Apache SparkThe University of California, Berkeley’s AMP Lab, developed Apache in 2009. Apache Spark is a fast large-scale data processing engine and executes applications in Hadoop clusters 100 times faster in memory and 10 times faster on disk. Spark is built on data science and its concept makes data science effortless. Spark is also popular for data pipelines and machine learning models development. Spark also includes a library – MLlib, that provides a progressive set of machine algorithms for repetitive data science techniques like Classification, Regression, Collaborative Filtering, Clustering, etc.
Explore Data & Analytics Statistics
- 36 percent of investment professionals use web scraping to derive data.
- Content analytics usage among IT professionals increased from 43 percent to 54 percent between January 2018 and January 2019.
- Analytics leaders are nearly twice as likely as others to report enacting a long-term strategy to respond to changes in core business practices.
- More than 30 percent of businesses say big data and analytics have fundamentally changed business practices in their research and development departments
- By 2025, the amount of the global datasphere subject to data analysis will grow by a factor of 50 to 5.2 zettabytes.
- Customer/social analysis is considered the second most important big data analytics use case, followed by predictive maintenance.
- 45 percent of companies run at least some big data workloads in the cloud.
- 62 percent of retail businesses see competitive advantages from information and analytics.
- In 2025, the IoT data analyzed and used to change business processes will be as much as all of the data created in 2020.
- Through 2019, 90% of large organizations will have hired a CDO, but only 50% will be considered a success.
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