{"component": "definition", "props": {"groups": [{"samples": [{"hash": "5WitOOf6YPe", "uri": "https://www.sec.gov/Archives/edgar/data/893821/000117891318002563/exhibit_99-2.htm", "label": "Attunity LTD", "score": 13.720054757, "published": false}, {"hash": "fCrKbt9dHmq", "uri": "https://www.sec.gov/Archives/edgar/data/893821/000117891316006529/exhibit_99-2.htm", "label": "Attunity LTD", "score": 11.7159479808, "published": false}, {"hash": "cLS79UpeBJ0", "uri": "https://www.sec.gov/Archives/edgar/data/893821/000117891315002873/exhibit_99-2.htm", "label": "Attunity LTD", "score": 10.7084188912, "published": false}], "snippet": "means very large and complex quantities of datasets that are difficult to process using traditional data processing applications;", "size": 5, "snippet_links": [{"key": "very-large", "type": "definition", "offset": [6, 16]}, {"key": "processing-applications", "type": "clause", "offset": [105, 128]}], "hash": "d9c11ea4e95d2d87122e562c1ce3526e", "id": 1}, {"samples": [{"hash": "jj8rtsVK2Q7", "uri": "/contracts/jj8rtsVK2Q7#big-data", "label": "Asset Purchase Agreement", "score": 29.340862423, "published": true}, {"hash": "d8PH0wG7S15", "uri": "/contracts/d8PH0wG7S15#big-data", "label": "Asset Purchase Agreement (Mastech Digital, Inc.)", "score": 28.5290896646, "published": true}, {"hash": "7dwZA3kLw60", "uri": "/contracts/7dwZA3kLw60#big-data", "label": "Asset Purchase Agreement (Mastech Digital, Inc.)", "score": 28.5290896646, "published": true}], "snippet": "means large amounts of structured or unstructured data that are so large and complex that traditional data processing is inadequate to deal with it.", "size": 4, "snippet_links": [{"key": "unstructured-data", "type": "definition", "offset": [37, 54]}, {"key": "data-processing", "type": "clause", "offset": [102, 117]}], "hash": "c56f68b093cca989fa000f448989b659", "id": 2}, {"samples": [{"hash": "1vhV2acFkpf", "uri": "https://hepia.infolibre.ch/Virtualisation-Reseaux/sdn_with_openflow1.3_ovswitch_and_ryu.pdf", "label": "hepia.infolibre.ch", "score": 3.7597535934, "published": false}, {"hash": "jzieOMpL2u8", "uri": "https://cordis.europa.eu/docs/projects/cnect/8/285248/080/deliverables/001-D1113MarketandCompetitionAnalysis.pdf", "label": "cordis.europa.eu", "score": 3.5174537988, "published": false}], "snippet": "means more bandwidth: Handling today\u2019s mega datasets requires massive parallel processing that is fueling a constant demand for additional capacity and any-to-any connectivity.", "size": 4, "snippet_links": [{"key": "parallel-processing", "type": "clause", "offset": [70, 89]}, {"key": "additional-capacity", "type": "clause", "offset": [128, 147]}], "hash": "6a8bde1806e5405f30bf18bf03be120a", "id": 3}, {"samples": [{"hash": "4S8kuBpK8H7", "uri": "https://www.rolandberger.com/publications/publication_pdf/white_paper_digital_platforms.pdf", "label": "www.rolandberger.com", "score": 3.424366872, "published": false}, {"hash": "aescNCFbmAc", "uri": "https://www.bmwi.de/Redaktion/EN/Publikationen/white-paper.pdf?__blob=publicationFile&v=2", "label": "www.bmwi.de", "score": 3.424366872, "published": false}], "snippet": "means enormous quantities of data. The amount of data is too large and diverse for conventional computers and databases. \u201cBig Data application\u201d covers new ICT methods and approaches", "size": 2, "snippet_links": [], "hash": "77040115e9b8fea38e6a237b4b687631", "id": 4}, {"samples": [{"hash": "eCsSope8tfW", "uri": "https://www.eeoc.gov/eeoc/meetings/10-13-16/trindel.cfm", "label": "www.eeoc.gov", "score": 8.1704312115, "published": false}, {"hash": "cRa6ZpWLe6s", "uri": "https://nysba.org/NYSBA/Meetings%20Department/2018%20Annual%20Meeting/Coursebooks/Labor%20Employment/P2%20Changes%20.pdf", "label": "nysba.org", "score": 5.0232717317, "published": false}], "snippet": "means different things to different people. One issue that I would like to clarify immediately is that this is not simply about very large datasets, with many columns and rows. Although the size of these datasets is typically quite large this is not what defines big data. Rather, what makes data 'big' has to do with the nature and the source of the data and how it is collected, merged, transformed and utilized. In the employment context, I would define big data as follows: big data is the combination of nontraditional and traditional employment data with technology-enabled analytics to create processes for