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Book of the Month: Data Models for Banking, Finance, and Insurance

Dataversity

This time, well be going over Data Models for Banking, Finance, and Insurance by Claire L. This book arms the reader with a set of best practices and data models to help implement solutions in the banking, finance, and insurance industries. Welcome to the first Book of the Month for 2025.This

Banking 130
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Python for Business: Optimize Pre-Processing Data for Decision-Making

Smart Data Collective

For example, the Impute library package handles the imputation of missing values, MinMaxScaler scales datasets, or uses Autumunge to prepare table data for machine learning algorithms. Besides, Python allows creating data models, systematizing data sets, and developing web services for proficient data processing.

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Benefits of Using Data Analytics in Equipment Financing

Smart Data Collective

Most banks will offer fantastic rates for this type of loan, but many have additional qualification requirements. This will help you realize why you need to use big data to get the financing that you are looking for. This is yet another benefit of using big data. Again, if the business is new, this advantage can be vital.

Finance 320
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Data Science Journey Walkthrough – From Beginner to Expert

Smart Data Collective

Since the field covers such a vast array of services, data scientists can find a ton of great opportunities in their field. Data scientists use algorithms for creating data models. These data models predict outcomes of new data. Data science is one of the highest-paid jobs of the 21st century.

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Data Model Development Using Jinja

Sisense

Every aspect of analytics is powered by a data model. A data model presents a “single source of truth” that all analytics queries are based on, from internal reports and insights embedded into applications to the data underlying AI algorithms and much more. Data modeling organizes and transforms data.

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How to Leverage Machine Learning for AML Compliance

BizAcuity

This may include combining variables, creating new variables based on existing ones, and scaling the data. Model Selection: A good model selection is one of the most critical steps in predictive analytics. The process involves selecting and creating attributes that are relevant for the specific problem.

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How to Leverage Machine Learning for AML Compliance

BizAcuity

This may include combining variables, creating new variables based on existing ones, and scaling the data. Model Selection: A good model selection is one of the most critical steps in predictive analytics. The process involves selecting and creating attributes that are relevant for the specific problem.