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Quantitative and Qualitative Data: A Vital Combination

Sisense

Let’s consider the differences between the two, and why they’re both important to the success of data-driven organizations. Digging into quantitative data. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?” The challenge comes when the data becomes huge and fast-changing.

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Amazon Redshift announcements at AWS re:Invent 2023 to enable analytics on all your data

AWS Big Data

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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Your Data Architecture Holds the Key to Unlocking AI’s Full Potential

CIO Business Intelligence

AI working on top of a data lakehouse, can help to quickly correlate passenger and security data, enabling real-time threat analysis and advanced threat detection. In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. Want to learn more?

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Periscope Data Expands to Israel, Empowering Data Teams with Powerful Tools

Sisense

With Itzik’s wisdom fresh in everyone’s minds, Scott Castle, Sisense General Manager, Data Business, shared his view on the role of modern data teams. Scott whisked us through the history of business intelligence from its first definition in 1958 to the current rise of Big Data. Omid Vahdaty, Jutomate.

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What is a Data Pipeline?

Jet Global

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.