Historically, developers independently implemented error handling, observability, and security within each application or microservice to ensure the success of inbound and outbound…
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Cloud & Infrastructure
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View allEnterprise Readiness of Cloud MLOps: A GigaOm Benchmark Report
MLOps is a practice for collaboration between data science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of machine learning…
Read MoreKey Criteria for Evaluating Intelligent Virtual Assistants
Intelligent virtual assistant (IVA) technology has transformed automated telephone response systems, such as those typically used in call centers for the first…
Read MoreSQL Transaction Processing and Analytic Performance Price-Performance Testing
The fundamental underpinning of an organization is its transactions. They must be done well, with integrity and performance. Not only has transaction…
Read MoreGigaOm Radar for Data Science Platforms: Cloud Providers, Data Platform Vendors, and Enterprise Incumbents
This Radar report will help enterprise buyers become familiar with data science platforms and vendor offerings. Most enterprise organizations now work with…
Read MoreGigaOm Radar for Data Science Platforms: Pure-Play Specialist and Startup Vendors
This Radar report will help enterprise buyers become familiar with data science platforms and vendor offerings. Enterprise customers manage massive amounts of…
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Ransomware: Why It’s Time to Think of it as a Data Management Problem
Over the last couple of years, ransomware has taken center stage in data protection, but very few people realize it is only…
Read MoreGigaOm Radar for Streaming Data Platforms: Streaming Data Specialist Vendors
This Radar report will help enterprise buyers become familiar with streaming data platforms and vendor offerings. The vendors reviewed in this Radar…
Read MoreGigaOm Radar for Streaming Data Platforms: Cloud Providers, Enterprise Incumbents, and Data Platform Vendors
This Radar report will help enterprise buyers become familiar with streaming data platforms and vendor offerings. The vendors reviewed in this Radar…
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Healthcare Natural Language Processing
Growing data volumes and differences in terminology, language, abbreviations, and even spelling in clinical documents make it challenging for medical professionals to…
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View allGigaOm Radar for Industrial IoT Security
The convergence of operational technology (OT) and information technology (IT) brings benefits and risks. Industrial plants and systems are designed for long…
Read MoreKey Criteria for Evaluating Identity as a Service Solutions
User access management, or identity and access management (IAM), is a critical part of enterprise IT. It has long allowed organizations to…
Read MoreGigaOm Radar for Zero-Trust Network Access (ZTNA)
Virtual private networks (VPNs) have long been the default method of securing remote access. VPNs provided a way to prevent exposing internal…
Read MoreGigaOm Radar for Extended Detection and Response (XDR) Solutions
Enterprise cybersecurity is typically composed of multiple security solutions from various vendors combined with a security information and event management (SIEM) and/or…
Read MoreKey Criteria for Evaluating XDR Solutions
Enterprise cybersecurity is typically composed of multiple solutions from various vendors, combined with a security information and event management (SIEM) and/or security…
Read MoreGigaOm Radar for E-Signature Solutions
As industries adopt hybrid operating models, e-signature solutions have become a critical tool for supporting traditional business functions. The e-signature market has…
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Ransomware: Why It’s Time to Think of it as a Data Management Problem
Over the last couple of years, ransomware has taken center stage in data protection, but very few people realize it is only…
Read MoreGigaOm Radar for Intelligent Fraud Detection in Financial Transactions
The use of artificial intelligence (AI)—typically in some form of machine learning (ML) designed for anomaly detection—is the norm today across the…
Read MoreKey Criteria for Evaluating Intelligent Fraud Detection in Financial Transactions
The banking and financial services industry—and any large organization processing payments—faces a challenge with fraudulent activity. The move of many businesses to…
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