Remove Marketing Remove Optimization Remove Predictive Analytics Remove Unstructured Data
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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

The Basel, Switzerland-based company, which operates in more than 100 countries, has petabytes of data, including highly structured customer data, data about treatments and lab requests, operational data, and a massive, growing volume of unstructured data, particularly imaging data.

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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

The global AI market is projected to grow to USD 190 billion by 2025, increasing at a compound annual growth rate (CAGR) of 36.62% from 2022, according to Markets and Markets. Real-time data analytics helps in quick decision-making, while advanced forecasting algorithms predict product demand across diverse locations.

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The most valuable AI use cases for business

IBM Big Data Hub

Not only will this help scale the AOT tech across markets, but it will also help tackle integrations including additional languages, dialects and menu variations. Clean up with predictive maintenance AI can be used for predictive maintenance by analyzing data directly from machinery to identify problems and flag required maintenance.

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Get Ready For These Six 2020 Business Intelligence Trends

Smart Data Collective

Some of these new tools use AI to predict events more accurately by employing predictive analytics to identify subtle relationships between even seemingly unrelated variables. Predictive analytics is the use of data and AI-powered algorithms to help analysts forecast the future and better predict business outcomes.

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

Companies surely need data scientists to help them empower their analytics processes, build a numbers-based strategy that will boost their bottom line, and ensure that enormous amounts of data are translated into actionable insights. But being an inquisitive Sherlock Holmes of data is no easy task.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

And, as industrial, business, domestic, and personal Internet of Things devices become increasingly intelligent, they communicate with each other and share data to help calibrate performance and maximize efficiency. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company. Digging into quantitative data.