DZone

MAY 5, 2021

Anytime, every time or sometime you would have heard someone going around with data analysis and saying maybe this could have happened because of this, maybe users did not like the feature or maybe we were wrong all the time. Any analysis and prediction in data analytics across industries experience what I call maybe syndrome.

Analytics 195

Analytics Testing Big Data Code 195

Dynatrace

JULY 6, 2022

AIOps brings an additional level of analysis to observability, as well as the ability to respond to events that warrant it. This requires significant data engineering efforts, as well as work to build machine-learning models. Big data automation tools. IT automation, DevOps, and DevSecOps go together.

Artificial Intelligence 189

Artificial Intelligence Tuning Strategy Big Data 189

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

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. Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the cloud network infrastructure to address the identified problems.

Network 325

Network Transportation AWS Cloud 325

Dynatrace

APRIL 11, 2023

Today’s organizations face increasing pressure to keep their cloud-based applications performing and secure. As data from different corners of the enterprise proliferates, teams need a better way to bring data together to identify performance and security issues, minimize security risk, and drive greater business value.

Cloud 187

Cloud DevOps Open Source Retail 187

DZone

DECEMBER 21, 2020

Setting up a data warehouse is the first step towards fully utilizing big data analysis. Still, it is one of many that need to be taken before you can generate value from the data you gather. An important step in that chain of the process is data modeling and transformation.

Big Data 197

Big Data Google Scalability Processing 197

Dynatrace

AUGUST 14, 2023

As user experiences become increasingly important to bottom-line growth, organizations are turning to behavior analytics tools to understand the user experience across their digital properties. In doing so, organizations are maximizing the strategic value of their customer data and gaining a competitive advantage.

Analytics 229

Analytics Social Media Website IoT 229

Rigor

JANUARY 13, 2020

Reading time 1 min Why share the library of the web performance books while there’s a substantial collection of fantastic websites and articles on the net? High Performance Browser Networking. This book is about performance problems and the various technologies created to fight them. High Performance Websites.

Performance 75

Performance Social Media Website Website Performance 75

Dynatrace

MAY 1, 2023

With 99% of organizations using multicloud environments , effectively monitoring cloud operations with AI-driven analytics and automation is critical. IT operations analytics (ITOA) with artificial intelligence (AI) capabilities supports faster cloud deployment of digital products and services and trusted business insights.

Analytics 188

Analytics Artificial Intelligence Big Data Open Source 188

Dynatrace

OCTOBER 4, 2022

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Several pain points have made it difficult for organizations to manage their data efficiently and create actual value.

Analytics 235

Analytics Artificial Intelligence Storage Serverless 235

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. Traditional log analysis evaluates logs and enables organizations to mitigate myriad risks and meet compliance regulations.

Analytics 188

Analytics Infrastructure Storage Efficiency 188

ScaleOut Software

NOVEMBER 24, 2020

At the same time, telemetry snapshots are stored in a data lake, such as HDFS , for offline batch analysis and visualization using big data tools like Spark. The results of batch analysis are typically produced after an hour’s delay or more. A second key limitation is the lack of real-time aggregate analysis.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Dynatrace

FEBRUARY 16, 2023

As observability and security data converge in modern multicloud environments, there’s more data than ever to orchestrate and analyze. The goal is to turn more data into insights so the whole organization can make data-driven decisions and automate processes. Logs on Grail Log data is foundational for any IT analytics.

Analytics 186

Analytics Innovation Metrics Database 186

ScaleOut Software

APRIL 3, 2020

This software can simultaneously perform these actions for hundreds of thousands of ventilators to keep this vital logistical information instantly available for real-time analysis. These questions can be answered using the latest data as it streams in from the field.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

This software can simultaneously perform these actions for hundreds of thousands of ventilators to keep this vital logistical information instantly available for real-time analysis. These questions can be answered using the latest data as it streams in from the field.

Logistics 52

Logistics Analytics Scalability Cloud 52

Scalegrid

FEBRUARY 8, 2024

Consequently, if any node happens to fail, the remaining ones provide continued access to the saved information without risking service interruptions or permanent data loss. These distributed storage services also play a pivotal role in big data and analytics operations.

Storage 130

Storage Systems Big Data Azure 130

All Things Distributed

DECEMBER 20, 2017

By knowing this, Kärcher can generate new top-line revenue in the form of subscription models for its analysis portal. Marketers use big data and artificial intelligence to find out more about the future needs of their customers. More than mere support. Customers provide feedback online immediately after their purchase.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

Dynatrace

JULY 5, 2022

AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. To achieve these AIOps benefits, comprehensive AIOps tools incorporate four key stages of data processing: Collection. Aggregation.

Artificial Intelligence 286

Artificial Intelligence Cloud Innovation Strategy 286

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 other two approaches are usually avoided due to the cost involved and data sensitivity. Conclusion.

Testing 60

Testing Storage Database Processing 60

Dynatrace

OCTOBER 4, 2022

Generally, the storage technology categorizes data into landing, raw, and curated zones depending on its consumption readiness. The result is a framework that offers a single source of truth and enables companies to make the most of advanced analytics capabilities simultaneously. Support diverse analytics workloads.

