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Sisu Optimizes Analytics with Machine Learning for Actions & Decisions

David Menninger's Analyst Perspectives

Sisu Data is an analytics platform for structured data that uses machine learning and statistical analysis to automatically monitor changes in data sets and surface explanations. It can prioritize facts based on their impact and provide a detailed, interpretable context to refine and support conclusions.

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Sisu Optimizes Analytics with Machine Language for Actions & Decisions

David Menninger's Analyst Perspectives

Sisu Data is an analytics platform for structured data that uses machine learning and statistical analysis to automatically monitor changes in data sets and surface explanations. It can prioritize facts based on their impact and provide a detailed, interpretable context to refine and support conclusions.

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Managing machine learning in the enterprise: Lessons from banking and health care

O'Reilly on Data

As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. Machine learning developers are beginning to look at an even broader set of risk factors. Sources of model risk.

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Have we reached the end of ‘too expensive’ for enterprise software?

CIO Business Intelligence

Before LLMs and diffusion models, organizations had to invest a significant amount of time, effort, and resources into developing custom machine-learning models to solve difficult problems. In many cases, this eliminates the need for specialized teams, extensive data labeling, and complex machine-learning pipelines.

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AI Product Management After Deployment

O'Reilly on Data

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”. objective functions, major changes to hyperparameters, etc.)

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

Invest in AI-powered quality tooling AI and machine learning are transforming data quality from profiling and anomaly detection to automated enrichment and impact tracing. Use machine learning models to detect schema drift, anomalies and duplication patterns and provide real-time recommended resolutions.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

That’s why it is of utmost importance to start with utilizing the right key performance indicators – there are numerous KPI examples that can make or break the quality process of data management. This data certainly gives the industry more room to develop with technologies such as machine learning and artificial intelligence.