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Creator of First-Ever Live Data Management Platform Now Allows Teams to Collect, Transport, and Analyze Data Seamlessly Across Multiple-Vendor Cloud Infrastructures from AWS, Google, Microsoft, and More MOUNTAIN VIEW, CALIF. (PRWEB)Â NOVEMBER 29, 2016 Treasure Data, providers of the first Live Data Management platform to make all data connected, current, and easily accessible, today announced the g
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Blog From RFP to Revenue Growth: A Fortune 1000 Companyâs First Year with a CDP Discover SCIâs journey with a customer data platform to reduce friction along the customer journey while creating more personalized digital experiences. Filter by Topic Filter by Topic AI & Machine Learning CDP CDP Use Cases Company News Customer Data Strategy Customer Service Data Privacy & Security Marketing Partners
2. WHO AM I ? ⢠Toru Takahashi (@nora96o) ⢠Treasure Data, Inc. ⢠Support Engineering Manager ⢠ã¡ã¼ã«ã«ãã£ããã«ãããã°æ¸ããããã³ã¼ããæ¸ãããã ⢠http://qiita.com/toru-takahashi ⢠æ°ã¥ãã¨ã社ä¼äººï¼å¹´ç®ã«çªå ¥ã»ã»ã» 2 3. 質åã§ãï¼ â¢ Treasure Data ã ç¥ã£ã¦ããäººã¯ ï¼ â¢ Fluentd ã ç¥ã£ã¦ããäººã¯ ï¼ â¢ Embulkãç¥ã£ã¦ãã人ã¯ï¼ ⢠Digdagãèãããã¨ããã人ã¯ï¼ ⢠ã¤ã³ãã© / åæåºç¤ ãæ®æ®µããéç¨ãéçºããã¦ãã人ã¯ï¼ ⢠iOS / Android / Unity / ããã³ãã¨ã³ãã®äººã¯ï¼ 3
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Digdag ã Apache License 2.0 ã®å ã§ãªã¼ãã³ã½ã¼ã¹åããã¾ãããï¼ ãã試ããã â¦ï¼ ä»ããã«ã§ãï¼ https://t.co/Uzc4a5GLCe ããã¥ã¡ã³ãï¼https://t.co/PF8wy5KHln â Sadayuki Furuhashi (@frsyuki) 2016å¹´6æ15æ¥ ã¨ãã訳ã§è©¦ãã¦ã¿ã¾ããã注ç®åº¦ã®é«ãã£ãã¯ã¼ã¯ããã¼ã¨ã³ã¸ã³ãDigdagããã¤ãã«OSSåããã¾ããï¼Githubãªãã¸ããªåã³ããã¥ã¡ã³ãã¯ä»¥ä¸ã¨ãªãã¾ãã treasure-data/digdag: Workload Automation System Getting started â Digdag 0.8 documentation ç®æ¬¡ ã¤ã³ã¹ãã¼ã« ç°å¢ã®æºå Digdagã®ã¤ã³ã¹ãã¼ã«å®æ½ ãã®ä»ããã¥ã¡ã³ãã®å 容ã«ã¤ã㦠Digdagãµã³ãã«ã¯ã¼ã¯ãã
PerfectQueue is a highly available distributed queue built on top of RDBMS. PerfectQueue provides similar API to Amazon SQS, while PerfectQueue focuses on reliability and flexible scheduling rather than scalability. PerfectQueue introduces following concepts: At-least-once semantics: Even if a worker node fails during processing a task, another worker takes over the task. Multiuser-aware fair sche
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Treasure Data is a data analytics service company that makes heavy use of Ruby in its platform and services. It uses Ruby for components like Fluentd (log collection), Embulk (data loading), scheduling, and its Rails-based API and console. Java and JRuby are also used for components involving Hadoop and Presto processing. The company's architecture includes collectors that ingest data, a PlazmaDB
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This document discusses a technical talk given by Makoto Yui at Treasure Data on May 14, 2015. The talk introduces Hivemall, an open source machine learning library built on Apache Hive. Yui explains how Hivemall allows machine learning to be performed using SQL, making it easy for developers to use. The talk covers how to use Hivemall for tasks like data preparation, feature engineering, model tr
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