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Automate deployment of an Amazon QuickSight analysis connecting to an Amazon Redshift data warehouse with an AWS CloudFormation template

AWS Big Data

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

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How Macmillan Publishers authored success using IBM Cognos Analytics

IBM Big Data Hub

Macmillan Publishers is a global publishing company and one of the “Big Five” English language publishers. They published many perennial favorites including Kristin Hannah’s The Nightingale , Bill Martin’s Brown Bear, Brown Bear, what do you see?

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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

Our call for speakers for Strata NY 2019 solicited contributions on the themes of data science and ML; data engineering and architecture; streaming and the Internet of Things (IoT); business analytics and data visualization; and automation, security, and data privacy. 719, trailing "data warehouse."

IoT 20
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Data Science, Past & Future

Domino Data Lab

The data governance, however, is still pretty much over on the data warehouse. Toward the end of the 2000s is when you first started getting teams and industry, as Josh Willis was showing really brilliantly last night, you first started getting some teams identified as “data science” teams.

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Enable Multi-AZ deployments for your Amazon Redshift data warehouse

AWS Big Data

Originally published on December 9th, 2022. Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Amazon Redshift is a cloud-based data warehouse that supports many recovery capabilities to address unforeseen outages and minimize downtime.

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Unlock The Power of Your Data With These 19 Big Data & Data Analytics Books

datapine

Due to this book being published recently, there are not any written reviews available. 4) Big Data: Principles and Best Practices Of Scalable Real-Time Data Systems by Nathan Marz and James Warren. Best for: the seasoned BI professional who is ready to think deep and hard about important issues in data analytics and big data.

Big Data 263
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What is a Data Pipeline?

Jet Global

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.