CIO

JUNE 14, 2023

Start with storage. Going from 250 PB to even a single exabyte means multiplying storage capabilities four times. When adding more storage nodes, it is important to ensure that the capacity addition is more optimal and efficient. So, what does it require for organizations to go from PB to EB scale? Focus on scalability.

Data 157

Data Scalability Storage Big Data 157

CIO

JANUARY 9, 2023

2] Here, we explore the demands and opportunities of edge computing and how an approach to Business Outcomes-as-a-Service can provide end-to-end analytics with lowered operational risk. It’s bringing advanced analytics and AI capabilities where they’re needed most – the edge. And they’re achieving significant wins. [2]

IoT 301

IoT Technical Review Company Data 301

AWS Machine Learning - AI

FEBRUARY 26, 2024

In this post, we demonstrate a few metrics for online LLM monitoring and their respective architecture for scale using AWS services such as Amazon CloudWatch and AWS Lambda. Overview of solution The first thing to consider is that different metrics require different computation considerations. The function invokes the modules.

Artificial Inteligence 106

Artificial Inteligence AWS Lambda Metrics 106

TechCrunch

FEBRUARY 24, 2021

Many companies spend a significant amount of money and resources processing data from logs, traces and metrics, forcing them to make trade-offs about how much to collect and store. “The classic problem with these cluster-based databases is that they’ve got locally attached storage.

Data 177

Data Storage Metrics Google Cloud 177

TechCrunch

MAY 17, 2022

“The industry at large is upon the next wave of technical hurdles for analytics based on how organizations want to derive value from data. Now, the challenge organizations are trying to solve are large scale analytics applications enabling interactive data experiences. Imply’s Apache Druid-powered query view.

Technical Review 249

Technical Review Analytics Cloud Enterprise 249

Cloudera

JULY 24, 2023

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

Open Source 66

Open Source Analytics Software Review Metrics 66

Hu's Place - HitachiVantara

JANUARY 15, 2019

For lack of similar capabilities, some of our competitors began implying that we would no longer be focused on the innovative data infrastructure, storage and compute solutions that were the hallmark of Hitachi Data Systems. A REST API is built directly into our VSP storage controllers.

Systems Review 72

Systems Review Storage System Software Review 72

Altexsoft

DECEMBER 9, 2020

Still, today, according to Deloitte research, insight-driven companies are fewer than those not using an analytical approach to decision-making, even though the majority agrees on its importance. What is analytics maturity model? They also serve as a guide in the analytics transformation process. Stages of analytics maturity.

Analytics 102

Analytics Technical Review Technology Applications 102

RapidValue

JUNE 26, 2020

Analytics is all about meaningful information at your fingertips. Reporting solutions in Oracle has gradually evolved from BI Publisher to OBIEE (Oracle Business Intelligence Enterprise Edition) both on premise and cloud visualization and now Oracle Analytics PaaS solution. Leveraging OAC & OADW for Agile Analytics.

Analytics 72

Analytics Cloud Technical Review Data 72

Datavail

AUGUST 2, 2022

Considering a move to cloud analytics? Before you dive in headfirst, however, it’s important to understand what a cloud analytics migration will mean for your IT expenses. What are the Costs of Cloud Analytics? The costs of cloud analytics will vary depending on your technology stack. Analytics compute.

Analytics 52

Analytics Cloud Artificial Inteligence How To 52

Altexsoft

SEPTEMBER 21, 2023

What if we told you that one of the world’s most powerful search and analytics engines started with the humble goal of organizing a culinary enthusiast’s growing list of recipes? First publicly introduced in 2010, Elasticsearch is an advanced, open-source search and analytics engine that also functions as a NoSQL database.

Weak Development Team 52

Weak Development Team Analytics Engineering Development Team Review 52

CIO

SEPTEMBER 26, 2023

Traditional IT monitoring software tells you what is happening via metrics, logs, traces, alerts, etc. Health scores for systems (servers, storage, data protection, hyper-converged appliances, and network) and cloud services that AIOps provides are a giant step beyond traditional monitoring.

