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.” They require extensive training, and real-user must spend valuable time filtering any false positives. What is AIOps?

Artificial Intelligence 224

Artificial Intelligence DevOps Innovation Metrics 224

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. Creating training datasets for machine learning !

Big Data 57

Big Data Analytics Latency Azure 57

The Netflix TechBlog

NOVEMBER 20, 2023

IPS enables users to continue to use the data processing patterns with minimal changes. Introduction Netflix relies on data to power its business in all phases. As our business scales globally, the demand for data is growing and the needs for scalable low latency incremental processing begin to emerge. append, overwrite, etc.).

Processing 221

Processing Big Data Efficiency Engineering 221

All Things Distributed

APRIL 27, 2011

We use high-performance transactions systems, complex rendering and object caching, workflow and queuing systems, business intelligence and data analytics, machine learning and pattern recognition, neural networks and probabilistic decision making, and a wide variety of other techniques. Driving down the cost of Big-Data analytics.

Technology 132

Technology Technology AWS Storage 132

Highly Scalable

MARCH 10, 2015

Although there are many books on data mining in general and its applications to marketing and customer relationship management in particular [BE11, AS14, PR13 etc.], The rest of the article is organized as follows: We first introduce a simple framework that ties together a retailer’s actions, profits and data.

Retail 152

Retail C++ Analytics Metrics 152

VoltDB

OCTOBER 17, 2024

Artificial Intelligence (AI) and Machine Learning (ML) AI and ML algorithms analyze real-time data to identify patterns, predict outcomes, and recommend actions. Big Data Analytics Handling and analyzing large volumes of data in real-time is critical for effective decision-making.

Automotive 52

Automotive IoT Energy Artificial Intelligence 52

Tech News Gather

OCTOBER 7, 2023

You can review call recordings, identify areas for improvement, and train your staff to serve your customers better. Moreover, the data collected by the app can help you understand customer pain points and preferences. Data-Driven Decision Making In the age of big data, data-driven decision-making is paramount.

Strategy 52

Strategy Big Data Scalability Games 52

SQL Server According to Bob

FEBRUARY 15, 2018

The conference kicks off next week on Wednesday February 21st with Training Days and lasts through Saturday, February 24th. Best practices on Building a Big Data Analytics Solution – Michael Rys. If you want to learn about Azure Data Lake, there is no one better. Cosmos DB has generated a huge interest.

Engineering 40

Engineering Azure Best Practices Servers 40

All Things Distributed

MAY 21, 2018

We already have an idea of how digitalization, and above all new technologies like machine learning, big-data analytics or IoT, will change companies' business models — and are already changing them on a wide scale. The workplace of the future.

Artificial Intelligence 69

Artificial Intelligence Technology Technology IoT 69

Smashing Magazine

JULY 29, 2019

Notice the async keyword on the Google analytics script? Google analytics has ‘low’ priority. It’s difficult to detect if someone on a desktop is on a broadband connection or is tethering through a data-limited dongle or mobile. The format that keeps the best quality for the smallest size may not be the one you expect.

Cache 97

Cache Mobile Google Network 97

Dynatrace

JUNE 26, 2024

This is where observability analytics can help. What is observability analytics? Observability analytics enables users to gain new insights into traditional telemetry data such as logs, metrics, and traces by allowing users to dynamically query any data captured and to deliver actionable insights.

Analytics 196

Analytics Infrastructure Metrics Efficiency 196

All Things Distributed

NOVEMBER 30, 2016

automatic speech recognition, natural language understanding, image classification), collect and clean the training data, and train and tune the machine learning models. Effectively applying AI involves extensive manual effort to develop and tune many different types of machine learning and deep learning algorithms (e.g.

AWS 156

AWS Lambda Artificial Intelligence Mobile 156

Adrian Cockcroft

NOVEMBER 18, 2024

SUS105 | Training and certification support in your sustainability journey Sustainability is a global priority for AWS and is of tremendous importance to its customers as well. Benoit de Chateauvieux, Climate Tech Solutions Architect, AWS Lisbeth Kaufman, Head of Climate Tech Startups BD, Amazon Web Services SUS104 ?

AWS 98

AWS Energy Lambda Government 98