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How to modernize data lakes with a data lakehouse architecture

IBM Big Data Hub

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

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What is a Data Pipeline?

Jet Global

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

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How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads

AWS Big Data

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. Additionally, data is extracted from vendor APIs that includes data related to product, marketing, and customer experience.

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7 key Microsoft Azure analytics services (plus one extra)

CIO Business Intelligence

The recent announcement of the Microsoft Intelligent Data Platform makes that more obvious, though analytics is only one part of that new brand. Azure Data Factory. Azure Data Lake Analytics. Data warehouses are designed for questions you already know you want to ask about your data, again and again.

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Lay the groundwork now for advanced analytics and AI

CIO Business Intelligence

Model, understand, and transform the data Comcast faced the challenge of collecting large amounts of information about potential security and reliability issues but with no easy way to make sense of it all, says Noopur Davis, corporate EVP, CISO, and chief product privacy officer.

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Cloudera’s Open Data Lakehouse Supercharged with dbt Core(tm)

Cloudera

Using these adapters, Cloudera customers can use dbt to collaborate, test, deploy, and document their data transformation and analytic pipelines on CDP Public Cloud, CDP One, and CDP Private Cloud. The Open Data Lakehouse . This variety can result in a lack of standardization, leading to data duplication and inconsistency.

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Connecting the Data Lifecycle

Cloudera

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. . The firm also worked on creating a solid pipeline from the data warehouse to the data lake.