Remove Data Processing Remove Data Warehouse Remove Technology
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How Will The Cloud Impact Data Warehousing Technologies?

Smart Data Collective

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. Big data and data warehousing.

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The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

This approach is repeatable, minimizes dependence on manual controls, harnesses technology and AI for data management and integrates seamlessly into the digital product development process. They must also select the data processing frameworks such as Spark, Beam or SQL-based processing and choose tools for ML.

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Accelerate Offloading to Cloudera Data Warehouse (CDW) with Procedural SQL Support

Cloudera

Did you know Cloudera customers, such as SMG and Geisinger , offloaded their legacy DW environment to Cloudera Data Warehouse (CDW) to take advantage of CDW’s modern architecture and best-in-class performance? The Data Warehouse on Cloudera Data Platform provides easy to use self-service and advanced analytics use cases at scale.

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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

AWS Big Data

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis.

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Migrate a petabyte-scale data warehouse from Actian Vectorwise to Amazon Redshift

AWS Big Data

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. The system had an integration with legacy backend services that were all hosted on premises. The downside here is over-provisioning.

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The DataOps Vendor Landscape, 2021

DataKitchen

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix.

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Introduction To The Basic Business Intelligence Concepts

datapine

Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. The data warehouse. 1) The raw data.