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The Best Embedded BI Tools For 2024

FineReport

In summary, embedded analytics refers to actionable intelligence seamlessly integrated into customer-facing products, applications, or services. Limited Interactivity Even after overcoming logistical and analytical hurdles to deploy embedded dashboards, the challenges persist. What Are the Main Benefits of Embedded BI Tools?

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

AWS Big Data

We introduce you to Amazon Managed Service for Apache Flink Studio and get started querying streaming data interactively using Amazon Kinesis Data Streams. Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources.

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How healthcare organizations can analyze and create insights using price transparency data

AWS Big Data

Under the Transparency in Coverage (TCR) rule , hospitals and payors to publish their pricing data in a machine-readable format. For more information, refer to Delivering Consumer-friendly Healthcare Transparency in Coverage On AWS. Then you can use Amazon Athena V3 to query the tables in the Data Catalog.

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BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard. Additionally, it manages table definitions in the AWS Glue Data Catalog , containing references to data sources and targets of extract, transform, and load (ETL) jobs in AWS Glue.

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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

Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. But first, let’s define what data quality actually is. What is the definition of data quality? Why Do You Need Data Quality Management? date, month, and year).

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Introducing Cloudera DataFlow Designer: Self-service, No-Code Dataflow Design

Cloudera

Developers need to onboard new data sources, chain multiple data transformation steps together, and explore data as it travels through the flow. A reimagined visual editor to boost developer productivity and enable self service. Figure 5: Parameter references in the configuration panel and auto-complete.

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What is Data Mapping?

Jet Global

Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation. Data mapping is important for several reasons.