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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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Data Science, Past & Future

Domino Data Lab

He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. Then we roll out a decade later.

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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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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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Shared Data Reporting: Deep Excel Functionality Meets Web-Based Dashboards

Jet Global

Rich Visualizations Finance teams know the numbers in a report tell a story–but it’s much easier for non-technical viewers to understand when presented via visual elements. As such, a combined solution that offers different ways to interact with the same data might be the best fit for your business.

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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.

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What is The Difference Between BI and Analytics?

Jet Global

BI and analytics are both umbrella terms referring to a type of data insight software. Many providers use them interchangeably, but some use them in conjunction, claiming to offer both business intelligence and business analytics. Think Google Analytics. This of course makes us wonder: what’s the difference?