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Intro

You might hear much about big data as a field that many scientists focus on research. At the beginning of the study, big data is a complex field not many students want to challenge. This field is large and requires multiple knowledge bases to complete a project or prove a statement that you pursue. 

So, if you dream about writing an essay about this topic (or want to do it to prove your ability in this field), you should refer to my article. It shares my extensive data explanations and orientates the researchers to find ideas in this challenging field. 

Big Data là gì? Những ưu điểm nổi bật giúp ứng dụng trong mọi lĩnh vực

What Is Big Data?

Definition

Big Data is large and complex data sets. Its size is large as traditional data processing software cannot collect, manage, and process data in a reasonable amount of time.

These large data sets can include structured, unstructured, and semi-structured data, which we can use to get people’s insights.

At a minimum, Big Data must meet the following three factors:

  • Volume: or called Capacity. Big data must be a large data set, but as mentioned above – there is no milestone to mark the standard size. It is a huge data file, and the “large” term makes you think “it’s so big.”
  • Variety: or called Diversity. Big data is not limited to Diversity. It includes all types of data in the world, such as images, text, video, audio, etc., regardless of whether the data is structured, semi-structured, or unstructured.
  • Velocity: is the increase of data. Big data is increased over time, and this increase is enormous. And like the Volume criterion, there is no standard to judge how significant the growth is, but it should be enough for you to say “data grew so fast.”

Some studies have shown that 80% of the data in the world is big data, and we have only exploited 20% of it.

Difference Between Big Data & Normal Data

The difference between big data and standard data is not significant. All the data that is not classified as big data is normal data.

What To Research In Big Data Field?

As long as you understand big data, you may want to know the targets you will research in the big data field. This section will help you determine a way to study and avoid misdirecting. 

Big data problems can be divided into two groups:

  • Problems of Data Storage: With a massive amount of data (with no limit), you have to find a way to store it all. It is a challenge for scientists to find new methods every day to keep the vast amount of data increasing at multiple levels. 
  • Problems of Data Processing: Operations that need to be handled such as analyzing a specific index, predicting a particular index, searching for certain information, etc.

Based on two groups, you can easily find your direction to research in the Big Data field. For example, when I was in college, I once tried to do my homework writing about the compression of multiple file data. Although it is not a new topic, it is excellent to help me do my homework, especially a collection of knowledge that I can review in the future. 

If you find any problem, make sure you classify and put it into a suitable group. Thus, you will have a whole picture of what you will study. For example, I once faced an issue when I tried to do my homework: The data processing for data storage. With this topic, how will you classify it?

Of course, the purpose is for data storage, and data processing is just a way you do to reach the final target. Therefore, the whole picture of this problem needs to be data storage. 

What Is The Role Of Writing Service In Helping You With Big Data Topic?

In the big data field, you might not want to research alone. This topic requires much progress that one person will be stressed to do. The better idea is to find a group and have unanimity on a topic idea. 

However, what happens if you insist on studying a big data topic alone? Of course, facing many challenges are what you need to perceive. Doing alone just increases the difficulty, but it does not mean impossibility. 

That is why I am writing this section to give you an idea of the best support for your process of studying alone. 

The writing services are excellent as they help me do my homework, so I once tried it to complete my big data essay efficiently. What benefits can you take from this service in writing a big data topic?

  • Data analysis: Data analysis is always the most challenging part that not many researchers voluntarily want. It takes much time and effort, and if you have a mistake, all will be wrong. That is why ordering a website that does your homework for data analysis will be an excellent option. The expert has years of experience in analyzing it and will never provide you with the wrong data because of guaranteeing outcome high-quality.  
  • Great Topic: Finding a topic is the stage that takes your time. You may wonder what topic will be great, but it is still under your capability. I had ordered a website that does your homework multiple times, so I understood what topic they provide. Of course, they try to synthesize all the topics people have done, then compare with your study level to confirm the suitable topic. For example, my level was bachelor’s, so the topic is all about introduction with a bit of analysis. 
  • Save Time & Money: Time is money, and your effort too. Using this service helps you save a lot of money researching the big data field. Also, when you analyze big data, you might need some tools to process the study. The experts in writing service can help you get rid of this difficulty. 