Artificial Intelligence 209

Artificial Intelligence Storage Analytics Government 209

Dynatrace

APRIL 21, 2021

In February 2021, Dynatrace announced full support for Google’s Core Web Vitals metrics , which will help site owners as they start optimizing Core Web Vitals performance for SEO. Not everyone has expertise in performance optimization and how it can impact SEO. To do this effectively, you need a big data processing approach.

Traffic 263

Traffic Metrics Mobile Analytics 263

The Netflix TechBlog

APRIL 29, 2019

The service that orchestrates failover uses numpy and scipy to perform numerical analysis, boto3 to make changes to our AWS infrastructure, rq to run asynchronous workloads and we wrap it all up in a thin layer of Flask APIs. CORE The CORE team uses Python in our alerting and statistical analytical work.

Open Source 279

Open Source Network Infrastructure Big Data 279

Dynatrace

OCTOBER 17, 2022

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. This second solution picks up at data collection, aggregation, and analysis, preparing it for execution. Deterministic AI.

DevOps 196

DevOps Artificial Intelligence Healthcare Innovation 196

The Netflix TechBlog

JULY 26, 2021

Such a paradigm aspires to assist front-line operations personnel and stakeholders in “running the business”²; performing their tasks through means such as ad hoc analysis, decision-support, and tracking (of tasks, assets, schedules, etc). Data Mesh leverages Iceberg tables as data warehouse sinks for downstream analytics use cases.

Big Data 253

Big Data Government Analytics Processing 253

Dynatrace

OCTOBER 25, 2022

This meant there were still operations, only they were performed by someone else! AIOps , a term coined by Gartner in 2016, combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination. Evolution of modern AIOps.

DevOps 218

DevOps Big Data Cloud Innovation 218

Dynatrace

OCTOBER 14, 2021

Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” A comprehensive, modern approach to AIOps is a unified platform that encompasses observability, AI, and analytics.

Artificial Intelligence 213

Artificial Intelligence DevOps Innovation Metrics 213

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

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

DECEMBER 13, 2016

With the launch of the AWS Europe (London) Region, AWS can enable many more UK enterprise, public sector and startup customers to reduce IT costs, address data locality needs, and embark on rapid transformations in critical new areas, such as big data analysis and Internet of Things. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

Testsigma

SEPTEMBER 8, 2021

If I consider current times, it has become a core concept in development, management, analytics, and also – automation testing. In-depth reporting : Testsigma’s reports are of extremely high quality and have been appreciated for the analytical information displayed in them. Cloud-based automation testing is a simple concept.

Cloud 76

Cloud Testing AWS Testing Tools 76

The Morning Paper

SEPTEMBER 19, 2019

Hyper Dimension Shuffle describes how Microsoft improved the cost of data shuffling, one of the most costly operations, in their petabyte-scale internal big data analytics platform, SCOPE. The authors claim a two orders-of-magnitude performance improvement. speedup over the best performing existing method.

Blockchain 46

Blockchain Hardware Google Analytics 46

Highly Scalable

MARCH 10, 2015

Retail is one of the most important business domains for data science and data mining applications because of its prolific data and numerous optimization problems such as optimal prices, discounts, recommendations, and stock levels that can be solved using data analysis methods. The resource can be homogenous (i.e.

Retail 152

Retail C++ Analytics Metrics 152

Smashing Magazine

JULY 29, 2019

Throughout the experiment I will suggest performance tips to speed up the first contentful paint and perceived loading time of the page. Performance Tip #1: Inline Critical CSS. Performance Tip #2: Minify And Uglify Your Assets. Performance Tip #3: Less Is More. Performance Tip #4: Compress Text-based Assets.

Cache 97

Cache Google Mobile Network 97

Dynatrace

APRIL 25, 2023

Having access to large data sets can be helpful, but only if organizations are able to leverage insights from the information. These analytics can help teams understand the stories hidden within the data and share valuable insights. “That is what exploratory analytics is for,” Schumacher explains.

Analytics 201

Analytics Big Data Media Operating System 201

All Things Distributed

NOVEMBER 15, 2010

This incredible power is available for anyone to use in the usual pay-as-you-go model, removing the investment barrier that has kept many organizations from adopting GPUs for their workloads even though they knew there would be significant performance benefit. with a peak performance of 4.701 PetaFLOPS. Where to go from here?

AWS 136

AWS Latency Programming Architecture 136

All Things Distributed

NOVEMBER 15, 2016

The data infrastructure to collect, store, and process data is geared primarily towards developers and IT professionals whereas insights need to be derived by not just technical professionals but also non-technical business users. Auto-discovery : One of the challenges with BI is discovering and accessing the data.

Analytics 152

Analytics Availability Media Social Media 152

All Things Distributed

NOVEMBER 30, 2016

Amazon AI services make the full power of Amazon's natural language understanding, speech recognition, text-to-speech, and image analysis technologies available at any scale, for any app, on any device, anywhere. Facial Analysis. Amazon Lex. Amazon Rekognition solves these problems.

AWS 165

AWS Lambda Artificial Intelligence Mobile 165