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

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 102

Data Generative AI Artificial Inteligence Compliance 102

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 Inteligence 88

Datavail

NOVEMBER 17, 2021

As data volumes continue to grow, the systems and architectures need to evolve. This is especially important for companies that rely on analytics to drive business insights and executive decisions. Most likely, your company has shifted their approach to data and analytics. Recognizing the Need for Change.

Case Study 97

Case Study Analytics Study Architecture 97

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

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

Infinidat

OCTOBER 14, 2021

End-to-end Visibility of Backup and Storage Operations with Integration of InfiniGuard® and Veritas APTARE IT Analytics. The outcome is the integration of Veritas APTARE IT Analytics and the Infinidat InfiniGuard® platform, enabling end-to-end visibility across the data infrastructure. APTARE IT Analytics is multi-faceted.

Backup 96

Backup Storage Analytics Disaster Recovery 96

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

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

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

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 98

Generative AI Technical Review Software Review Systems Review 98

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 103

Generative AI Video Engineering Artificial Inteligence 103

Dell EMC

OCTOBER 14, 2020

As data teams continue to scale their Hadoop and analytics systems, the need increases for flexible compute and storage. To address these issues, many data teams pivot to architectures that allow for independent scaling of compute and storage in both Object and HDFS for Hadoop.

Analytics 109

Analytics Data Storage Architecture 109

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

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

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

O'Reilly Media - Ideas

JANUARY 14, 2025

Interest in Data Lake architectures rose 59%, while the much older Data Warehouse held steady, with a 0.3% In our skill taxonomy, Data Lake includes Data Lakehouse , a data storage architecture that combines features of data lakes and data warehouses.) Usage of material about Software Architecture rose 5.5%

Trends 132

Trends Technology Security Artificial Inteligence 132

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

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 Machine Learning 111

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

Cloudera

SEPTEMBER 24, 2021

One of the most substantial big data workloads over the past fifteen years has been in the domain of telecom network analytics. Advanced predictive analytics technologies were scaling up, and streaming analytics was allowing on-the-fly or data-in-motion analysis that created more options for the data architect.

Analytics 96

Analytics Network Innovation Open Source 96

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 Inteligence 88

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

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 113

Generative AI AWS Groups Artificial Inteligence 113

Cloudera

SEPTEMBER 6, 2022

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Why telco should consider modern data architecture. The challenges.

Telecommunications 84

Telecommunications Architecture Data Government 84

O'Reilly Media - Data

APRIL 3, 2018

Companies continue to use data to improve decision-making (business intelligence and analytics) and for automation (machine learning and AI). This year’s sessions on Data Engineering and Architecture showcases streaming and real-time applications, along with the data platforms used at several leading companies. Privacy and security.

Machine Learning 238

Machine Learning Artificial Inteligence Company Case Study 238

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

Datavail

JULY 27, 2021

Whether you’re a tiny startup or a massive Fortune 500 firm, cloud analytics has become a business best practice. A 2018 survey by MicroStrategy found that 39 percent of organizations are now running their analytics in the cloud, while another 45 percent are using analytics both in the cloud and on-premises.

Azure 98

Azure Analytics Cloud Company 98

CIO

OCTOBER 4, 2022

It’s yet another key piece of evidence showing that there is a tangible return on a data architecture that is cloud-based and modernized – or, as this new research puts it, “coherent.”. Data architecture coherence. The focus on a modern data architecture has never been clearer. more machine learning use casesacross the company.

Machine Learning 178

Machine Learning Artificial Inteligence Data Architecture 178

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 61

Generative AI Artificial Inteligence Metrics AWS 61

AWS Machine Learning - AI

NOVEMBER 19, 2024

Solution overview This section outlines the architecture designed for an email support system using generative AI. The following diagram provides a detailed view of the architecture to enhance email support using generative AI.

Knowledge Base 90

Knowledge Base Generative AI Technical Review AWS 90