We’re so proud to share that Iguazio has been named a sample vendor in eight Gartner Hype Cycles in 2022:
- The Hype Cycle for Data Science and Machine Learning
- The Hype Cycle for Artificial Intelligence
- Hype Cycle for Analytics and Business Intelligence
- The Hype Cycle for Infrastructure Strategy
- The Hype Cycle for ITSM
- Hype Cycle for Healthcare Data, Analytics and AI
- The Hype Cycle for Customer Experience Analytics
- The Hype Cycle for CRM Sales Technology
Iguazio was mentioned in the following categories: MLOps, Logical Feature Store, Adaptive ML, Data-Centric AI, AI Engineering, AI TRiSM, Operational AI Systems, ModelOps, AI Engineering in HCLS and Continuous Intelligence.
We are delighted to have been mentioned alongside global industry leaders like AWS, IBM, Microsoft, Google, Databricks and Dataiku.
These hype cycles are a great tool for enterprises considering their AI methodology and evaluating vendors. Here are some details on each report:
1. The Hype Cycle for Data Science and Machine Learning, 2022 analyzes the maturity of the DSML landscape and how it is evolving to meet the requirements of the enterprise while delivering business value. According to the DSML Hype Cycle, innovation and novel techniques are being used by data and analytics leaders to find solutions to challenges and to stay ahead of the pack.
In this DSML Hype Cycle, Iguazio is mentioned in the following categories:
- MLOps, which discusses the streamlining of the end-to-end development, testing, validation, deployment, operationalization and instantiation of ML models; and how MLOps is standardizing the process to drive ML value.
- Logical Feature Store, which explains how feature stores enable reusability, reproducibility and reliability of features for ML; for breaking down silos and accelerating feature engineering.
- Adaptive ML, which reviews how to conduct online retraining of ML models so they can quickly adapt to real-world requirements.
2. The Hype Cycle for Artificial Intelligence, 2022 evaluates the use of AI innovations for real business utility and high impact. The AI Hype Cycle identifies the need to commoditize and operationalize AI for adding intelligence to applications, devices and productivity tools, and analyzes the impact on the business, as well as on people and processes.
In this AI Hype Cycle, Iguazio is mentioned in the following categories:
- Data-Centric AI, which discusses how AI solutions enrich and enhance training data, through solutions like feature stores and others.
- AI Engineering, which reviews the streamlining of operationalizing AI-based systems by unifying DataOps, MLOps and DevOps pipelines - for implementing AI best practices.
- AI TRiSM, which explains how to protect AI model governance, trustworthiness, fairness, reliability, robustness, efficacy and data protection.
- Operational AI Systems, which discusses how to orchestrate, automate and scale production-read and enterprise-grade AI pipelines - for accelerating production of AI, removing friction, scaling and reusing AI components.
- ModelOps, which focuses on end-to-end governance and lifecycle management of analytics, AI and decision models; to help organizations move from the lab to production.
3. The Hype Cycle for Analytics and Business Intelligence, 2022 reviews the maturity of innovations across the analytics and business intelligence space; while demonstrating how analytics tools automate tasks and data science tools democratize accessibility.
4. The Hype Cycle for Infrastructure Strategy, 2022 analyzes how I&O leaders can drive innovation in platform strategies, while taking into account new consumption models, skills, automation and sustainability; and while also optimizing costs.
5. The Hype Cycle for ITSM, 2022 examines existing and new technologies that help drive innovation in IT service management; to make them more nimble and business-aligned. I&O leaders are encouraged to use the HypeCycle to build out their roadmap.
6. The Hype Cycle for Healthcare Data, Analytics and AI, 2022 tracks new technologies that have an impact on data and analytics initiatives in life science, payer and provider sectors, so data leaders can make strategic planning decisions that will positively impact healthcare organizations.
In this hype cycle, Iguazio was mentioned in the AI Engineering in HCLS category.
7. The Hype Cycle for Customer Experience Analytics, 2022 assesses how data, analytics and AI, as well as data trends and sources, is driving customer experience analytics adoption. The report examines how digitalization efforts help mature technologies, while data privacy and ethics programs remain important considerations.
8. The Hype Cycle for CRM Sales Technology, 2022 analyzes sales technologies and how they can improve buyer experience and empower sellers. The report covers the need to use technologies that increase innovation as well as those that enable resilience.
Iguazio’s Contribution to the Machine Learning, MLOps and AI Spaces
Iguazio provides innovative ML orchestration and pipeline automation technologies and a strong data engineering infrastructure. Together, the Iguazio platform allows enterprises and organizations to streamline and manage their AI from the lab to production, in a simplified, scalable and automated manner. This operationalization of ML pipelines orchestrates and accelerates model training, deployment and management, while cutting down on friction between data scientists, data engineers and DevOps, and reducing operational costs.
Iguazio’s unique online and offline feature store supports feature reusability and scale, and is fully integrated with the model serving and monitoring capabilities of the Iguazio platform. Unlike other feature stores on the market, the Iguazio feature store serves as a robust data transformation service, alongside additional platform features like the real-time serving pipeline, monitoring and retraining capabilities and CI/CD for ML. The result is a powerful platform that abstracts away the complexities of AI/ML and empowers organizations to generate business value across multiple use cases.
Three examples of this are our work with Ecolab, LATAM Airlines and S&P Global. Ecolab accelerated the rollout of new AI services by 12X using Iguazio on Microsoft Azure. LATAM Airlines deployed more than 40 AI services across commercial and operational departments, to create business value and to plan for the post-pandemic future. S&P Global deploys semantic extraction with NLP on engineering documents to drive better decision making, processing thousands of PDF files in parallel and in real time, and orchestrates dependencies with AI. We have many more success stories from customers across verticals.
Prior to these 2022 Hype Cycles, Iguazio was also mentioned by Garter in the following reports:
- The 2022 Market Guide for DSML Engineering Platforms
- Seven Gartner Hype Cycles in 2021
- The 2021 Market Guide for AI Trust, Risk and Security Management
- The 2021 Magic Quadrant for Data Science and ML Platforms (honorable mention)
- Five Gartner Hype Cycles in 2020
- The 2020 Magic Quadrant for Data Science and ML Platforms (honorable mention)
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.