identifying, recruiting, segmenting and scoring job candidates and employees.", "size": 2, "snippet_links": [{"key": "very-large", "type": "definition", "offset": [128, 138]}, {"key": "the-nature", "type": "clause", "offset": [318, 328]}, {"key": "source-of-the-data", "type": "clause", "offset": [337, 355]}, {"key": "the-employment", "type": "clause", "offset": [418, 432]}, {"key": "the-combination", "type": "clause", "offset": [490, 505]}, {"key": "employment-data", "type": "definition", "offset": [540, 555]}], "hash": "702aca7d21b62dab9a95b96e1eac98d3", "id": 5}, {"samples": [{"hash": "gCERibeqcg4", "uri": "https://ise-prodnr-eu-west-1-data-integration.s3-eu-west-1.amazonaws.com/legacy/ListingParticulars_cde1dbb4-f4c1-45e6-898c-4f9a99149fef.pdf", "label": "ise-prodnr-eu-west-1-data-integration.s3-eu-west-1.amazonaws.com", "score": 8.9767282683, "published": false}, {"hash": "fOiHFiYsdw3", "uri": "http://www.oblible.com/Prospectus/www.oblible.com__USP0606PAC97.pdf", "label": "www.oblible.com", "score": 8.9767282683, "published": false}], "snippet": "means voluminous amounts of structured or unstructured data that demands fast, innovative and cost-effective ways to process for review and decision-making;", "size": 2, "snippet_links": [{"key": "unstructured-data", "type": "definition", "offset": [42, 59]}, {"key": "process-for-review", "type": "clause", "offset": [117, 135]}], "hash": "e6d407c5876df72a2611810452fd889e", "id": 6}, {"samples": [{"hash": "2jqTPCyH5gk", "uri": "/contracts/2jqTPCyH5gk#big-data", "label": "Exclusive License Agreement (World Technology Corp.)", "score": 29.5284052019, "published": true}, {"hash": "iRZdGgNy1rJ", "uri": "/contracts/iRZdGgNy1rJ#big-data", "label": "Exclusive License Agreement (World Technology Corp.)", "score": 29.1204654346, "published": true}], "snippet": "means any data outputs provided by GI\u2019s Advanced App, including, but not limited to, user data for those users that consent to the use of their data, alcohol sensor raw signals, alcohol sensor converted signals, and any advanced algorithms outputs. Proprietary and ConfidentialThis Agreement and information contained therein is not for use or disclosure outside of WRMT, its Affiliates, and third party representatives, and GI except under written agreement by the contracting parties", "size": 2, "snippet_links": [{"key": "not-limited", "type": "clause", "offset": [69, 80]}, {"key": "user-data", "type": "definition", "offset": [85, 94]}, {"key": "consent-to", "type": "clause", "offset": [116, 126]}, {"key": "and-information", "type": "clause", "offset": [292, 307]}, {"key": "use-or-disclosure", "type": "clause", "offset": [337, 354]}, {"key": "party-representatives", "type": "definition", "offset": [398, 419]}, {"key": "written-agreement", "type": "definition", "offset": [441, 458]}, {"key": "the-contracting-parties", "type": "clause", "offset": [462, 485]}], "hash": "9c172e7631fe15d4aca4d94d33caa831", "id": 7}, {"samples": [{"hash": "dwkOx9rjhI0", "uri": "https://pergamos.lib.uoa.gr/uoa/dl/object/1321382/file.pdf", "label": "pergamos.lib.uoa.gr", "score": 5.9295878181, "published": false}], "snippet": "means more bandwidth: Handling today\u2019s \u201cbig data\u201d or mega datasets requires massive parallel processing on thousands of servers, all of which need direct connections to each other. The rise of mega datasets is fueling a constant demand for additional network capacity in the data center. Operators of high scale data center networks face the task of scaling the network to previously unimaginable size, maintaining any-to-many and any-to-any connectivity without disruptions.", "size": 2, "snippet_links": [{"key": "parallel-processing", "type": "clause", "offset": [84, 103]}, {"key": "direct-connections", "type": "clause", "offset": [147, 165]}, {"key": "network-capacity", "type": "definition", "offset": [251, 267]}, {"key": "data-center", "type": "definition", "offset": [275, 286]}, {"key": "operators-of", "type": "clause", "offset": [288, 300]}, {"key": "the-network", "type": "clause", "offset": [358, 369]}], "hash": "90e1de2b4cfe000d9d35d97394bf317e", "id": 8}, {"samples": [{"hash": "fmiq1lEYbvr", "uri": "https://www.docdroid.net/file/download/IadFYf6/sdn-101-and-more-ie-stuff-pdf.pdf", "label": "www.docdroid.net", "score": 6.697467488, "published": false}], "snippet": "means more bandwidth Handling today\u2019s \u201cbig data\u201d or mega datasets requires massive paral- lel