Tag: datasets

Feed: R-bloggers. Author: R on Just be-cause. [This article was first published on R on Just be-cause, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. We’ve seen on a previous post that one of the main differences between classic ML and Causal Inference is the additional step of using the correct adjustment set for the predictor features. In order to find the correct adjustment set we need a DAG that represents the relationships ... Read More

Feed: AWS Big Data Blog. Many AWS customers use a multi-account strategy. A centralized AWS Glue Data Catalog is important to minimize the amount of administration related to sharing metadata across different accounts. This post introduces capability that allows Amazon Athena to query a centralized Data Catalog across different AWS accounts.Overview of solution In late 2019, AWS introduced the ability to Connect Amazon Athena to your Apache Hive Metastore. Using this functionality, you can also configure Athena to point to a Data Catalog in a different account. The Hive Metastore functionality uses an AWS Lambda function to federate queries to ... Read More

Feed: Planet MySQL; Author: Bernd Ocklin; The MySQL NDB Cluster team works on fundamental redesigns of core parts of NDB architecture. One of these changes is the partial checkpoint algorithm. You can now take full advantage of it when building much larger clusters: NDB 8.0 can use 16 TB data memory per data node for in-memory tables. 3-replica 5 PB clusters can be build with disk data. The new partial checkpoint algorithm executes restarts up to 4x faster, reduces checkpoint times by a factor of 6x in typical set-ups and minimizes cluster’s disk space consumption. In addition the new checkpoints ... Read More

Feed: R-bloggers. Author: R Views. [This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. One hundred fifty-two packages made it to CRAN in December. Here are my “Top 40” picks in ten categories: Data, Genomics, Machine Learning, Mathematics, Medicine, Science, Statistics, Time Series, Utilities, and Visualization. Data climate v0.3.0: Provides access to meteorological and hydrological data from OGIMET, University of Wyoming – atmospheric vertical profiling data, ... Read More

Feed: R-bloggers. Author: John. Statisticians often come across outliers when working with datasets and it is important to deal with them because of how significantly they can distort a statistical model. Your dataset may havevalues that are distinguishably different from most other values, these arereferred to as outliers. Usually, an outlier is an anomaly that occurs due tomeasurement errors but in other cases, it can occur because the experimentbeing observed experiences momentary but drastic turbulence. In either case, itis important to deal with outliers because they can adversely impact theaccuracy of your results, especially in regression models. In this tutorial, ... Read More

Feed: Cambridge Intelligence. Author: Dan Williams. In this final post in our three-parter exploring the typical challenges you face when visualizing your graph data for the first time, we look at the ‘starburst’ – a pattern where one heavily connected node dominates the chart.Usual suspect #3: it’s hard to see past a starburstWhere do starbursts come from?In previous posts, we saw how the underlying data source plays a significant role in determining whether you see a chart dominated by snowstorms or hairballs. But in both those cases, the main focus was on visualizing a dataset in its entirety.When working with ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: pearl-chen; If you’re at a multinational company, running your data operations across various clouds and geographies can be a time-consuming, complicated process. Cloud Pak for Data, our leading data and AI platform, partners with Cockroach to solve multicloud and compliance challenges so organizations can scale their data strategies across the globe.CockroachDB is a relational database for next generation, cloud-native applications. Named for the most resilient species on earth, CockroachDB delivers a durable, consistent, distributed SQL transactional database at scale. Said VP of business development Eric Goldstein: “We've built the ... Read More

Feed: Actian. Author: Jack Mardack. It feels like only yesterday that “Machine Learning” and “Artificial Intelligence” were equated with science fiction by most regular folks outside of tech. As a movie-going culture, we have a long history of associating these concepts with self-aware robots or rogue computer programs that could escape the laboratories where they were created and threaten all humanity. But in 2020, ML and AI have been considerably demystified. And yet, even if it seems less likely now that the Singularity will be triggered by the reckless ambition of some tech startup, consumers have new reasons to be concerned. Yes, ML and AI are going mainstream, and it’s not just disruption-minded startups that are leveraging these technologies. Enterprises in a wide range of established industries are finding solid business reasons ... Read More

Feed: AWS Partner Network (APN) Blog. Author: AWS Admin. By Matt Yellen, Principal Engineer at CloudZeroAnalyzing large datasets can be challenging, especially if you aren’t thinking about certain characteristics of the data and what you’re ultimately looking to achieve. There are a number of factors organizations need to consider in order to build systems that are flexible, affordable, and fast, while at the same time meeting the needs of their end users. For example, you need to understand where your data is coming from, how often it changes, and how the data will be queried. In some cases, a fixed ... Read More

Feed: Recent Announcements. AWS Glue now supports three new transforms - Purge, Transition, Merge - that can help you extend your extract, transform, and load (ETL) logic in Apache Spark applications. You can use the Purge transform to remove files, partitions or tables, and quickly refine your datasets on S3 ... Read More