Remove Data Integration Remove Data Lake Remove Insurance
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Salesforce debuts Zero Copy Partner Network to ease data integration

CIO Business Intelligence

For instance, a Data Cloud-triggered flow could update an account manager in Slack when shipments in an external data lake are marked as delayed. Sharing Customer 360 insights back without data replication. With zero-copy support, the insurance company wouldn’t have to load that weather data into their platform.

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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. Apache Hudi connector for AWS Glue For this post, we use AWS Glue 4.0,

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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 111
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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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Don’t Fear Artificial Intelligence; Embrace it Through Data Governance

CIO Business Intelligence

This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Further, data management activities don’t end once the AI model has been developed. Addressing the Challenge.

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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.

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AWS Glue Data Quality is Generally Available

AWS Big Data

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. DeeQu is optimized to run data quality rules in minimal passes that makes it efficient.