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1. Augmented Analytics
Edge Analytics
Explainable AI (XAI)
Data Privacy and Ethics
Automated Machine
Learning (AutoML)
Augmented analytics is set to revolutionize
the data analytics process. It combines
machine learning and AI to automate data
preparation, insight generation, and sharing.
This enables data analysts to focus on
strategic decision-making while the system
handles the technical aspects.
While AI and machine learning
are powerful, understanding
their decisions has been
challenging. Explainable AI aims
to make AI systems more
transparent and interpretable.
This trend will be crucial,
especially in sectors where
accountability and compliance
are paramount, like finance and
healthcare..
With the proliferation of IoT devices,
data is increasingly generated at the
edge, close to where it is needed. Edge
analytics processes data locally,
reducing latency and enabling real-time
decision-making. In 2023, expect to see
wider adoption of edge analytics in
various industries, from manufacturing
to healthcare.
AutoML platforms are
democratizing machine learning by
automating complex tasks. They
allow individuals with limited ML
expertise to build and deploy
machine learning models. In 2023,
we anticipate an expansion of
AutoML tools, making AI more
accessible.
As data collection grows, so do concerns
about privacy and ethics. Regulations
like GDPR and CCPA are pushing
organizations to prioritize data ethics. In
2023, expect a heightened focus on
responsible data handling and
transparent data practices.