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What is a data scientist? A key data analytics role and a lucrative career

CIO Business Intelligence

Data scientists are often engaged in long-term research and prediction, while data analysts seek to support business leaders in making tactical decisions through reporting and ad hoc queries aimed at describing the current state of reality for their organizations based on present and historical data.

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Accelerating scope 3 emissions accounting: LLMs to the rescue

IBM Big Data Hub

Some companies attempt to estimate Scope 3 emissions by collecting data from suppliers and manually categorizing data, but progress is hindered by challenges such as large supplier base, depth of supply chains, complex data collection processes and substantial resource requirements.

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Digital listening reveals 3 leading innovation drivers

CIO Business Intelligence

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. Big Data collection at scale is increasing across industries, presenting opportunities for companies to develop AI models and leverage insights from that data.

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Unintentional data

The Unofficial Google Data Science Blog

Implicitly, there was a prior belief about some interesting causal mechanism or an underlying hypothesis motivating the collection of the data. As computing and storage have made data collection cheaper and easier, we now gather data without this underlying motivation.

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Five Key Elements For A Big Analytics Driven Business Impact

Occam's Razor

In a world when your work will never be done, how do you assess that the core things necessary are present? What guarantees that agility and innovation are present in your analytics practice? My answer was: " Look for these two elements, if they are present then it is worth helping the company with free consulting and analysis.

Analytics 141
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Product Management for AI

Domino Data Lab

Pete Skomoroch presented “ Product Management for AI ” at Rev. Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. Session Summary.

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Backtesting index rebalancing arbitrage with Amazon EMR and Apache Iceberg

AWS Big Data

If a match is not found between the existing dataset and the new dataset, the new data will be inserted as new records in the table and status code will be set to ‘new’ for these records. Similarly, if the existing dataset has stocks that are not present in the new dataset, those records will remain expired with a status code of ‘expired’.