Big Data

Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.

Advantages of BigData:

  • Opportunities to Make Better Decisions.
  • Increasing Productivity and Efficiency.
  • Reducing Costs.
  • Improving Customer Service and Customer Experience.
  • Fraud and Anomaly Detection.
  • Greater Agility and Speed to Market.



Disadvantages of BigData:

  • Questionable Data Quality
  • Heightened Security Risks
  • Compliance Headaches
  • Cost and Infrastructure Issues
  • Big Data Skills Shortage

The dictionary definition of big data is extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. Data with many fields (columns) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source. Big data was originally associated with three key concepts: volume, variety, and velocity. The analysis of big data presents challenges in sampling, and thus previously allowing for only observations and sampling. Therefore, big data often includes data with sizes that exceed the capacity of traditional software to process within an acceptable time and value.