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The Role Of Technology In A Changing Financial Services Sector Part II

Cloudera

One of the key takeaways from recent times that should be considered into the future, is that banks need to rethink how they look at tail risk or extreme events that rarely happen. . Machine Learning and AI provide powerful predictive engines that rely on historical data to fit the models.

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Decoding Data Analyst Job Description: Skills, Tools, and Career Paths

FineReport

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. AWS S3: Offers cloud storage for storing and retrieving large datasets.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Because data analysts often build machine learning models, programming and AI knowledge are also valuable. Deep learning algorithms are neural networks modeled after the human brain.

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What Leaders Want: Shifting to AI-Driven Healthcare

DataRobot Blog

Integrating and aligning data across organizations (acute, primary, mental health, social care, and third sector) can be challenging, but is essential to enable forward-looking population health management, strengthen risk stratification, and support the redesign of care pathways.

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Incorporating Artificial Intelligence for Businesses : The Modern Approach to Data Analytics

BizAcuity

85% of AI (marketing) projects fail due to risk, confusion, and lack of upskilling among marketing teams.(Source: Marketers also have access to several AI softwares to save time and optimize their work at every step of the funnel. Content writing, copywriting, video analytics and customer reinvestment, all have AI applications now.

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Four starting points to transform your organization into a data-driven enterprise

IBM Big Data Hub

Furthermore, a global effort to create new data privacy laws, and the increased attention on biases in AI models, has resulted in convoluted business processes for getting data to users. How do business leaders navigate this new data and AI ecosystem and make their company a data-driven organization? Start a trial.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

You can use third-party data products from AWS Marketplace delivered through AWS Data Exchange to gain insights on income, consumption patterns, credit risk scores, and many more dimensions to further refine the customer experience. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics.