CIO

APRIL 9, 2025

The networking, compute, and storage needs not to mention power and cooling are significant, and market pressures require the assembly to happen quickly. AI and analytics integration. Organizations can enable powerful analytics and AI capabilities by linking VMware-hosted data with services such as BigQuery and Vertex AI.

Google Cloud 133

Google Cloud Load Balancer Virtualization Artificial Intelligence 133

CIO

NOVEMBER 14, 2024

“Our digital transformation has coincided with the strengthening of the B2C online sales activity and, from an architectural point of view, with a strong migration to the cloud,” says Vibram global DTC director Alessandro Pacetti. In this case, IT works hand in hand with internal analytics experts.

Cloud 179

Cloud Technical Review Data B2C 179

TechCrunch

JUNE 1, 2022

Essentially, Coralogix allows DevOps and other engineering teams a way to observe and analyze data streams before they get indexed and/or sent to storage, giving them more flexibility to query the data in different ways and glean more insights faster (and more cheaply because doing this pre-indexing results in less latency).

Analytics 246

Analytics DevOps Storage Business Intelligence 246

CIO

AUGUST 9, 2022

Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. What is a data engineer? Data engineer job description.

Data Engineering 197

Data Engineering Analytics Engineering Data 197

CIO

AUGUST 9, 2023

In generative AI, data is the fuel, storage is the fuel tank and compute is the engine. All this data means that organizations adopting generative AI face a potential, last-mile bottleneck, and that is storage. Novel approaches to storage are needed because generative AI’s requirements are vastly different.

Generative AI 148

Generative AI Storage Scalability Technical Review 148

CIO

SEPTEMBER 14, 2023

Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. What is a data engineer?

Data Engineering 203

Data Engineering Analytics Engineering Data 203

CIO

JUNE 23, 2023

As the general manager of the Oakland Athletics, Beane used data and analytics to find undervalued baseball players on a shoestring budget. Artificial intelligence (AI) is the analytics vehicle that extracts data’s tremendous value and translates it into actionable, usable insights.

Storage 148

Storage Data Artificial Intelligence Artificial Inteligence 148

CIO

APRIL 9, 2025

Cloud-based workloads can burst as needed, because IT can easily add more compute and storage capacity on-demand to handle spikes in usage, such as during tax season for an accounting firm or on Black Friday for an e-commerce site. Theres no downtime, and all networking and dependencies are retained. Enhancing applications.

Cloud 88

Cloud Google Cloud Disaster Recovery Data Center 88

CIO

APRIL 9, 2025

VCF is a comprehensive platform that integrates VMwares compute, storage, and network virtualization capabilities with its management and application infrastructure capabilities. TB raw data storage ( ~2.7X TB raw data storage. TB raw data storage, and v22-mega-so with 51.2 TB raw data storage.

Google Cloud 88

Google Cloud Cloud Engineering Storage 88

CIO

AUGUST 3, 2023

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices. After moving its expensive, on-premise data lake to the cloud, Comcast created a three-tiered architecture.

Analytics 148

Analytics CTO Games Generative AI 148

OTS Solutions

DECEMBER 4, 2023

Private cloud architecture is an increasingly popular approach to cloud computing that offers organizations greater control, security, and customization over their cloud infrastructure. What is Private Cloud Architecture? Why is Private Cloud Architecture important for Businesses?

Architecture 130

Architecture Cloud Disaster Recovery Scalability 130

CIO

APRIL 1, 2025

Using Zero Trust Architecture (ZTA), we rely on continuous authentication, least privilege access, and micro-segmentation to limit data exposure. He also stands by DLP protocol, which monitors and restricts unauthorized data transfers, and prevents accidental exposure via email, cloud storage, or USB devices.

Data 88

Data Authentication Compliance Artificial Intelligence 88

AWS Machine Learning - AI

MARCH 20, 2025

Use cases for Amazon Bedrock Data Automation Key use cases such as intelligent document processing , media asset analysis and monetization , speech analytics , search and discovery, and agent-driven operations highlight how Amazon Bedrock Data Automation enhances innovation, efficiency, and data-driven decision-making across industries.

Data 96

Data Generative AI Artificial Inteligence Compliance 96

Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI. It is a critical feature for delivering unified access to data in distributed, multi-engine architectures.

Data 84

Data Analytics Systems Review Architecture 84

CIO

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Artificial Inteligence 178

Artificial Inteligence Data Artificial Intelligence Analytics 178

Altexsoft

AUGUST 12, 2020

A door automatically opens, a coffee machine starts grounding beans to make a perfect cup of espresso while you receive analytical reports based on fresh data from sensors miles away. This article describes IoT through its architecture, layer to layer. The standardized architectural model proposed by IoT industry leaders.

IoT 140

IoT Architecture Wireless Transportation 140

Perficient

NOVEMBER 17, 2024

No single platform architecture can satisfy all the needs and use cases of large complex enterprises, so SAP partnered with a small handful of companies to enhance and enlarge the scope of their offering. Semantic Modeling Retaining relationships, hierarchies, and KPIs for analytics. What is SAP Datasphere? What is Databricks?

Artificial Inteligence 59

Artificial Inteligence Machine Learning Architecture Analytics 59

TechCrunch

SEPTEMBER 27, 2021

As more enterprises migrate to cloud-based architectures, they are also taking on more applications (because they can) and, as a result of that, more complex workloads and storage needs. Firebolt raises $127M more for its new approach to cheaper and more efficient Big Data analytics.

Artificial Inteligence 246

Artificial Inteligence Applications Cloud Artificial Intelligence 246

Cloudera

AUGUST 17, 2022

What if you could access all your data and execute all your analytics in one workflow, quickly with only a small IT team? CDP One is a new service from Cloudera that is the first data lakehouse SaaS offering with cloud compute, cloud storage, machine learning (ML), streaming analytics, and enterprise grade security built-in.

