOVEMBER 1, 2019

Alongside more traditional sessions such as Real-World Deployed Systems and Big Data Programming Frameworks, there were many papers focusing on emerging hardware architectures, including embedded multi-accelerator SoCs, in-network and in-storage computing, FPGAs, GPUs, and low-power devices. Heterogeneous ISA. Final words.

Architecture 12

Architecture Hardware Cache Storage 12