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

AWS Big Data

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. Query the data using Athena Athena is a serverless, interactive analytics service built to analyze unstructured, semi-structured, and structured data where it is hosted.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

“Digitizing was our first stake at the table in our data journey,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. For that, he relied on a defensive and offensive metaphor for his data strategy.

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Create a modern data platform using the Data Build Tool (dbt) in the AWS Cloud

AWS Big Data

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

For the downstream consumption by all departments across the organization, smava’s Data Platform team prepares curated data products following the extract, load, and transform (ELT) pattern. The data products from the Business Vault and Data Mart stages are now available for consumers.

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The Rising Need for Data Governance in Healthcare

Alation

Storing the same data in multiple places can lead to: Human error: mistakes when transcribing data reduce its quality and integrity. Multiple data structures: different departments use distinct technologies and data structures. Data governance is the solution to these challenges.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!