Big Data definition

Big Data means very large and complex quantities of datasets that are difficult to process using traditional data processing applications;

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Big Data means large amounts of structured or unstructured data that are so large and complex that traditional data processing is inadequate to deal with it.

Big Data means more bandwidth: Handling today’s mega datasets requires massive parallel processing that is fueling a constant demand for additional capacity and any-to-any connectivity.

Examples of Big Data in a sentence

• Big Data 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 Big Data Products online or in person for a public group of attendees or on a custom basis.

• Driven by the “Internet of Things” and Big Data, 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, Big Data, 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 Big Data platform based on Apache Hadoop and Spark.

More Definitions of Big Data

Big Data means enormous quantities of data. The amount of data is too large and diverse for conventional computers and databases. “Big Data application” covers new ICT methods and approaches

Big Data 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.

Big Data means voluminous amounts of structured or unstructured data that demands fast, innovative and cost-effective ways to process for review and decision-making;

Big Data means any data outputs provided by GI’s 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

Big Data means more bandwidth: Handling today’s “big data” 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.

Big Data means more bandwidth Handling today’s “big data” 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.

Big Data versus "big brother": on the appropriate use of large-scale data collections in pediatrics. Pediatrics. 2013;131 Suppl 2:S127-S32.