Artificial Inteligence 317

Artificial Inteligence Artificial Intelligence Sustainability Systems Administration 317

Openxcell

JUNE 9, 2023

Big Data analytics,on the other hand, refers to using this huge amount of data to make informed business decisions. Let us have a look at Big Data Analytics more in detail. What is Big Data Analytics? This blog explains all about Big Data Analytics, its trends, tools and more.

Big Data 52

Big Data Analytics Tools Data 52

CIO

JULY 18, 2022

A key challenge with organizational alignment is communicating across all departments the goals, metrics, and benefits of a process or function. The recognition of data’s value to a business has led to many metrics and measures focused on data and its quality. Departmental or individual recognition and rewards.

Data 226

Data Metrics Culture Transportation 226

Codegiant

DECEMBER 19, 2023

This design allows for faster query processing and less data storage space, making it ideal for analytics and observability. Here's a breakdown of how this works and why it matters: Columnar Storage In a column-oriented DBMS like ClickHouse, data is stored in columns instead of rows.

Storage 52

Storage Analytics Metrics Scalability 52

Honeycomb

MAY 8, 2024

It relies on telemetry data (such as logs, metrics, traces, profiles, and events) and analysis tools, such as Honeycomb. You’re probably familiar with the most common types already—application logs and system metrics. Often, you’ll hear observability referred to as having three pillars: logs, metrics, and traces.

Metrics 87

Metrics Weak Development Team Analysis Tools 87

CIO

OCTOBER 23, 2023

Circular economy: By 2030, for every metric ton of products a customer buys, one metric ton will be reused or recycled, 100% of Dell packaging will be made from recycled or renewable material, or will utilize reused packaging, and more than half of its product content will be made from recycled, renewable or reduced carbon emissions material.

Sustainability 271

Sustainability Data Center Technical Review Energy 271

Sunflower Lab

MARCH 13, 2024

Core Features of Power BI for Supply Chain Analytics From seamless data connectivity to intuitive visualization capabilities and seamless integration with other Microsoft products, Power BI emerges as a vital asset in optimizing supply chain operations. Here’s an in-depth look at three common types of supply chain dashboards: 1.

Transportation 52

Transportation Weak Development Team Metrics Healthcare 52

CIO

JANUARY 20, 2023

According to a recent IDC whitepaper , leaders saw on average two and a half times better results than other organizations in many business metrics. But Kevin Young, senior data and analytics consultant at consulting firm SPR, says organizations can first share data by creating a data lake like Amazon S3 or Google Cloud Storage.

Data 297

Data Compliance Architecture Technical Review 297

Altexsoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. What is Big Data analytics? Key Big Data characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

CIO

JANUARY 10, 2024

No IT organization wants to get caught short on processing or storage resources that could negatively affect operations, or have to suddenly add resources that exceed the budget. We need hard metrics because we’re running 800 instances of cloud computers. You worry you don’t have enough capacity, so you overprovision,” he says.

Cloud 259

Cloud Technical Review CTO Coach Fractional CTO 259

Xebia

DECEMBER 1, 2022

Grafana is a free and open source platform which allows you to query, visualize, alert on and understand your metrics. The first thing to do is to create the Log Analytics Workspace. One more prerequisite is to provision Storage Account with a share for Grafana to store its data in. Displaying PostgreSQL metrics.

Azure 130

Azure Resources Metrics Analytics 130

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

TechCrunch

SEPTEMBER 13, 2022

I still have storage crates in my kitchen from Webvan, a grocery delivery contender that flamed out so famously, MBA candidates now study it in business school. Use DORA metrics to support the next generation of remote-work models. ” Use DORA metrics to support the next generation of remote-work models.

Strategy 207

Strategy Windows Metrics Study 207

Altexsoft

NOVEMBER 9, 2021

In this article, we’ll explain what procurement analytics is, highlight the main difficulties within the purchasing process, and look at how analytics can address them. What is procurement analytics and the opportunities it offers? Main components of procurement analytics. Procurement and its challenges.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Perficient

DECEMBER 13, 2023

Data Analyses To get insights from such vast and diverse data sets, an appropriate analytical tool is essential. Organized Data Storage AWS S3 (Simple Storage Service) stores the structured, unstructured, or semi-structured data. Various analytical tools like AWS QuickSight connect to Redshift to bring out user insights.

