- Industry 2021 Predictions for AI, Analytics, Data Science, Machine Learning - Dec 16, 2020.
We bring you industry predictions from 12 innovative companies - what key trends they expect in 2021 in AI, Analytics, Data Science, and Machine Learning?
- Data Science Volunteering: Ways to Help - Dec 11, 2020.
No matter the field in which you hold some expertise, sharing your skills to benefit the lives of others or supporting non-profit organizations that try to make the world a better place is a noble and time-worthy personal pursuit. Many opportunities exist in data science to contribute to meaningful projects and crucial needs from your local community to a global scale.
- Outbreak Analytics: Data Science Strategies for a Novel Problem - Apr 30, 2020.
You walk down one aisle of the grocery store to get your favorite cereal. On the dairy aisle, someone sick from COVID-19 coughs. Did your decision to grab your cereal before your milk possibly keep you healthy? How can these unpredictable, near-random choices be included in complex models?
- Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms - Feb 24, 2020.
The Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms has the largest number of leaders ever. We examine the leaders and changes and trends vs previous years.
- Industry AI, Analytics, Machine Learning, Data Science Predictions for 2020 - Dec 16, 2019.
Predictions for 2020 from a dozen innovative companies in AI, Analytics, Machine Learning, Data Science, and Data industry.
- Gainers, Losers, and Trends in Gartner 2019 Magic Quadrant for Data Science and Machine Learning Platforms - Feb 11, 2019.
We compare Gartner 2019 MQ for Data Science, Machine Learning Platforms to its previous versions and identify notable changes for leaders and challengers, including RapidMiner, KNIME, TIBCO, Alteryx, Dataiku, SAS, and MathWorks.
- AI and ML Day in Australia with Alteryx, Tableau, Amazon, Snowflake, Commonwealth Bank, and IAPA - Aug 8, 2018.
Key information regarding The Alteryx Analytics Revolution Summit roadshow in Australia, including dates, guest speakers, livestream information and how you can register for the roadshow closest to you.
- Unlock the Next Era of Analytics – AI and Machine Learning at Scale - Apr 12, 2018.
Join us on Apr 19 for an interactive virtual event to hear from a panel of analytic experts as they dispel the myths and dive into the nitty-gritty of how AI and machine learning will impact analytic teams.
- Build a Foundation that Supports AI and Machine Learning - Apr 6, 2018.
In an upcoming livestream on April 19, we’ll dig into how to build a foundation that supports AI and Machine Learning with industry experts and uncover what many companies are going through.
- Gainers and Losers in Gartner 2018 Magic Quadrant for Data Science and Machine Learning Platforms - Feb 27, 2018.
We compare Gartner 2018 Magic Quadrant for Data Science, Machine Learning Platforms vs its 2017 version and identify notable changes for leaders and challengers, including IBM, SAS, RapidMiner, KNIME, Alteryx, H2O.ai, and Domino.
- Data Science vs Addiction: Estimating Opioid Abuse by Location - Jan 26, 2018.
Data science can help find the optimal locations for drug treatment facilities, even in the face of major data challenges.
- CRN Big Data Business Analytics Companies - May 12, 2015.
Data, Analytics, and Intelligence play a key role in CRN Big Data 100 in 2015. New additions include predictive analytics firms Knime, Logi Analytics, Looker, Luminoso, Predixion, RapidMiner, and Salesforce.
- Forrester Wave(tm) Big Data Predictive Analytics 2015: Gainers and Losers - Apr 3, 2015.
IBM, SAS, and SAP lead in Forrester Wave(tm) Big Data Predictive Analytics Solutions for Q2, 2015. We compare with a previous Forrester Wave for 2013 and examine gainers and losers.
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- Gartner 2015 Magic Quadrant for Advanced Analytics Platforms: who gained and who lost - Feb 23, 2015.
SAS, IBM, KNIME, and RapidMiner lead in Gartner 2015 Magic Quadrant for Advanced Analytics Platforms. We analyze who gained and who lost versus last year.
- October 2014 Analytics, Big Data, Data Mining Acquisitions and Startups Activity - Nov 8, 2014.
October 2014 acquisitions, startups, and company activity in Analytics, Big Data, Data Mining, and Data Science: DrivenData, Map-D, Microsoft buys Equivio, Alteryx, Cazena, Ello, Zoomdata, Cloudera buys DataPad, Tibco goes private.
- Top KDnuggets tweets, Oct 29-30: If you can’t code, you can’t be a data scientist; 13 Machine Learning Books - Oct 31, 2014.
The #strataconf debate: If You Can't Code, You Can't Be a Data Scientist; 13 Machine Learning Books recommended by Berkeley machine learning expert; Data Blending for Dummies - free ebook from Alteryx; Data Science 2.0, upcoming book from Vincent Granville.
- Top KDnuggets tweets, Jul 23-24: 81% of retail firms gather #BigData, only 34% use analytics - Jul 25, 2014.
81% of retail firms gather #BigData, only 34% use analytics to drive pricing optimization; Google Brain project: Google is not really a search company. The Journal of Big Data has published its first articles - Hadoop, Mahout, Data; MLlib; Apache Spark component for machine learning.
- Top KDnuggets tweets, Jun 30 – Jul 1: Is “Data Scientist” more than “Data Analyst”? Good list of 41 Big Data Influencers - Jul 2, 2014.
Is "Data Scientist" more than "Data Analyst"? ; 41 Big Data Influencers - Journalists, Public Sector, Industry, Academia; Alteryx and Databricks to lead development of Apache SparkR ; Top data mining researcher @Jure Leskovec lecture on Webgraph structure.
- Top stories for May 4-10 - May 11, 2014.
Data Scientists Not Required with Alteryx Analytics 9.0; 9 Free Books for Learning Data Mining and Data Analysis; Exclusive Interview: Todd Holloway, Data Science Lead, Trulia; Did Target really predict teen pregnancy?
- Data Scientists Not Required: Promises the recently launched Alteryx Analytics 9.0 - May 4, 2014.
Alteryx Analytics 9.0 blends new sources of customer Insight such as Social Media, Google Analytics, and Marketo with data from legacy environments such as SAS Analytics.