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How Ruparupa gained updated insights with an Amazon S3 data lake, AWS Glue, Apache Hudi, and Amazon QuickSight

AWS Big Data

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

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How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

A solid ramp in initial interest puts a new medicine on a trajectory to meet its lifetime sales targets. During the product launch, everyone in the sales and marketing organizations is hyper-focused on business development. Marketing invests heavily in multi-level campaigns, primarily driven by data analytics.

Analytics 246
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Amazon Redshift announcements at AWS re:Invent 2023 to enable analytics on all your data

AWS Big Data

These announcements drive forward the AWS Zero-ETL vision to unify all your data, enabling you to better maximize the value of your data with comprehensive analytics and ML capabilities, and innovate faster with secure data collaboration within and across organizations.

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How Can Manufacturing Data Help Your Organization?

Sisense

From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. And cloud data warehouses or data lakes give companies the capability to store these vast quantities of data. Data improves and streamlines production quality control.

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CIOs rise to the ESG reporting challenge

CIO Business Intelligence

CIOs — who sign nearly half of all net-zero services deals with top providers, according to Everest Group analyst Meenakshi Narayanan — are uniquely positioned to spearhead data-enabled transformation for ESG reporting given their data-driven track records.

Reporting 110
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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?” Qualitative data benefits: Unlocking understanding.

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The Gartner 2021 Leadership Vision for Data & Analytics Leaders Webinar Q&A

Andrew White

Does Data warehouse as a software tool will play role in future of Data & Analytics strategy? You cannot get away from a formalized delivery capability focused on regular, scheduled, structured and reasonably governed data. Data lakes don’t offer this nor should they. E.g. Data Lakes in Azure – as SaaS.