100 Suggested Ideas For Big Data Field

Let’s check some suggested ideas for the big data field below. They are all the ideas from the original works, so you may be interested and can refer to figure out yours. 

  1. Big Data versus the Crowd: Looking for Relationships in All the Right Places
  2. Analyzing Big Data: The Path to Competitive Advantage
  3. IBM Big Data Fundamentals Technical Mastery Test
  4. Learn internet marketing system with big data technology
  5. Big Data and Grid Computing solutions
  6. Research on security and extensive data mining in cloud computing
  7. Big Data technology and business data analysis applications
  8. Measuring consumer engagement with brands with BIG DATA
  9. Applying Big Data in analyzing customer’s shopping and consumption behavior to promote business activities
  10. Research and build Cloudera open source solution model for extensive data application deployment
  11. PageRank algorithm
  12. Program to multiply two large matrix
  13. Research some issues about big data and its application in business analysis
  14. Opportunities to manage big data efficiently and effectively
  15. Using big data and artificial intelligence in banking operations
  16. Extensive data application in evaluation statistics
  17. Trends of big data applications in attracting and retaining talents
  18. The role of big data in financial companies and the implications of big data on management accounting
  19. Big data governance, dynamic capability and decision-making effectiveness: Fuzzy sets approach
  20. Big data and application trends in information activities – libraries
  21. Extensive data application to analyze loan credit vulnerabilities and solutions to limit the bank’s case
  22. Applying methods in big data to data storage
  23. Analyzing the influence of big data on the data analysis process at auditing firms
  24. Efficient traffic data cleaning and visualization utilizing big data technologies
  25. Studying the role of big data in intelligent tourism destination
  26. Using big data to construct the residential property price index
  27. Big data system for health care records
  28. Design and implement big data system for cardiovascular data
  29. An extensive data analytics framework for IoT applications in the cloud
  30. Big data with innovative libraries
  31. Applying GPU database in processing big data
  32. Research and build Cloudera open-source solution model for extensive data application deployment.
  33. Analyzing The Impact Of Big Data On The Data Analysis Process
  34. Applying Big Data in automating human resource recruitment
  35. The correlations between big data analytics and financial performance empirical investigation in the banking sector
  36. The benefits of Big Data and data analysis for human resource management in enterprises
  37. Overview of big data and application efficiency in e-commerce business and economics
  38. Clustering data in data mining
  39. Applying Data Warehouse in analyzing information about value-added services on phones
  40. Data warehouse and data mining
  41. DataMining application for the development of fixed telephone subscribers
  42. Building Data Warehouse system management software
  43. Applying blockchain to retail problem 
  44. Applying big data to process big data in cancer prediction problem 
  45. Applying big data to process big data in text NLP problem 
  46. Applying big data to process big data to predict the risk of investment packages through the Monte Carlo Simulation algorithm 
  47. Applying big data to process big data to predict natural disasters through social media posts, through the ROC algorithm 
  48. Applying big data to process big data to predict motorcycle sales, through collecting consumer sentiment to motorcycle shops, through logical regression algorithm 
  49. Applying big data to process big data to predict the risk of investment packages through the Monte Carlo Simulation algorithm 
  50. Apply historical data of sales, analyze predictive data, make business decisions, use Tableau 
  51. Apply historical data of purchases and sales, analyze predictive data, and make business decisions
  52. Research and apply methods of big data in a copy detection system
  53. Research and application of big data methods in Traffic Sign Detection/Recognition
  54. Research and apply methods of big data in traffic violation detection
  55. Research and apply methods of big data in controlling people entering and exiting an area

Enjoy a favorite movie. Things get done when you come back

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