Scalegrid

MAY 13, 2020

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. Let’s walk through the top use cases for Greenplum: Analytics.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

FEBRUARY 1, 2024

Organizations that miss out on implementing AI risk falling behind their competition in an age where software delivery speed, agility, and security are crucial success factors. By packaging [these capabilities] into hypermodal AI, we are able to run deep custom analytics use cases in sixty seconds or less.”

Artificial Intelligence 182

Artificial Intelligence Analytics Efficiency Database 182

Dynatrace

OCTOBER 4, 2022

Grail needs to support security data as well as business analytics data and use cases. With that in mind, Grail needs to achieve three main goals with minimal impact to cost: Cope with and manage an enormous amount of data —both on ingest and analytics. High-performance analytics—no indexing required.

Artificial Intelligence 264

Artificial Intelligence Analytics Storage Architecture 264

Dynatrace

MAY 17, 2023

This is one example of the many use cases we’re exploring. For example, it can help DevOps and platform engineering teams write code snippets by drawing on information from software libraries. Achieving this precision requires another type of artificial intelligence: causal AI.

Innovation 256

Innovation Software Software Artificial Intelligence 256

Dynatrace

NOVEMBER 2, 2022

This methodology combines software design, development, automation, operations, and analytics to boost customer experience, increase application security, and reduce downtime that affects business outcomes. Today, software development teams use artificial intelligence (AI) to conduct software testing so they can eliminate human intervention.

Software 192

Software Software Artificial Intelligence DevOps 192

Dynatrace

OCTOBER 14, 2021

Artificial intelligence for IT operations (AIOps) is an IT practice that uses machine learning (ML) and artificial intelligence (AI) to cut through the noise in IT operations, specifically incident management. Let’s say, for example, an application is experiencing a slowdown in receiving its search requests.

Artificial Intelligence 208

Artificial Intelligence DevOps Innovation Metrics 208

Dynatrace

JANUARY 23, 2024

Deriving business value with AI, IT automation, and data reliability When it comes to increasing business efficiency, boosting productivity, and speeding innovation, artificial intelligence takes center stage. And the ability to easily create custom apps enables teams to do any analytics at any time for any use case.

Performance 182

Performance DevOps Innovation Artificial Intelligence 182

Dynatrace

JULY 5, 2022

As organizations look to speed their digital transformation efforts, automating time-consuming, manual tasks is critical for IT teams. 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. Dynatrace news.

Artificial Intelligence 282

Artificial Intelligence Cloud Innovation Strategy 282

Dynatrace

MAY 27, 2022

As a result, many IT teams are turning to artificial intelligence for IT operations (AIOps) , which integrates AI into operations to automate systems across the development lifecycle. Each piece of the AIOps triumvirate plays a crucial role in the automation process to speed innovation. An example of the self-healing web.

Artificial Intelligence 183

Artificial Intelligence Innovation Servers Database 183

Dynatrace

MARCH 22, 2023

For example, ensuring software stacks don’t use default accounts or passwords, error handling doesn’t reveal sensitive information, and application server frameworks use secure settings. In addition, analyze data from a unified observability view that provides contextualized application security analytics.

Open Source 194

Open Source Artificial Intelligence Internet Internet 194

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. Let’s say, for example, an application is experiencing a slowdown in receiving its search requests. Deterministic AI.

DevOps 192

DevOps Artificial Intelligence Healthcare Innovation 192

Scalegrid

DECEMBER 21, 2023

Such as INFO which gives statistics about the server, LATENCY LATEST which provides latency measurements in real time and MONITOR which allows observation of the client’s transmitted command at live speed. Examples include slow command execution time which leads to poor latency and increased memory usage.

Strategy 130

Strategy Monitoring Latency DevOps 130

Scalegrid

JANUARY 12, 2024

Various forms can take shape when discussing workloads within the realm of cloud computing environments – examples include order management databases, collaboration tools, videoconferencing systems, virtual desktops, and disaster recovery mechanisms. This also aids scalability down the line.

Cloud 130

Cloud Virtualization Storage Efficiency 130

Dynatrace

MARCH 16, 2021

To recognize both immediate and long-term benefits, organizations must deploy intelligent solutions that can unify management, streamline operations, and reduce overall complexity. Here’s how. What is AIOps and what are the challenges? What is the impact of AIOps on the business?

Artificial Intelligence 189

Artificial Intelligence Open Source Cloud Analytics 189

Dynatrace

JANUARY 6, 2020

We also made the point that machine learning systems can improve IT efficiency; speeding analysis by narrowing focus. Let’s look at a few simple examples on how intellectual debt might begin to accrue. Intermittent problems have always been challenging – to capture, to reproduce, to analyze.

Artificial Intelligence 144

Artificial Intelligence Efficiency Analytics Innovation 144

All Things Distributed

DECEMBER 20, 2017

In today's era of global digitalization there are many examples that show that IT does matter. Developments like cloud computing, the internet of things, artificial intelligence, and machine learning are proving that IT has (again) become a strategic business driver. More than mere support.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

O'Reilly

NOVEMBER 28, 2023

47% are using it specifically to generate marketing copy, and 56% are using it for other kinds of copy (internal memos and reports, for example). AI isn’t yet at the point where it can write as well as an experienced human, but if your company needs catalog descriptions for hundreds of items, speed may be more important than brilliant prose.

Open Source 108

Open Source Artificial Intelligence Google Infrastructure 108

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. At the same time there are many grounds for optimism.

Artificial Intelligence 76

Artificial Intelligence Technology Technology IoT 76

Abhishek Tiwari

DECEMBER 27, 2017

Databricks Delta is a perfect example of this class. Data solution vendors like SnapLogic and Informatica are already developing machine learning and artificial intelligence (AI) based smart data integration assistants. Overall, less complexity to deal with. A solution like Delta makes ETL unnecessary for the data warehousing.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49