Overview of Big Data and their Research Challenges

In the Digital world, data is the vital role of the information. Nowadays, data is collected from various sources like social media, machines and other digital technologies. It provides large datasets with a collection of many fields. In general, traditional data processing is not capable to handle the large set of data. So, to overcome this problem big data analytics concept is defined. It is a smart and intelligent way that handles huge sets of data. More scientists works based on this concept, the result is very efficient. It is differentiated with traditional technologies such as volume, velocity, and variety of data research paper writing. Volume defines the huge amount of data, velocity defines how fast the data are gathered while the rate of growth for being analysis. Finally, the variety provides data information such as structured, unstructured or semi-structured.

Challenges in Big Data
  • Major Research challenges in Big Data. They are,
  • Security
  • Accessibility
  • Mobility
  • Storage and Transport
  • Applied Ontology
  • Inconsistencies

Technical Challenges in Big Data
  • Failure Handling
  • Data heterogeneity
  • Data quality
Big data is the process to analyze huge sets of data which contains a variety of data types in the area of uncovers hidden patterns, health care; reduce crime, fraud detection, and other useful business information. Big data is not the only store and process the data, it just keeps the integrity of the data and also data are very confidential for the organizations. In trending, there are many PhD research topics in big data analytics. At the same time, in future big data researches are highlighted. Get more details about PhD Thesis and Research Guidance Center.

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