Dynatrace

DECEMBER 15, 2022

In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. This transition to public, private, and hybrid cloud is driving organizations to automate and virtualize IT operations to lower costs and optimize cloud processes and systems. So, what is ITOps? What is ITOps? ITOps vs. AIOps.

Artificial Intelligence 208

Artificial Intelligence DevOps Hardware Virtualization 208

Dynatrace

JULY 5, 2022

Artificial intelligence for IT operations (AIOps) uses machine learning and AI to help teams manage the increasing size and complexity of IT environments through automation. To achieve these AIOps benefits, comprehensive AIOps tools incorporate four key stages of data processing: Collection. Aggregation.

Artificial Intelligence 291

Artificial Intelligence Cloud Innovation Strategy 291

Scalegrid

MARCH 14, 2024

Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. This consistency aids not only in application deployment but also simplifies scaling processes.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

JUNE 1, 2020

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course, end-users that access these applications – including your customers and employees. Websites, mobile apps, and business applications are typical use cases for monitoring.

Artificial Intelligence 183

Artificial Intelligence Social Media Monitoring IoT 183

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. CloudOps includes processes such as incident management and event management. The four stages of data processing.

DevOps 201

DevOps Artificial Intelligence Healthcare Innovation 201

Testsigma

FEBRUARY 12, 2021

The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. With all of these processes in place, cost optimization is also a high concern for organizations worldwide. The world’s Artificial Intelligence market is anticipated to increase from $28.42

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

DZone

JUNE 4, 2019

Financial Analytics – Financial services and financial technology (FinTech) are increasingly turning to automation and artificial intelligence to fuel their decision making processes for investments. There are several AI/ML focused use cases to highlight.

Storage 100

Storage FinTech Artificial Intelligence Performance 100

Dynatrace

JUNE 1, 2020

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course end-users that access these applications – including your customers and employees. Websites, mobile apps, and business applications are typical use cases for monitoring.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

All Things Distributed

DECEMBER 20, 2017

Developments like cloud computing, the internet of things, artificial intelligence, and machine learning are proving that IT has (again) become a strategic business driver. Marketers use big data and artificial intelligence to find out more about the future needs of their customers. More than mere support.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

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.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

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.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

O'Reilly

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Hardware 99

Hardware Storage Big Data Blockchain 99

Abhishek Tiwari

DECEMBER 27, 2017

A common theme across all these trends is to remove the complexity by simplifying data management as a whole. In 2018, we anticipate that ETL will either lose relevance or the ETL process will disintegrate and be consumed by new data architectures. Unified data management architecture.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

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. Only parts of the processes are being performed by machines, or at least supported by them.

Artificial Intelligence 77

Artificial Intelligence Technology Technology IoT 77

All Things Distributed

NOVEMBER 30, 2016

There are many more application areas where we use ML extensively: search, autonomous drones, robotics in fulfillment centers, text processing and speech recognition (such as in Alexa) etc. And this process must be repeated for every object, face, voice, and language feature in an application.

AWS 166

AWS Lambda Artificial Intelligence Mobile 166