Remove 2019 Remove Data Lake Remove Data Warehouse Remove Visualization
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Data Science News from Microsoft Ignite 2019

Data Science 101

Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. Visual Studio Online. Here they are in my order of importance (based upon my opinion).

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Three Trends for Modernizing Analytics and Data Warehousing in 2019

Cloudera

Natural language analytics and streaming data analytics are emerging technologies that will impact the market. The most common big data use case is data warehouse optimization. Big data architecture is used to augment different applications, operating alongside or in a discrete fashion with a data warehouse.

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Happy Birthday, CDP Public Cloud

Cloudera

On September 24, 2019, Cloudera launched CDP Public Cloud (CDP-PC) as the first step in delivering the industry’s first Enterprise Data Cloud. CDP Machine Learning: a kubernetes-based service that allows data scientists to deploy collaborative workspaces with secure, self-service access to enterprise data. That Was Then.

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Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways. One of the downsides of the role that data now plays in the modern business world is that users can be overloaded with jargon and tech-speak, which can be overwhelming.

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Enrich your customer data with geospatial insights using Amazon Redshift, AWS Data Exchange, and Amazon QuickSight

AWS Big Data

Load generic address data to Amazon Redshift Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Redshift Serverless makes it straightforward to run analytics workloads of any size without having to manage data warehouse infrastructure.

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Acquisitions on the Horizon in BI and Data Analytics Industry?

Sisense

2019 can best be described as an era of modern cloud data analytics. Convergence in an industry like data analytics can take many forms. Two orthogonal approaches to data analytics have developed in this decade of BI: 1. The allure of operationalizing BI in-data is its perceived simplicity.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. in lieu of simply landing in a data lake.