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Understanding Big Data and Data Science Concepts, Essays (high school) of Computer science

Computer science

A comprehensive overview of key concepts related to big data and data science. It covers topics such as structured, unstructured, and semi-structured data, the 3vs (volume, variety, and velocity) of big data, cognitive computing, data curation, data analytics, and the essential skills required for data scientists. The document also includes questions and answers that test the reader's understanding of these concepts. With its detailed explanations and practical examples, this document could be a valuable resource for university students, researchers, or professionals interested in exploring the field of big data and data science.

Typology: Essays (high school)

2020/2021

Uploaded on 11/25/2022

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Questions & Answers section.1.
1. ……… a data that is which is not organized in a pre-defined manner or does
not have a pre-defined data model, thus it is not a good fit for a mainstream
relational database.
a. Structured data c. Semi-structured data
b. unstructured data
2. ……………. helps organizations understand the relative growth of their big
data and how quickly that data reaches sourcing users, applications and
systems.
a. Variety c. Volume
b. Velocity d. Complexity
3. …… is information that does not reside in a rational database but that have
some organizational properties that make it easier to analyze.
a. Semi- Structured data c. Quasi-structured data
b. unstructured data d. Structured Data
4. …… is a data whose elements are addressable for effective analysis. It has
been organised into a formatted repository that is typically a database.
a. Structured Data c. unstructured data
b. Quasi-structured data d. Semi- Structured data
5. Extensible Markup Language [XML] data files is example of ………..
a. Structured Data c. unstructured data
b. Quasi-structured data d. Semi- Structured data
6. …………………refers to the number of types of data.
a. Variety c. Volume
b. Velocity d. Complexity
7. ……… is to simulate human thought processes in a computerized model.
a.Data Science c. Cognitive Computing
b.Adaptive Computing d. Data simulation
8. To be ……. Is to learn as information and goals change in Cognitive Computing.
a.Adaptive c. Interactive
b.Contextual d.None of above
9. ……………. is the systematic study and analysis of various data resources,
understanding the meaning of data
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.Questions & Answers section.

  1. ……… a data that is which is not organized in a pre-defined manner or does not have a pre-defined data model, thus it is not a good fit for a mainstream relational database. a. Structured data c. Semi-structured data b. unstructured data
  2. ……………. helps organizations understand the relative growth of their big data and how quickly that data reaches sourcing users, applications and systems. a. Variety c. Volume b. Velocity d. Complexity
  3. …… is information that does not reside in a rational database but that have some organizational properties that make it easier to analyze. a. Semi- Structured data c. Quasi-structured data b. unstructured data d. Structured Data
  4. …… is a data whose elements are addressable for effective analysis. It has been organised into a formatted repository that is typically a database. a. Structured Data c. unstructured data b. Quasi-structured data d. Semi- Structured data
  5. Extensible Markup Language [XML] data files is example of ……….. a. Structured Data c. unstructured data b. Quasi-structured data d. Semi- Structured data
  6. …………………refers to the number of types of data. a. Variety c. Volume b. Velocity d. Complexity
  7. ……… is to simulate human thought processes in a computerized model. a.Data Science c. Cognitive Computing b.Adaptive Computing d. Data simulation
  8. To be ……. Is to learn as information and goals change in Cognitive Computing. a.Adaptive c. Interactive b.Contextual d.None of above
  9. ……………. is the systematic study and analysis of various data resources, understanding the meaning of data

a. Data c. Data Science b. Data Warehouses d. Big Data

  1. ………………provides subject matter expertise for analytical techniques, data modeling, and applying valid analytical techniques to given business problems a. Data Scientist c. Data Engineer b. Business User d. Project Sponsor
  2. ……………… Is data science activity that includes Collection of data and knowledge, acquisition techniques ,Storage of data and Accessing stored data a. Data Flow b. Data Analytics c. Data Curation
  3. Which of the following focuses on the discovery of (previously) unknown properties on the data? a. Data mining c. Big Data b. Data wrangling d. Machine Learning
  4. …………..…. Is data science activity that includes Statistical analysis, Simulation and modeling, Visual techniques, Application specific and methods a. Data Flow b. Data Analytics c. Data Curation
  5. ……………... Is data science activity that includes Data cleaning, Presentation and Data description a. Data Flow b. Data Analytics c. Data Curation
  6. The term big data refers to: a. Structured data only c.Unstructured data only b.Structured and unstructured data d.None of above
  7. Which of the following is not one of the three Vs? a.Volume c.Velocity b.Variation d.Variety
  8. Information can be converted into ……... about historical patterns and future trends. a. Data c. Information b. Knowledge d. Patterns 18.True/ False: XML data can be considered as unstructured data. False 19.True/ False Relational data can be considered as semi-structured data

a) Data Analysis b) Data Science c) Descriptive Analytics d) None of the mentioned

  1. Which of the following characteristic of big data is relatively more concerned to data science? a) Velocity b) Variety c) Volume d) None of the Mentioned
  2. Which of the following best describes the principal goal of data science? a) To collect and archive exhaustive data sets from various source systems for corporate record keeping uses. b) To mine and analyze large amounts of data in order to uncover information that can be leveraged for operational improvements and business gains. c) To prepare data for analysts to use as part of analytics applications. 31.What is that a. ………………it is expensive to manage and hard to extract. Big data b. ………………it is a multidisciplinary field that manages, manipulates, extracts, and interprets knowledge from huge data. Data Science c. …………….. it is highly organized and easily understood by machine language structured data d. ………………it is the use of computerized models to simulate human thinking process to solve complicated problems that characterized by uncertainty Cognitive computing e. ………………..it can describe high velocity data, with rapid data ingestion and near real time analysis. Big data 32.Given the fact that Facebook has 60 TB of daily logs and the cost of 1 TB of disk: $35, how much is the cost to store this data? 60*35 = 2100$ 33.When you know that Time to read 1 TB disk: 3 hrs how many hours does Facebook need to read their daily logs? 3 * 60 = 180hrs 34.Arrange the following Data Volumes from the largest size to the smallest. a. 178 MB

b. 200 KB c. 30 TB 30 TB > 178 MB > 200 KB 35.Data scientists make big data in structured format even if it is unstructured. a. True b. False