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Doing Business in a Big Data World

Strategy Driven

The Internet and cloud computing have revolutionized the nature of data capture and storage, tempting many companies to adopt a new 'Big Data' philosophy: collect all the data you can; all the time. Big Data is Not Just More Data : That’s because the nature of the data we can now collect has changed.

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Big Data in Healthcare: Sources and Real-World Applications

Altexsoft

In this article, we will explain the concept and usage of Big Data in the healthcare industry and talk about its sources, applications, and implementation challenges. What is Big Data and its sources in healthcare? So, what is Big Data, and what actually makes it Big? Let’s see where it can come from.

Big Data 116
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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

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The role of self-service BI for business agility

Capgemini

For self-service BI to succeed, however, the entire data value chain may need to be fixed. Data has to be easy to find, understand, access, and use for everyone in the chain: data engineers, analysts, data scientists, and business users. Prior, he was responsible for Informatica’s Intelligent Data Platform.

Agile 52
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Top Data science books you should definitely read

Apiumhub

Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by by EMC Education Services. The whole data analytics lifecycle is explained in detail along with case study and appealing visuals so that you can see the practical working of the entire system.

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The Good and the Bad of Hadoop Big Data Framework

Altexsoft

The biggest star of the Big Data world, Hadoop was named after a yellow stuffed elephant that belonged to the 2-year son of computer scientist Doug Cutting. Source: The Wall Street Journal. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics.

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Predictive analytics helps Fresenius anticipate dialysis complications

CIO

Our primary challenge was in our ability to scale the real-time data engineering, inferences, and real-time monitoring to meet service-level agreements during peak loads (6K messages per second, 19MBps with 60K concurrent lambda invocations per second) and throughout the day (processing more than 500 million messages daily, 24/7).”