Healthcare 52

Healthcare AWS Lambda Data 52

TechCrunch

MAY 24, 2022

In 2017, Sharp and the two Bitinckas left Splunk to create a platform, Cribl , that creates what Sharp describes as an observability pipeline: a system that can ingest logs and metrics, parse and enrich them, and route them to the appropriate destination. ” Image Credits: Cribl. .”

Tools 212

Tools Survey Metrics Enterprise 212

TechCrunch

JUNE 7, 2022

He and Cheung saw the history of AI reaching an inflection point: Over the previous 10 years, companies invested in AI to keep up with tech trends or help with analytics. Josh Tobin, a former research scientist at OpenAI, observed the trend firsthand while teaching a deep learning course at UC Berkeley in 2019 with Vicki Cheung.

Artificial Inteligence 251

Artificial Inteligence Machine Learning Weak Development Team Data 251

TechCrunch

OCTOBER 7, 2021

The underlying large-scale metrics storage technology they built was eventually open sourced as M3. It will give users more detailed notifications around workflows, with root cause analysis, and it will also give engineers, whether or not they are data science specialists, more tools to run analytics on their data sets.

Cloud 209

Cloud Sport Open Source Machine Learning 209

CIO

JANUARY 4, 2023

It’s a tall order, and one that will hinge on a few factors: Accelerator deployment and management at scale Changes to power and cooling design decisions at very large scale Open-source deployment of high-performance clusters to run simulation, AI, and data analytics workloads What’s New and Growing Among HPC Users? IT Leadership.

Artificial Inteligence 144

Artificial Inteligence Data Center Artificial Intelligence Analytics 144

The Citus Data

DECEMBER 7, 2019

The Windows team measures the quality of new software builds by scrutinizing 20,000 diagnostic metrics based on data flowing in from 800 million Windows devices. Given the importance of Windows for Microsoft’s customers, the RQV analytics dashboard is a critical tool for Windows engineers, program managers, and execs.

Azure 53

Azure Analytics Windows Weak Development Team 53

Perficient

FEBRUARY 22, 2024

Besides data-intensive activities such as data storage management and data transformation, a robust data fabric requires a data virtualization layer as a sole interfacing logical layer that integrates all enterprise data across various source applications. Below is a schematic of how the Oracle semantic model works with its three layers.

Virtualization 52

Virtualization Enterprise Data Analytics 52

CIO

JUNE 9, 2023

Simply put, data management is a sophisticated process involving various stages, such as data storage, processing, analysis, and visualization. Intel is proud to be working with Dell to deliver modern data and analytics solutions that help organizations unlock the untapped value of their data.”

Strategy 251

Strategy Data Transportation Exercises 251

Sunflower Lab

MARCH 21, 2024

Enter the Power BI Purchase Dashboard: a powerful analytics tool allowing organizations real-time insights into their procurement activities, supplier performance, spending habits, and more. Improving Business Growth with Power BI A bicycle manufacturing company aimed to enhance its business operations through data analytics.

Budget 52

Budget Comparison Metrics Analysis 52

CIO

JULY 18, 2022

Access to a rich ISV ecosystem of applications and services can help enterprises unify and extract value from data wherever it resides and throughout its entire life cycle, whether that means delivering secure backup-and-recovery capabilities or serving up analytics capabilities aimed at improving both day-to-day and strategic decision-making.

Data 167

Data Disaster Recovery Backup Systems Review 167

Cloudera

MARCH 22, 2023

While in the old world where questions around data quality or system performance were answered by monitoring a few logs and metrics, in a distributed landscape (like a hybrid data platform) it’s not that straightforward. There are many logs and metrics, and they are all over the place.

Metrics 87

Metrics Government Lambda Systems Administration 87

Altexsoft

APRIL 23, 2019

And these data channels serve as a pair of eyes for executives, supplying them with the analytical information of what is going on with a business and the market. Online analytical processing cubes. Business intelligence and predictive analytics. This type of data processing is also called descriptive analytics.

Business Intelligence 93

Business Intelligence Analytics Tools Strategy 93