Big Data Platforms and Techniques

Abstract

Data is growing at unprecedented rate and has led to huge volume generated; the data sources include mobile, internet and sensors. This voluminous data is generated and updated at high velocity by batch and streaming platforms. This data is also varied along structured and unstructured types. This volume, velocity and variety of data led to the term big data. Big data has been premised to contain untapped knowledge, its exploration and exploitation is termed big data analytics. This literature reviewed platforms such as batch processing, real time processing and interactive analytics used in big data environments. Techniques used for big data are machine learning, Data Mining, Neural Network and Deep Learning. There are big data architecture offerings from Microsoft, IBM and National Institute of Standards and Technology. Big data potentials can transform economies and reduce running cost of institutions. Big data has challenges such as storage, computation, security and privacy

The accounting curriculum and the emergence of Big Data

“…BDA involves quantitative analysis, development testing, training, scoring and monitoring models (Borodo et al, 2016). Various techniques such as data mining, semantic analytics, data visualization, geospatial analysis and data discovery are used to gain insight from extracted data.…”

“…They imitate the human brain system and have the capacity to scan images, recognize and classify them. Techniques can be mixed to achieve better results (Borodo et al, 2016).…”

“…BDA involves the use of software such as Hadoop, NoSQL, Spark, Map Reduce, tableau for data visualization, GoogleAnalytics, MapReduce (Borodo et al, 2016).…”

“…Association ruling for instance can be used in descriptive analytics as it shows the probability of an event happening. For example, if a customer buys butter, he is probably going to buy bread (Borodo et al, 2016).…”

Analysis of Mobile Service Providers Performance Using Naive Bayes Data Mining Technique

“…Problem arises, with the growing field of big data, utilization of structured and unstructured data leads to worthy information for telecommunications industry in Malaysia to grow exponentially [4]. Consequently, issues on utilization of structured and unstructured data requires critical and analytical methods to overcome the needs of industry [5], [6]. There are many challenges to be faced for finding out the best telecommunication service provider since nowadays there are too many choices of mobile communication services with a different service rates and speeds [7].…”