{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,4]],"date-time":"2022-04-04T23:50:59Z","timestamp":1649116259030},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,8,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Big Data and Big Data analytics have attracted major interest in research and industry and continue to do so. The high\ndemand for capable and scalable analytics in combination with the ever increasing number and volume of application\nscenarios and data has lead to a large and intransparent landscape full of versions, variants and individual\nalgorithms. As this zoo of methods lacks a systematic way of description, understanding is almost impossible which\nseverely hinders effective application and efficient development of analytic algorithms. To solve this issue we propose\nour concept of modular analytics that abstracts the essentials of an analytic domain and turns them into a set of\nuniversal building blocks. As arbitrary algorithms can be created from the same set of blocks, understanding is eased and\ndevelopment benefits from reusability.<\/jats:p>","DOI":"10.1515\/itit-2016-0003","type":"journal-article","created":{"date-parts":[[2016,7,29]],"date-time":"2016-07-29T08:56:09Z","timestamp":1469782569000},"page":"176-185","source":"Crossref","is-referenced-by-count":0,"title":["Big by blocks: modular analytics"],"prefix":"10.1515","volume":"58","author":[{"given":"Martin","family":"Hahmann","sequence":"first","affiliation":[{"name":"Technische Universit\u00e4t Dresden, Dep. of Computer Science, N\u00f6thnitzer Str. 46, D-01062 Dresden, Germany"}]},{"given":"Claudio","family":"Hartmann","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Dresden, Dep. of Computer Science, N\u00f6thnitzer Str. 46, D-01062 Dresden, Germany"}]},{"given":"Lars","family":"Kegel","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Dresden, Dep. of Computer Science, N\u00f6thnitzer Str. 46, D-01062 Dresden, Germany"}]},{"given":"Dirk","family":"Habich","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Dresden, Dep. of Computer Science, N\u00f6thnitzer Str. 46, D-01062 Dresden, Germany"}]},{"given":"Wolfgang","family":"Lehner","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Dresden, Dep. of Computer Science, N\u00f6thnitzer Str. 46, D-01062 Dresden, Germany"}]}],"member":"374","published-online":{"date-parts":[[2016,7,28]]},"container-title":["it - Information Technology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.degruyter.com\/view\/j\/itit.2016.58.issue-4\/itit-2016-0003\/itit-2016-0003.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2016-0003\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2016-0003\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,23]],"date-time":"2021-06-23T11:44:52Z","timestamp":1624448692000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2016-0003\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,7,28]]},"references-count":0,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2016,6,24]]},"published-print":{"date-parts":[[2016,8,28]]}},"alternative-id":["10.1515\/itit-2016-0003"],"URL":"https:\/\/doi.org\/10.1515\/itit-2016-0003","relation":{},"ISSN":["1611-2776","2196-7032"],"issn-type":[{"value":"1611-2776","type":"print"},{"value":"2196-7032","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,7,28]]}}}