What are the current research topics in big data?

What are the current research topics in big data?

General big data research topics [3] are in the lines of:

  • Scalability — Scalable Architectures for parallel data processing.
  • Real-time big data analytics — Stream data processing of text, image, and video.
  • Cloud Computing Platforms for Big Data Adoption and Analytics — Reducing the cost of complex analytics in the cloud.

What are the issues in big data?

Top 6 Big Data Challenges

  • Lack of knowledge Professionals. To run these modern technologies and large Data tools, companies need skilled data professionals.
  • Lack of proper understanding of Massive Data.
  • Data Growth Issues.
  • Confusion while Big Data Tool selection.
  • Integrating Data from a Spread of Sources.
  • Securing Data.

What Are big data 5 challenges?

5 Challenges Of Big Data Analytics in 2021

  • Business analytics solution fails to provide new or timely insights.
  • Inaccurate analytics.
  • Using data analytics in complicated.
  • Long system response time.
  • Expensive maintenance.

What is big data research paper?

Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets.

What is big data thesis?

Thesis Research Topics in Big Data Privacy, Security Issues in Big Data. Storage Systems of Scalable for Big Data. Massive Big Data Processing of Software and Tools. Techniques and Data Mining Tools for Big Data. Big Data Adoptation and Analytics of Cloud Computing Platforms.

How do you analyze data in a research paper?

  1. Step 1: Write your hypotheses and plan your research design.
  2. Step 2: Collect data from a sample.
  3. Step 3: Summarize your data with descriptive statistics.
  4. Step 4: Test hypotheses or make estimates with inferential statistics.
  5. Step 5: Interpret your results.

Why cloud is used in big data?

The public cloud has emerged as an ideal platform for big data. A cloud has the resources and services that a business can use on demand, and the business doesn’t have to build, own or maintain the infrastructure. Thus, the cloud makes big data technologies accessible and affordable to almost any size of enterprise.

Which aspects of big data lead to IT security challenges?

Fake Data Generation. One of the most significant security issues facing big data today is the generation of fake data.

  • Reversing Data Masking Measures.
  • Multi-Cloud Computing.
  • Data Cleansing Problems.
  • Big Data Complexity.
  • Real-Time Security Compliance.
  • Data Mining Issues.
  • Lack of Security Spending.
  • What are the three issues with big data explain briefly?

    This data needs to be analyzed to enhance decision making. But, there are some challenges of Big Data encountered by companies. These include data quality, storage, lack of data science professionals, validating data, and accumulating data from different sources.

    How can we protect big data?

    9 Tips for Securing Big Data

    1. Think about security before you start your big data project.
    2. Consider what data may get stored.
    3. Centralize accountability.
    4. Encrypt data both at rest and in motion.
    5. Separate your keys and your encrypted data.
    6. Use the Kerberos network authentication protocol.
    7. Use secure automation.

    What are data issues?

    Data quality issues can stem from duplicate data, unstructured data, incomplete data, different data formats, or the difficulty accessing the data. In this article, we will discuss the most common quality issues with data and how to overcome these.

    What are big data concepts?

    Put simply, big data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address business problems you wouldn’t have been able to tackle before.

    What are the top 3 Big Data privacy risks?

    Top 4 big data privacy risks In most cases, data breaches are the result of out-of-date software, weak passwords, and targeted malware attacks.