Remove Analytics Remove Data Transformation Remove Events Remove Metadata
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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. Using EventBridge integration, filtered positional updates are published to an EventBridge event bus. The ingestion approach is not in scope of this post.

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Deliver decompressed Amazon CloudWatch Logs to Amazon S3 and Splunk using Amazon Data Firehose

AWS Big Data

You can use Amazon Data Firehose to aggregate and deliver log events from your applications and services captured in Amazon CloudWatch Logs to your Amazon Simple Storage Service (Amazon S3) bucket and Splunk destinations, for use cases such as data analytics, security analysis, application troubleshooting etc.

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Enhance your analytics embedding experience with the new Amazon QuickSight JavaScript SDK

AWS Big Data

Additionally, there are major rewrites to deliver developer-focused improvements, including static type checking, enhanced runtime validation, strong consistency in call patterns, and optimized event chaining. is modernized by using promises for all actions, so developers can use async and await functions for better event management.

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What is Data Lineage? Top 5 Benefits of Data Lineage

erwin

An understanding of the data’s origins and history helps answer questions about the origin of data in a Key Performance Indicator (KPI) reports, including: How the report tables and columns are defined in the metadata? Who are the data owners? What are the transformation rules? Data Governance.

Metadata 111
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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes. This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team.

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Cloudera DataFlow Designer: The Key to Agile Data Pipeline Development

Cloudera

Key requirements for building data pipelines Every data pipeline starts with a business requirement. For example, a developer may be asked to tap into the data of a newly acquired application, parsing and transforming it before delivering it to the business’s favorite analytical system where it can be joined with existing data sets.

Testing 84
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Cross-account integration between SaaS platforms using Amazon AppFlow

AWS Big Data

On many occasions, they need to apply business logic to the data received from the source SaaS platform before pushing it to the target SaaS platform. AnyCompany’s marketing team hosted an event at the Anaheim Convention Center, CA. The marketing team created leads based on the event in Adobe Marketo. Let’s take an example.

Sales 72