Tag: datasets

Feed: R-bloggers. Author: Ryan Sheehy. Here is the course link. Course Description This course will help you take your data visualization skills beyond the basics and hone them into a powerful member of your data science toolkit. Over the lessons we will use two interesting open datasets to cover different types of data (proportions, point-data, single distributions, and multiple distributions) and discuss the pros and cons of the most common visualizations. In addition, we will cover some less common alternatives visualizations for the data types and how to tweak default ggplot settings to most efficiently and effectively get your message ... Read More

Feed: Neo4j Graph Database Platform. Author: Jocelyn Hoppa. We use Neo4j to design our next-generation Power chips, said Chuck Calio, Offering Manager IBM PowerAI at IBM.The future of graph technology is in AI, but it’s not the only use case. From designing hardware (naturally a graph) to dynamic pricing, IBM’s Chuck Calio sees use cases for graphs as myriad and the demand from customers strong.In this week’s five-minute interview (conducted at GraphTour San Francisco) we discuss how IBM designs next generation chips using Neo4j – and the way those chips accelerate graph algorithms. Tell us about how you use Neo4j ... Read More

Feed: R-bloggers. Author: Kristian Larsen. Categories Data Management Tags Databases Import Data R Programming Tips & Tricks In this article, you learn how to connect R with Excel by importing and exporting data between the two programs. Excel: pros and cons Excel is still very popular among companies and organizations. One of the main advantages in a spreadsheet is ease of providing the user with a rapid overview of a dataset, using visualizations and tables. On the other hand, given the incredible growth of data, the spreadsheet really lacks efficient and agile solutions for data management and data cleaning. Solution: ... Read More

Feed: Neo4j Graph Database Platform. Author: Jocelyn Hoppa. Until recently, adopting graph analytics required significant expertise and determination, since tools and integrations were difficult and few knew how to apply graph algorithms to their quandaries and business challenges. It is our goal to help change this.We are writing this blog series to help organizations better leverage graph analytics so they make new discoveries and develop intelligent solutions faster.While there are other graph algorithm libraries and solutions, this series focuses on the graph algorithms in the Neo4j platform. However, you’ll find these blogs helpful for understanding more general graph concepts regardless ... Read More

Feed: R-bloggers. Author: Stefan Gouyet. The Professional Footballers’ Association (PFA) Team of the Year is released in England at the end of each season, picking the 11 most influential players in each of Britain’s leagues. The Team of the Year award was launched in the 1973-1974 season, meaning there was 44 years worth of data to web scrape. Using Wikipedia’s PFA Team of the Year pages (filtered by decade) and the rvest package, I was left with a dataframe of 484 soccer players (44 years * 11 players per/year). Here are some visualizations I thought were cool: Liverpool, Arsenal, and (most significantly) ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: karan-sachdeva; The business that gets there first won’t necessarily win digital and AI game. It will be the one that ingrains digital and AI in its business as much as possible. Starting from applying intelligent data science where it matters most and progressively using it in every aspect of the business. In the modern banking environment, consumers are well informed. They expect intuitive, engaging and informative experiences when they bank. Banks need solutions that can help them delight their customers with personalized experiences, empower their workforce to provide differentiated ... Read More

Feed: What's New. Amazon Web Services is Hiring. Amazon Web Services (AWS) is a dynamic, growing business unit within Amazon.com. We are currently hiring Software Development Engineers, Product Managers, Account Managers, Solutions Architects, Support Engineers, System Engineers, Designers and more. Visit our careers page to learn more. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation ... Read More

Feed: Microsoft Power BI Blog | Microsoft Power BI. Author: . Possibly the biggest scalability feature (literally) in the history of Microsoft BI is actually here! The Power BI Desktop feature summary announced aggregations built on composite models is now supported in the Power BI service. It works on both shared (Pro) and Premium capacity. Here is a summary of reasons to use aggregations: Query performance over big data - as users interact with visuals on Power BI reports, DAX queries are submitted to the Power BI dataset. Boost query speeds by caching data at the aggregated level, using a ... Read More

Feed: R-bloggers. Author: David Robinson. I recently came up with the idea for a series of screencasts: I've thought about recording a screencast of an example data analysis in #rstats. I'd do it on a dataset I'm unfamiliar with so that I can show and narrate my live thought process. Any suggestions for interesting datasets to use? — David Robinson (@drob) October 6, 2018 Hadley Wickham had the great suggestion of analyzing a Tidy Tuesday dataset. Tidy Tuesday is a fantastic project run by the R for Data Science online learning community (especially Thomas Mock) that releases an interesting dataset ... Read More

Feed: AWS Big Data Blog. A data lake provides a centralized repository that you can use to store all your structured and unstructured data at any scale. A data lake can include both raw datasets and curated, query-optimized datasets. Raw datasets can be quickly ingested, in their original form, without having to force-fit them into a predefined schema. Using data lakes, you can run different types of analytics on both raw and curated datasets. By using Amazon S3 as the storage layer of your data lakes, you can have a set of rich controls at both the bucket and object ... Read More