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Modernizing Data Architectures

Data Virtualization

Recently, we have seen the rise of new technologies like big data, the Internet of things (IoT), and data lakes. But we have not seen many developments in the way that data gets delivered. Modernizing the data infrastructure is the.

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Waking Up The World of Big Data

Sisense

The term “Big Data” has lost its relevance. The fact remains, though: every dataset is becoming a Big Data set, whether its owners and users know (and understand) that or not. Big Data isn’t just something that happens to other people or giant companies like Google and Amazon. Big Data Today.

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Otis takes the smart elevator to new heights

CIO Business Intelligence

Otis One’s cloud-native platform is built on Microsoft Azure and taps into a Snowflake data lake. IoT sensors send elevator data to the cloud platform, where analytics are applied to support business operations, including reporting, data visualization, and predictive modeling. based company’s elevators smarter.

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Keys to Ensure that Data isn’t Slowing Down your Innovation Efforts

Cloudera

The hard part is to turn aspiration into reality by creating an organization that is truly data-driven. technologies. For those models to produce meaningful outcomes, organizations need a well-defined data lifecycle management process that addresses the complexities of capturing, analyzing, and acting on data.

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Big Data for Business: A Requirement for Today’s Business Analytics

David Menninger's Analyst Perspectives

Organizations now must store, process and use data of significantly greater volume and variety than in the past.

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A Few 2016 Technology Predictions

In(tegrate) the Clouds

I enjoy the end of the year technology predictions, even though it’s hard to argue with this tweet from Merv Adrian: By 2016, 99% of readers will be utterly sick of predictions. 2016 will be the year of the data lake. I can’t help it. Merv Adrian (@merv) December 19, 2015. platform.twitter.com/widgets.js.

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Join a streaming data source with CDC data for real-time serverless data analytics using AWS Glue, AWS DMS, and Amazon DynamoDB

AWS Big Data

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Recently, data lakes have gained lot of traction to become the foundation for analytical solutions, because they come with benefits such as scalability, fault tolerance, and support for structured, semi-structured, and unstructured datasets.