Dynatrace

JUNE 26, 2023

This, in turn, accelerates the need for businesses to implement the practice of software automation to improve and streamline processes. This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI. Software is behind most of our human and business interactions.

Software 186

Software Software Analytics Big Data 186

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., I’ve been excited about the potential for approximate query processing in analytic clusters for some time, and this paper describes its use at scale in production. VLDB’19. Approximate query support. Implementation.

Big Data 57

Big Data Analytics Latency Azure 57

The Netflix TechBlog

JUNE 1, 2021

Data Engineers of Netflix?—?Interview Interview with Samuel Setegne Samuel Setegne This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. For example?—?clinical

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

Dynatrace

JULY 6, 2022

Scripts and procedures usually focus on a particular task, such as deploying a new microservice to a Kubernetes cluster, implementing data retention policies on archived files in the cloud, or running a vulnerability scanner over code before it’s deployed. The range of use cases for automating IT is as broad as IT itself.

Artificial Intelligence 187

Artificial Intelligence Tuning Strategy Big Data 187

All Things Distributed

AUGUST 18, 2011

Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud. However, this cannot be done without efficient, scalable data analytics.

Big Data 111

Big Data Analytics AWS Cloud 111

Dynatrace

DECEMBER 15, 2022

Complex cloud computing environments are increasingly replacing traditional data centers. In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. Organizations are also increasingly integrating application security into their DevOps teams and processes — also known as DevSecOps.

Artificial Intelligence 201

Artificial Intelligence DevOps Hardware Virtualization 201

Scalegrid

MAY 13, 2020

Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Testsigma

MAY 26, 2021

In today’s world where ‘data is the new oil’ ( as said by Clive Humby), not giving proper attention to data-driven testing is not justified. If you have an application that needs data input in some form then it will require data-driven testing. The data repository could be a CSV file, excel sheet, DB table, etc.

Testing 70

Testing Healthcare Performance Testing Website 70

The Netflix TechBlog

JUNE 7, 2021

At much less than 1% of CPU and memory on the instance, this highly performant sidecar provides flow data at scale for network insight. Berkeley Packet Filter (BPF) is an in-kernel execution engine that processes a virtual instruction set, and has been extended as eBPF for providing a safe way to extend kernel functionality.

Network 325

Network Transportation AWS Cloud 325

Dynatrace

MARCH 24, 2023

Container technology enables organizations to efficiently develop cloud-native applications or to modernize legacy applications to take advantage of cloud services. Container orchestration is a process that automates the deployment and management of containerized applications and services at scale.

Infrastructure 184

Infrastructure Open Source Operating System Cloud 184

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. Unlike manual or automatic log queries, in-memory computing can continuously run analytics code on all incoming data and instantly find issues.

IoT 78

IoT Analytics Big Data Architecture 78

Dynatrace

JULY 6, 2020

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. See the health of your big data resources at a glance. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics.

Azure 147

Azure Cloud Big Data Virtualization 147

Testsigma

JULY 14, 2020

According to Wikipedia, Data-Driven Testing(DDT) is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded. Database tables.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

All Things Distributed

DECEMBER 20, 2017

How companies can use ideas from mass production to create business with data. In this way, designers are part of an ecosystem in which the functionalities of simulations, data and people come together, enabling them to develop better products faster. Value creation through data. Strategically, IT doesn't matter.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

Testsigma

MAY 7, 2020

IBM Big Data and Analytics Hub website cited a case study, where a US insurance company was estimating 15% of their testing efforts to be just test data collection for the backend system and the frontend system. The test data management for the company had become a big problem and had to be solved.

Testing 60

Testing Storage Database Processing 60

The Netflix TechBlog

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

Processing 210

Processing Big Data Efficiency Engineering 210

Percona

JANUARY 19, 2023

With disks being faster nowadays and CPU and memory resources being cheaper, we could easily say MySQL can handle TBs of data with good performance. For instance, in Percona Managed Services , we have many clients with TBs worth of data that are well performant. There are many compression tools and algorithms for data out there.

Open Source 91

Open Source Storage Database Big Data 91

The Netflix TechBlog

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. With the latest Data Mesh Platform, data movement in Netflix Studio reaches a new stage.

Big Data 253

Big Data Government Analytics Processing 253

The Netflix TechBlog

MARCH 2, 2021

Stephanie Lane , Wenjing Zheng , Mihir Tendulkar Source credit: Netflix Within the rapid expansion of data-related roles in the last decade, the title Data Scientist has emerged as an umbrella term for myriad skills and areas of business focus. Learning through data is in Netflix’s DNA. It can be hard to know from the outside.

Analytics 207

Analytics C++ Innovation Engineering 207

Dynatrace

MAY 1, 2023

IT operations analytics is the process of unifying, storing, and contextually analyzing operational data to understand the health of applications, infrastructure, and environments and streamline everyday operations. ITOA automates repetitive cloud operations tasks and streamlines the flow of analytics into decision-making processes.

Analytics 186

Analytics Artificial Intelligence Big Data Open Source 186

High Scalability

APRIL 14, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Scalability Engineering 105

High Scalability

MAY 12, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MARCH 24, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

APRIL 28, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MARCH 30, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MAY 26, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 100

Education AWS Software Engineering Scalability 100

Dynatrace

APRIL 20, 2023

Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. based financial services group, discussed how the bank uses log monitoring on the Dynatrace platform with an emphasis on observability and security data.

Analytics 186

Analytics Infrastructure Storage Efficiency 186

All Things Distributed

JUNE 26, 2016

previously known as Emdeon) uses Amazon SNS to handle millions of confidential client transactions daily to process claims and pharmacy requests serving over 340K physicians and 60K pharmacies in full compliance with healthcare industry regulations. . Seamless ingestion of large volumes of sensed data.

AWS 90

AWS Cloud Healthcare Blockchain 90

The Netflix TechBlog

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. On the other hand, these optimizations themselves need to be sufficiently inexpensive to justify their own processing cost over the gains they bring.

Storage 203

Storage Latency Efficiency Data Engineering 203

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

ScaleOut Software

NOVEMBER 24, 2020

Rapid advances in the telematics industry have dramatically boosted the efficiency of vehicle fleets and have found wide ranging applications from long haul transport to usage-based insurance. The volume of incoming telemetry challenges current telematics systems to keep up and quickly make sense of all the data.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

The Netflix TechBlog

OCTOBER 27, 2020

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy.

Latency 243

Latency Storage Big Data Tuning 243

Testsigma

MAY 14, 2021

However, the primary goal of traditional testing and cloud-based testing remains the same i.e., to deliver high-quality and efficient software. Data is present on the local server and hence cannot be accessed from everywhere. Data is present on the cloud hence can be accessed from any location. Cloud-based testing disadvantages.

Cloud 67

Cloud Testing Testing Tools Internet 67

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse?

Artificial Intelligence 207

Artificial Intelligence Analytics Storage Government 207

Dynatrace

FEBRUARY 16, 2023

How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. The goal is to turn more data into insights so the whole organization can make data-driven decisions and automate processes.

Analytics 184

Analytics Innovation Metrics Database 184

The Netflix TechBlog

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

O'Reilly

SEPTEMBER 19, 2023

” I’ve called out the data field’s rebranding efforts before; but even then, I acknowledged that these weren’t just new coats of paint. Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” Goodbye, Hadoop.

Hardware 99

Hardware Storage Big Data Blockchain 99