Traditional Techniques are not able to store and manage the big data. In this paper, we are focusing on various data analytics techniques and challenges in that techniques.C. KomalavalliChetna LaroiyaInternational Conference on Cloud Computing, Data Science &ampampampampamp Engineering...
Big Data Analytics and Deep Learning are two high-focus of data science. Big Data has become important as many organizations both public and private have been collecting massive amounts of domain-specific information, which can contain useful information
Big Data Analytics and Deep Learning are two high-focus of data science. Big Data has become important as many organizations both public and private have been collecting massive amounts of domain-specific information, which can contain useful information
In the data-driven world, business intelligence is in high demand. 97.2 percent of companies today are investing in big data and AI to drive growth and development.Despite this, many organizations face big data analytics challenges and strategic, tactical level efficiency. According to Gartner, 87...
One of the key values of the banking industry has been its 'Customer-Focused' mindset, but in the new era, the trend is moving to being 'Customer-Centric'. This is because advances in technology and communication, combined with an explosive growth in data and information, have given rise ...
Big Data (BD), with their potential to ascertain valued insights for enhanced decision-making process, have recently attracted substantial interest from both academics and practitioners. Big Data Analytics (BDA) is increasingly becoming a trending practice that many organizations are adopting with the ...
We are talking about “Hadoop”, a cost-effective and scalable platform for BigData analysis. Using the Hadoop system instead of Traditional ETL (extraction, transformation, and loading) processes gives you better results in less time. Running of Hadoop Cluster efficiently implies selecting an optima...
Big Data Analytics in IOT: Challenges, Open Research Issues and ToolsBig Data AnalyticsInternet of ThingsHadoopMassive dataStructured dataUnstructured dataTerabytes of data are generated day-to-day from modern information systems, cloud computing and digital technologies, as the increasing number of ...
Big data preprocessing: methods and prospects The massive growth in the scale of data has been observed in recent years being a key factor of the Big Data scenario. Big Data can be defined as high volu... S García,S Ramírez-Gallego,J Luengo,... - 《Big Data Analytics》 被引量: 22...
Big data analytics refers to the process of gathering, arranging and analyzing huge data set to uncover the hidden knowledge that enables us to take effective and efficient decision making. The source data mostly may contain heterogeneity, noise, outliers, missing values and inconsistency. The poor...