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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. It served many enterprise use cases across API feeds, content mastering, and analytics interfaces.

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Rapidminer Platform Supports Entire Data Science Lifecycle

David Menninger's Analyst Perspectives

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. Rapidminer Studio is its visual workflow designer for the creation of predictive models.

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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

Businesses are constantly evolving, and data leaders are challenged every day to meet new requirements. For many enterprises and large organizations, it is not feasible to have one processing engine or tool to deal with the various business requirements. This post is co-written with Andries Engelbrecht and Scott Teal from Snowflake.

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Unify your data: AI and Analytics in an Open Lakehouse

Cloudera

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

Jet Global

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.