Remove Data Transformation Remove Events Remove Publishing
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SQL Streambuilder Data Transformations

Cloudera

As an essential part of ETL, as data is being consolidated, we will notice that data from different sources are structured in different formats. It might be required to enhance, sanitize, and prepare data so that data is fit for consumption by the SQL engine. What is a data transformation?

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Plug-and-play integration : A seamless, plug-and-play integration between data producers and consumers should facilitate rapid use of new data sets and enable quick proof of concepts, such as in the data science teams. As part of the required data, CHE data is shared using Amazon DataZone.

IoT 111
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How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes

AWS Big Data

For instance, Domain A will have the flexibility to create data products that can be published to the divisional catalog, while also maintaining the autonomy to develop data products that are exclusively accessible to teams within the domain. Consumer feedback and demand drives creation and maintenance of the data product.

Metadata 105
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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

Developers can use the support in Amazon Location Service for publishing device position updates to Amazon EventBridge to build a near-real-time data pipeline that stores locations of tracked assets in Amazon Simple Storage Service (Amazon S3). In this model, the Lambda function is invoked for each incoming event.

Analytics 122
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Biggest Trends in Data Visualization Taking Shape in 2022

Smart Data Collective

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. Data virtualization is ideal in any situation where the is necessary: Information coming from diverse data sources.

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How Open Universities Australia modernized their data platform and significantly reduced their ETL costs with AWS Cloud Development Kit and AWS Step Functions

AWS Big Data

We used the AWS Step Function state machines to define, orchestrate, and execute our data pipelines. Amazon EventBridge We used Amazon EventBridge, the serverless event bus service, to define the event-based rules and schedules that would trigger our AWS Step Functions state machines.

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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.