processing on thousands of servers, all of which need direct connections to each other. The rise of mega datasets is fueling a constant demand for ad- ditional network capacity in the data center. Op- erators of hyperscale data center networks face the daunting task of scaling the network to previously unimaginable size, maintaining any-to-any connec- tivity without going broke.", "size": 1, "snippet_links": [{"key": "direct-connections", "type": "clause", "offset": [148, 166]}, {"key": "network-capacity", "type": "definition", "offset": [254, 270]}, {"key": "data-center", "type": "definition", "offset": [278, 289]}, {"key": "the-network", "type": "clause", "offset": [372, 383]}], "hash": "63e66fa5a8a053fc81899d186d4e6690", "id": 9}, {"samples": [{"hash": "flMrZVX3KPz", "uri": "/contracts/flMrZVX3KPz#big-data", "label": "PHD Dissertation", "score": 29.5582690404, "published": true}], "snippet": "versus \"big brother\": on the appropriate use of large-scale data collections in pediatrics. Pediatrics. 2013;131 Suppl 2:S127-S32.", "size": 1, "snippet_links": [{"key": "appropriate-use", "type": "definition", "offset": [29, 44]}, {"key": "data-collections", "type": "clause", "offset": [60, 76]}], "hash": "f104bee861ed4c6acb8f52dad7a736ae", "id": 10}], "next_curs": "ClUST2oVc35sYXdpbnNpZGVyY29udHJhY3RzcjELEhpEZWZpbml0aW9uU25pcHBldEdyb3VwX3Y1NiIRYmlnLWRhdGEjMDAwMDAwMGEMogECZW4YACAA", "definition": {"title": "Big Data", "snippet": "means very large and complex quantities of datasets that are difficult to process using traditional data processing applications;", "size": 40, "id": "big-data", "examples": ["<strong>Big Data</strong> visualization involves the presentation of data of almost any type in a graphical format that makes it easy to understand and interpret.", "Named Support Contacts must be trained via training courses provided by Hitachi to You for the <strong>Big Data</strong> Products online or in person for a public group of attendees or on a custom basis.", "Driven by the \u201cInternet of Things\u201d and <strong>Big Data</strong>, companies will undergo a transformation that will make the largest part of the business digital and the technological basis of this transformation is precisely Cloud Computing.", "Technology domains may include Cloud, Virtualization, Data Management, <strong>Big Data</strong>, System Architecture, Data Center Operations and Tooling, Cyber Security, Best Practice development, Database Design and Development, Integration, Consolidation, Migration, IT Strategic Planning, and specific IT Products.", "Previously referred to as SAP Cloud Platform Automation Pilot Cloud Service Description The Cloud Service provides enterprises a fully managed <strong>Big Data</strong> platform based on Apache Hadoop and Spark.", "Previously referred to as SAP HANA Cloud Platform, streaming service Cloud Service Description SAP Cloud Platform <strong>Big Data</strong> Services provides enterprises a fully managed <strong>Big Data</strong> platform based on Apache Hadoop and Spark.", "The Community Forum enables StreetLight InSight users across North American agencies and engineering firms to share tips and tricks and discuss how best to use <strong>Big Data</strong> analytics for a variety of mobility applications.", "Digital Technologies \u2022 Artificial Intelligence \u2022 <strong>Big Data</strong> and Data Analytics \u2022 Cloud Computing \u2022 Distributed Ledger Technologies (DLT-Blockchain) \u2022 Internet of Things \u2022 Digital Games 3.", "Example topics include: (i) modifications to existing national security research funding programs (SBIR/STTR) to better engage with startups, (ii) coordination of <strong>Big Data</strong> opportunities, or (iii) new models for engagement with entrepreneurs under existing contracting rules.", "To manage it all, you&#x27;re investing in technology \u2013 Mobile, IoT, Cloud, <strong>Big Data</strong>, Security \u2013 to help you and the people around you work more efficiently, catch errors before they become problems, and provide deeper insights so you can make decisions with confidence."], "related": [["glo-data", "GLO Data", "GLO Data"], ["unicef-data", "UNICEF Data", "UNICEF Data"], ["historical-data", "Historical data", "Historical data"], ["system-data", "System Data", "System Data"], ["raw-data", "Raw Data", "Raw Data"]], "related_snippets": [], "updated": "2025-07-06T21:58:30+00:00"}, "json": true, "cursor": ""}}