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Back to the Financial Regulatory Future

Cloudera

While there are clear reasons SVB collapsed, which can be reviewed here , my purpose in this post isn’t to rehash the past but to present some of the regulatory and compliance challenges financial (and to some degree insurance) institutions face and how data plays a role in mitigating and managing risk. Well, sort of.

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Harmonize data using AWS Glue and AWS Lake Formation FindMatches ML to build a customer 360 view

AWS Big Data

In this post, we look at how we can use AWS Glue and the AWS Lake Formation ML transform FindMatches to harmonize (deduplicate) customer data coming from different sources to get a complete customer profile to be able to provide better customer experience. The following diagram shows our solution architecture.

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Create an Apache Hudi-based near-real-time transactional data lake using AWS DMS, Amazon Kinesis, AWS Glue streaming ETL, and data visualization using Amazon QuickSight

AWS Big Data

Change data capture (CDC) is one of the most common design patterns to capture the changes made in the source database and reflect them to other data stores. a new version of AWS Glue that accelerates data integration workloads in AWS. Then we can query the data with Amazon Athena visualize it in Amazon QuickSight.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

It can be used to reveal structures in data — insurance firms might use cluster analysis to investigate why certain locations are associated with particular insurance claims, for instance. Data analytics and data science are closely related. Generally, the output of data analytics are reports and visualizations.

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AWS Glue Data Quality is Generally Available

AWS Big Data

They have to then review the data statistics to identify data quality rules, and write code to implement these checks in their data pipelines. Data engineers must then write code to monitor data pipelines, visualize quality scores, and alert them when anomalies occur.

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The Impact of Healthcare BI Tools on Decision-Making and Patient Care

FineReport

In addition to security concerns, achieving seamless healthcare data integration and interoperability presents its own set of challenges. The fragmented nature of healthcare systems often results in disparate data sources that hinder efficient decision-making processes.

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Data Modeling 101: OLTP data modeling, design, and normalization for the cloud

erwin

While talking to the business people about the business requirements, entities tend to be the plural nouns that they mention: insureds, beneficiaries, policies, terms, etc. Look again at Figure 7, what is the difference between an insured and a beneficiary? This data duplication can lead to inaccurate data, which no business wants.