Katal et al. [26] provide a varied discussion covering several big data issues, challenges, tools, characteristics, sources, and best practices in relation to such applications as social media, sensor data, log storage, and risk analysis.
Along with standard big data issues like accuracy, privacy, regulation and governance, developing countries are particularly susceptible to methodological problems such as fewer new data sources, issues with limited internet access and lack of private sector investment.
The results depict that the LHNFCSF addresses the medical big data issues by reducing the dimensions of large datasets and speeding up the learning process and improves the classification performance.
Enterprises dealing with such Big Data issues at this scale cannot use existing analytical techniques effectively, and so false alarms are especially problematic.
Because the big data issues have appeared for nearly ten years, in [106], Fan and Bifet pointed out that the terms "big data" [107] and "big data mining" [108] were first presented in 1998, respectively.
These experiments also show that Solid ensures low-latency operations because data effectively managed in real-time remain small, so do not suffer Big Data issues.
In addition, we consider the Big Data issues that arise when handling such forms of heterogeneous security data.
"But if we want to be able to deal with big data issues throughout the EU, then every national authority has to have the tools it needs to enforce the rules… I think there's a strong case for new EU rules as part of the answer".
In this paper, we propose a filling algorithm based on complete tolerance class to solve the missing of energy big data issue.
