{"id":1414,"date":"2021-10-05T07:14:20","date_gmt":"2021-10-05T07:14:20","guid":{"rendered":"https:\/\/blog.amt.in\/?p=1414"},"modified":"2021-10-05T07:14:20","modified_gmt":"2021-10-05T07:14:20","slug":"introduction-to-big-data","status":"publish","type":"post","link":"https:\/\/blog.amt.in\/index.php\/2021\/10\/05\/introduction-to-big-data\/","title":{"rendered":"Introduction to Big Data"},"content":{"rendered":"

Big data\u00c2\u00a0is\u00c2\u00a0data sets\u00c2\u00a0that are so voluminous and complex that traditional\u00c2\u00a0data-processing\u00c2\u00a0application software\u00c2\u00a0are inadequate to deal with them.\u00c2\u00a0Big data challenges include\u00c2\u00a0capturing data,\u00c2\u00a0data storage,\u00c2\u00a0data analysis, search,\u00c2\u00a0sharing,\u00c2\u00a0transfer,\u00c2\u00a0visualization,\u00c2\u00a0querying,\u00c2\u00a0updating,\u00c2\u00a0information privacy\u00c2\u00a0and data source.\u00c2\u00a0There are a number of concepts associated with big data.\u00c2\u00a0\u00c2\u00a0Originally there were 3 concepts\u00c2\u00a0volume,\u00c2\u00a0variety,\u00c2\u00a0velocity.\u00c2\u00a0Other concepts later attributed with big data are\u00c2\u00a0veracity\u00c2\u00a0(<\/i>i.e.,\u00c2\u00a0<\/i>how\u00c2\u00a0<\/i>much noise is in the data)<\/i>\u00c2\u00a0and\u00c2\u00a0value.<\/p>\n

Lately, the term “big data” tends to refer to the use of\u00c2\u00a0predictive analytics,\u00c2\u00a0user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. There is little doubt that the quantities of data now available are indeed large, but that\u00e2\u20ac\u2122s not the most relevant characteristic of this new data ecosystem.<\/p>\n

Analysis of data sets can find new correlations to spot business trends, prevent diseases, combat crime and so on.\u00c2\u00a0Scientists, business executives, practitioners of medicine, advertising and\u00c2\u00a0governments\u00c2\u00a0alike regularly meet difficulties with large data-sets in areas including\u00c2\u00a0Internet search,\u00c2\u00a0fin-tech,\u00c2\u00a0urban informatics, and\u00c2\u00a0business informatics. Scientists encounter limitations in\u00c2\u00a0e-Science\u00c2\u00a0work, including\u00c2\u00a0meteorology,\u00c2\u00a0genomics,\u00c2\u00a0connectomics, complex physics simulations, biology and environmental research.<\/p>\n

Data sets grow rapidly – in part because they are increasingly gathered by cheap and numerous information-sensing\u00c2\u00a0Internet of things\u00c2\u00a0devices such as\u00c2\u00a0mobile devices, aerial (remote sensing), software logs,\u00c2\u00a0cameras, microphones,\u00c2\u00a0radio-frequency identification\u00c2\u00a0(RFID) readers and\u00c2\u00a0wireless sensor networks.<\/p>\n

The world’s technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s.<\/p>\n

Relational database management systems\u00c2\u00a0and desktop statistics and software packages to visualize data often have difficulty handling big data. The work may require massively parallel software running on tens, hundreds, or even thousands of servers.\u00c2\u00a0What counts as “big data” varies depending on the capabilities of the users and their tools, and expanding capabilities make big data a moving target.\u00c2\u00a0For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration. Big data can be described by the following characteristics as below.<\/p>\n

Volume:<\/p>\n

\n
The quantity of generated and stored data. The size of the data determines the value and potential insight, and whether it can be considered big data or not.<\/dd>\n
Variety:<\/dd>\n<\/dl>\n
\n
The type and nature of the data. This helps people who analyze it to effectively use the resulting insight. Big data draws from text, images, audio, video plus it completes missing pieces through data fusion.<\/dd>\n
Velocity:<\/dd>\n<\/dl>\n
\n
In this context, the speed at which the data is generated and processed to meet the demands and challenges that lie in the path of growth and development. Big data is often available in real-time.<\/dd>\n
Veracity:<\/dd>\n<\/dl>\n
\n
The\u00c2\u00a0data quality\u00c2\u00a0of captured data can vary greatly, affecting the accurate analysis.<\/dd>\n
Big Data virtualization is a way of gathering data from a few sources in a single layer. The gathered data layer is virtual. Unlike other methods, most of the data remains in place and is taken on demand directly from the source systems.<\/dd>\n
The above is a brief about Big Data. Watch this space for more updates on the latest trends in Technology.<\/dd>\n<\/dl>\n","protected":false},"excerpt":{"rendered":"

Big data\u00c2\u00a0is\u00c2\u00a0data sets\u00c2\u00a0that are so<\/p>\n","protected":false},"author":1,"featured_media":1416,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[137,138,7],"tags":[139,140,18],"class_list":["post-1414","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-big-data","category-data-processing","category-techtrends","tag-big-data","tag-data-processing","tag-technology"],"_links":{"self":[{"href":"https:\/\/blog.amt.in\/index.php\/wp-json\/wp\/v2\/posts\/1414","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.amt.in\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.amt.in\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.amt.in\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.amt.in\/index.php\/wp-json\/wp\/v2\/comments?post=1414"}],"version-history":[{"count":1,"href":"https:\/\/blog.amt.in\/index.php\/wp-json\/wp\/v2\/posts\/1414\/revisions"}],"predecessor-version":[{"id":1415,"href":"https:\/\/blog.amt.in\/index.php\/wp-json\/wp\/v2\/posts\/1414\/revisions\/1415"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.amt.in\/index.php\/wp-json\/wp\/v2\/media\/1416"}],"wp:attachment":[{"href":"https:\/\/blog.amt.in\/index.php\/wp-json\/wp\/v2\/media?parent=1414"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.amt.in\/index.php\/wp-json\/wp\/v2\/categories?post=1414"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.amt.in\/index.php\/wp-json\/wp\/v2\/tags?post=1414"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}