Remove Big Data Remove Data Lake Remove Insurance
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Outdated business apps can cloud your AI vision

CIO Business Intelligence

Customer concerns about old apps At Ensono, Klingbeil runs a customer advisory board, with CIOs from the banking and insurance industries well represented. Banking and insurance are two industries still steeped in the use of mainframes, and Ensono manages mainframes for several customers. We are in mid-transition, Stone says.

Insurance 108
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Simplify operational data processing in data lakes using AWS Glue and Apache Hudi

AWS Big Data

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

Data Lake 111
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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

Data analytics on operational data at near-real time is becoming a common need. Due to the exponential growth of data volume, it has become common practice to replace read replicas with data lakes to have better scalability and performance. For more information, see Changing the default settings for your data lake.

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Read and write S3 Iceberg table using AWS Glue Iceberg Rest Catalog from Open Source Apache Spark

AWS Big Data

In today’s data-driven world , organizations are constantly seeking efficient ways to process and analyze vast amounts of information across data lakes and warehouses. This post will showcase how this data can also be queried by other data teams using Amazon Athena. Verify that you have Python version 3.7

Data Lake 116
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Access Amazon Redshift data from Salesforce Data Cloud with Zero Copy Data Federation

AWS Big Data

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

Data Lake 122
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Handle UPSERT data operations using open-source Delta Lake and AWS Glue

AWS Big Data

Many customers need an ACID transaction (atomic, consistent, isolated, durable) data lake that can log change data capture (CDC) from operational data sources. There is also demand for merging real-time data into batch data. Delta Lake framework provides these two capabilities.

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

AWS Big Data

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. The following diagram shows our solution architecture.