[unable to retrieve full-text content]We discuss 3Vs of Big Data; Infonomics and many aspects of monetizing information including promising analytics methods, successful companies, main challenges; Information marketplaces and why data ownership concept is misguided, and more.
Original Post: Exclusive Interview: Doug Laney on Big Data and Infonomics
[unable to retrieve full-text content]Curious about the future of Big Data and AI? Here’s what the trends have it in 2018 for innovations.
Original Post: Four Big Data Trends for 2018
[unable to retrieve full-text content]DSTI mission is simple: training executive students to become ready-to-go Data Scientists and Big Data Analysts. Check our small private online course programme.
Original Post: Online MSc in Applied Data Science, Big Data – part-time, small, private
The SparklyR package from RStudio provides a high-level interface to Spark from R. This means you can create R objects that point to data frames stored in the Spark cluster and apply some familiar R paradigms (like dplyr) to the data, all the while leveraging Spark’s distributed architecture without having to worry about memory limitations in R. You can also access the distributed machine-learning algorithms included in Spark directly from R functions. If you don’t happen to have a cluster of Spark-enabled machines set up in a nearby well-ventilated closet, you can easily set one up in your favorite cloud service. For Azure, one option is to launch a Spark cluster in HDInsight, which also includes the extensions of Microsoft ML Server. While this service recently had a significant price reduction, it’s still more expensive than running a “vanilla” Spark-and-R…
Original Post: A simple way to set up a SparklyR cluster on Azure
[unable to retrieve full-text content]Check out these introductory data videos from noted expert and influencer Ronald van Loon.
Original Post: Introductory Data Concepts: Fantastic Video Tutorials from Ronald van Loon
[unable to retrieve full-text content]Interactive visualization of large datasets on the web has traditionally been impractical. Apache Arrow provides a new way to exchange and visualize data at unprecedented speed and scale.
Original Post: Supercharging Visualization with Apache Arrow
[unable to retrieve full-text content]Nonprofits can use analytics to boost their fundraising efforts, measure and monitor the impact of their activities, build predictive models, optimize allocation of funds, and more
Original Post: How Nonprofits Can Benefit from the Power of Data Science
[unable to retrieve full-text content]It’s really hard to find predictions about the future made in the 1950’s. I decided to review the most popular sci-fi movies from 1950’s, and provide my perspective as to what these movies might tell us about 2018.
Original Post: Back to the Future: 2018 Big Data and Data Science Prognostications
[unable to retrieve full-text content]An overview of the installation and implementation of simple techniques for working with large datasets in your machine.
Original Post: Simple Ways Of Working With Medium To Big Data Locally
[unable to retrieve full-text content]Cutting-edge science and new business fundamentals intersect and merge at Strata Data Conference. Win KDnuggets Pass – submit your entry by Jan 3, 2018.
Original Post: Win KDnuggets Free Pass to Strata Data Conference San Jose, Mar 5-8, 2018