#HYPE CYCLE 2022 HOW TO#

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. 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.ĥ. 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.Ĥ. 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.ģ.

#HYPE CYCLE 2022 HOW TO#

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.AI TRiSM, which explains how to protect AI model governance, trustworthiness, fairness, reliability, robustness, efficacy and data protection.AI Engineering, which reviews the streamlining of operationalizing AI-based systems by unifying DataOps, MLOps and DevOps pipelines - for implementing AI best practices.Data-Centric AI, which discusses how AI solutions enrich and enhance training data, through solutions like feature stores and others.In this AI Hype Cycle, Iguazio is mentioned in the following categories: 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. The Hype Cycle for Artificial Intelligence, 2022 evaluates the use of AI innovations for real business utility and high impact. Adaptive ML, which reviews how to conduct online retraining of ML models so they can quickly adapt to real-world requirements.Ģ.

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.

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.

In this DSML Hype Cycle, Iguazio is mentioned in the following categories: 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. 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.

These hype cycles are a great tool for enterprises considering their AI methodology and evaluating vendors. We are delighted to have been mentioned alongside global industry leaders like AWS, IBM, Microsoft, Google, Databricks and Dataiku. 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.

The Hype Cycle for CRM Sales Technology.The Hype Cycle for Customer Experience Analytics.Hype Cycle for Healthcare Data, Analytics and AI.The Hype Cycle for Infrastructure Strategy.Hype Cycle for Analytics and Business Intelligence.The Hype Cycle for Artificial Intelligence.The Hype Cycle for Data Science and Machine Learning.We’re so proud to share that Iguazio has been named a sample vendor in eight Gartner Hype Cycles in 2022:

Hype cycle 2022