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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. Data Warehouse.

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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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Understanding Structured and Unstructured Data

Sisense

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. Structured vs unstructured data.

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Unlocking Data Storage: The Traditional Data Warehouse vs. Cloud Data Warehouse

Sisense

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Data warehouse vs. databases.

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Cloudera Data Warehouse – A Partner Perspective

Cloudera

Among the many reasons that a majority of large enterprises have adopted Cloudera Data Warehouse as their modern analytic platform of choice is the incredible ecosystem of partners that have emerged over recent years. Informatica’s Big Data Manager and Qlik’s acquisition of Podium Data are just 2 examples.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Educating ChatGPT on Data Lakehouse

Cloudera

Hopefully this blog will give ChatGPT an opportunity to learn and correct itself while counting towards my 2023 contribution to social good. The one key component that is missing is a common, shared table format, that can be used by all analytic services accessing the lakehouse data.