Big Data refers to data sets that are too large or complex for traditional data-processing application software to adequately deal with. Data with many cases offer greater statistical power, while data with higher complexity may lead to a higher false discovery rate. there are many examples of big data sources we will discuss here.
Big Data Sources Examples
Social network profiles are the practice of expanding the number of one’s business and/or social contacts by making connections through individuals, often through social media sites such as Facebook, Twitter, LinkedIn, and Google+. This requires a fairly straightforward API integration for importing pre-defined fields and values, for example, a social network API integration that gathers every B2B marketer on Twitter.
Social influencer is a user on social media who has established credibility in a specific industry. A social media influencer has access to a large audience and can persuade others by virtue of their authenticity and reach. resources. Discover Brand Influencers to Expand Social Reach. Editor, analyst, and subject-matter expert blog comments, user forums, Twitter & Facebook “likes,” Yelp-style catalog and review sites, and other review-centric sites like Apple’s App Store, Amazon, ZDNet, etc.
Activity-generated data is digital information created by the activity of computers, mobile phones, embedded systems, and other networked devices. Such data became more prevalent as technologies such as radio frequency identification (RFID) and telematics advanced. This category includes web site tracking information, application logs, and sensors such as check-ins and another location tracking among other machine-generated content.
Software as a Service (SaaS) is a software licensing and delivery model in which software is licensed on a subscription basis and is centrally hosted. It is sometimes referred to as “on-demand software”, and was formerly referred to as “software plus services” by Microsoft.
Cloud Applications is a software program where cloud-based and local components work together. This model relies on remote servers for processing logic that is accessed through a web browser with a continual internet connection.
Hadoop MapReduce application results is a software framework for distributed processing of large data sets on compute clusters of commodity hardware. It is a sub-project of the Apache Hadoop project. The framework takes care of scheduling tasks, monitoring them and re-executing any failed tasks. The next generation technology architectures for handling and parallel parsing from logs.
Data warehouse appliances is a combination hardware and software product that is designed specifically for analytical processing. With it, however, it is the vendor who is responsible for simplifying the physical database design layer and making sure that the software is tuned for the hardware.
NoSQL data sources provide a mechanism for storage and retrieval that is modeled in means other than the tabular relations used in relational databases. NoSQL databases are increasingly used in big data and real-time web applications. These are specialty applications that fill gaps in Hadoop-based environments,
Network and in-stream monitoring technologies Packet evaluation and distributed query processing-like applications, as well as email parsers, are also likely areas that will explode with new startup technologies.
Legacy documents Archives of statements, insurance forms, medical record, and customer correspondence are still an untapped resource. Parsing this semi-structured legacy content can be challenging without specialty tools like Xenos.