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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

The market for data warehouses is booming. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes.

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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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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. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

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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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Top Considerations for Building an Open Cloud Data Lake

Data fuels the modern enterprise — today more than ever, businesses compete on their ability to turn big data into essential business insights. Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data.

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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. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

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Complexity Drives Costs: A Look Inside BYOD and Azure Data Lakes

Jet Global

Ostensibly, the new product represents Microsoft’s transition to a newer, more cloud-friendly ERP for midsized enterprises. OLAP reporting has traditionally relied on a data warehouse. OLAP reporting based on a data warehouse model is a well-proven solution for companies with robust reporting requirements.