Which statement is true of big data?
1 Answer. The correct answer is option A (Big data refers to data sets that are at least a petabyte in size). Big data is normally referred as the large volume of data like petabyte and exabyte in size (1 petabyte = 1,00,000 GB).
1 Answer. The correct option is c (enables retailers and suppliers alike to gain better customer insights). Big data analysts use the Recency Frequency Monetary analysis to find out the important customers.
The definition of big data is data that contains greater variety, arriving in increasing volumes and with more velocity. This is also known as the three Vs. Put simply, big data is larger, more complex data sets, especially from new data sources.
Which of the following is true about big data? Answer - B) Big data refers to data sets that are at least of petabyte in size is true.
Big data is a term which is used to describe any data set that is so large and complex that it is difficult to process using traditional applications.
1 Answer. The correct answer is option D (can be analyzed with traditional spreadsheets). Big data cannot be analyzed with traditional spreadsheets or database systems like RDBMS because of the huge volume of data and a variety of data like semi-structured and unstructured data.
| Q. | Which of the following are Benefits of Big Data Processing? |
|---|---|
| A. | Businesses can utilize outside intelligence while taking decisions |
| B. | Improved customer service |
| C. | Better operational efficiency |
| D. | All of the above |
The 5 V's of big data (velocity, volume, value, variety and veracity) are the five main and innate characteristics of big data. Knowing the 5 V's allows data scientists to derive more value from their data while also allowing the scientists' organization to become more customer-centric.
What are the Characteristics of Big Data? Three characteristics define Big Data: volume, variety, and velocity. Together, these characteristics define “Big Data”.
The classification of big data is divided into three parts, such as Structured Data, Unstructured Data, and Semi-Structured Data.
Which of the following is not a characteristic of big data Mcq?
d) Variety. Option(b) Vision is not a characteristic of Big Data. A large volume of data that is very complex in nature is the Big data. These types of data can not be handled using traditional methods.
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.
6. Which of the following are incorrect Big Data Technologies? Explanation: Apache Pytarch is incorrect Big Data Technologies.
There are actually 4 measurable characteristics of big data we can use to define and put measurable value to it. Volume, Velocity, Variety, and Veracity. These characteristics are what IBM termed as the four V's of big data.
Big data comes from myriad sources -- some examples are transaction processing systems, customer databases, documents, emails, medical records, internet clickstream logs, mobile apps and social networks.
What is true of Big Data in comparison to traditional data? Big Data requires a different approach to analysis, computing, and storage mechanisms.
The biggest advantage of Big Data is the fact that it opens up new possibilities for organizations. Improved operational efficiency, improved customer satisfaction, drive for innovation, and maximizing profits are only a few among the many, many benefits of Big Data.
Big data allows businesses to deliver customized products to their targeted market—no more spending fortunes on promotional campaigns that do not deliver. With big data, enterprises can analyze customer trends by monitoring online shopping and point-of-sale transactions.
C.It helps in optimizing business processes.
Which of the following best describes Big Data analysis? It is the use of tools and analysis techniques for treating very large, very complex data sets.
What are the different features of big data analytics Mcq?
- 1). Easy Result Formats. ...
- 2). Raw data Processing. ...
- 3). Prediction apps or Identity Management. ...
- 4). Reporting Feature. ...
- 5). Security Features. ...
- 6). Fraud management. ...
- 7). Technologies Support. ...
- 8). Version Control.
What is big data analytics? Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes.
Explanation: Big data analysis does the following except Spreads data.
Big data is a collection of data from many different sources and is often describe by five characteristics: volume, value, variety, velocity, and veracity.
The classification of big data is divided into three parts, such as Structured Data, Unstructured Data, and Semi-Structured Data.
Big data is a combination of structured, semistructured and unstructured data collected by organizations that can be mined for information and used in machine learning projects, predictive modeling and other advanced analytics applications.