Analytics 116

Analytics Artificial Inteligence Machine Learning Policies 116

Honeycomb

NOVEMBER 19, 2024

You probably use some subset (or superset) of tools including APM, RUM, unstructured logs, structured logs, infra metrics, tracing tools, profiling tools, product analytics, marketing analytics, dashboards, SLO tools, and more. Observability 1.0 Three big reasons the rise of observability 2.0

Software Review 133

Software Review Weak Development Team Metrics Technical Review 133

CIO

SEPTEMBER 10, 2024

It added that enterprises will also have the capability to connect enterprise data in their Oracle Database to applications running on Amazon Elastic Compute Cloud (Amazon EC2), AWS Analytics services, or AWS’s advanced AI and machine learning (ML) services, including Amazon Bedrock.

AWS 218

AWS Azure Database Administration Google Cloud 218

CIO

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data 199

Data Data Engineering Database Administration Artificial Inteligence 199

AWS Machine Learning - AI

MARCH 4, 2025

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. The solution incorporates the following key features: Using a Retrieval Augmented Generation (RAG) architecture, the system generates a context-aware detailed assessment.

Generative AI 91

Generative AI Technical Review Software Review Systems Review 91

AWS Machine Learning - AI

OCTOBER 29, 2024

These insights are stored in a central repository, unlocking the ability for analytics teams to have a single view of interactions and use the data to formulate better sales and support strategies. Organizations typically can’t predict their call patterns, so the solution relies on AWS serverless services to scale during busy times.

Generative AI 96

Generative AI Video Engineering Artificial Inteligence 96

Cloudera

NOVEMBER 7, 2023

Are you struggling to manage the ever-increasing volume and variety of data in today’s constantly evolving landscape of modern data architectures? One of these two layouts should be used for all new storage needs. Most traditional analytics applications like Hive, Spark, Impala, YARN etc.

Storage 105

Storage System Architecture Analytics 105

TechCrunch

DECEMBER 14, 2021

This is where Carto comes along with a product specialized on spatial analytics. Carto provides connectors with databases (PostgreSQL, MySQL or Microsoft SQL Server), cloud storage services (Dropbox, Box or Google Drive) or data warehouses (Amazon Redshift, Google BigQuery or Snowflake). Carto can ingest data from multiple sources.

Data 234

Data Telecommunications Transportation Analysis 234

Perficient

MARCH 31, 2025

However, enabling external users to access raw data while maintaining security and lineage integrity requires a well-thought-out architecture. This blog outlines a reference architecture to achieve this balance. Recommended Architecture 1. Allow external users to access raw data without compromising governance.

Data 52

Data Architecture Government Policies 52

Cloudera

MAY 9, 2024

The Gartner Data and Analytics Summit in London is quickly approaching on May 13 th to 15 th , and the Cloudera team is ready to hit the show floor! As far as data storage and processing resources go, there’s cloud, and then there’s your data center.

Analytics 102

Analytics Data Data Center Course 102

AWS Machine Learning - AI

MARCH 20, 2025

Therefore, it was valuable to provide Asure a post-call analytics pipeline capable of providing beneficial insights, thereby enhancing the overall customer support experience and driving business growth. This is powered by the web app portion of the architecture diagram (provided in the next section).

Generative AI 68

Generative AI Artificial Inteligence Metrics AWS 68

Cloudera

AUGUST 3, 2021

Advanced analytics empower risk reduction . Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. . Improve Visibility within Supply Chains.

Analytics 111

Analytics Open Source Government Artificial Inteligence 111

TechCrunch

OCTOBER 18, 2022

In the stream processing paradigm, app logic, analytics and queries exist continuously, and data flows through them continuously. Wu makes that case that only companies with deep pockets and data analytics expertise can adopt existing stream processing solutions, due to the complexity and high cost of ownership.

Cloud 207

Cloud Data Systems Review AWS 207

CIO

AUGUST 19, 2024

The shift toward a dynamic, bidirectional, and actively managed grid marks a significant departure from traditional grid architecture. This transformation is fueled by several factors, including the surging demand for electric vehicles (EVs) and the exponential growth of renewable energy and battery storage.

Energy 183

Energy Load Balancer Systems Review Technical Review 183

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 Artificial Inteligence 209

Cloudera

SEPTEMBER 15, 2022

It was designed as a native object store to provide extreme scale, performance, and reliability to handle multiple analytics workloads using either S3 API or the traditional Hadoop API. There are also newer AI/ML applications that need data storage, optimized for unstructured data using developer friendly paradigms like Python Boto API.

Storage 87

Storage System Artificial Inteligence Big Data 87

AWS Machine Learning - AI

NOVEMBER 15, 2024

Additional integrations with services like Amazon Data Firehose , AWS Glue , and Amazon Athena allowed for historical reporting, user activity analytics, and sentiment trends over time through Amazon QuickSight. The following diagram illustrates the Principal generative AI chatbot architecture with AWS services.

Generative AI 111

Generative AI AWS Groups Artificial Inteligence 111

CIO

JULY 18, 2024

This limits both time and cost while increasing productivity, allowing employees to make stronger analytical decisions. However, enterprises with integration solutions that coexist with native IT architecture have scalable data capture and synchronization abilities. These issues add up and lead to unreliability.

Cloud 167

Cloud Data Storage eBook 167

CIO

APRIL 1, 2025

Data processing costs: Track storage, retrieval and preprocessing costs. This involves leveraging advanced techniques such as predictive analytics for cost forecasting, automation of cost management processes and continuous refinement of financial strategies to identify and eliminate inefficiencies.

Technical Review 88

Technical Review Azure Budget Artificial Intelligence 88