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Fundamentals of Apache Spark

Knowledge Hut

It’s also called a Parallel Data processing Engine in a few definitions. Spark is utilized for Big data analytics and related processing. It was open-sourced in 2010 under a BSD license. We collect hundreds of petabytes of data on this platform and use Apache Spark to analyze these enormous amounts of data.

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Top 10 Real World Applications of Cloud Computing

Knowledge Hut

Every day, enormous amounts of data are collected from business endpoints, cloud apps, and the people who engage with them. Cloud computing enables enterprises to access massive amounts of organized and unstructured data in order to extract commercial value.

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The Evolution of Table Formats

Monte Carlo

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

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Data Science Foundations & Learning Path

Knowledge Hut

In the age of big data processing, how to store these terabytes of data surfed over the internet was the key concern of companies until 2010. Now that the issue of storage of big data has been solved successfully by Hadoop and various other frameworks, the concern has shifted to processing these data.

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Big Data vs. Crowdsourcing Ventures - Revolutionizing Business Processes

ProjectPro

Generally, a data scientist spends 78% of his time in preparing the data for big data analytics. For example, before the analysis the crowd can tell whether the data points are a Tweet or updates from Facebook and whether it carries a negative, positive or neutral connotation.

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5 Big Data Use Cases- How Companies Use Big Data

ProjectPro

How Nike uses Big Data- Top sports brand Nike leverages big data analytics to develop ecological designs for its products, including a dye technique that requires no water. According to IDC, the amount of data will increase by 20 times - between 2010 and 2020, with 77% of the data relevant to organizations being unstructured.

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. Unstructured data sources.