Cognitive Class: Big Data 101 Exam Answers 2021

Cognitive Class: Big Data 101 Exam Answers 2021

Big data is an area that deals with methods for analysing, systematically extracting information from, or otherwise dealing with data sets that are too large or complex for conventional data-processing application software to handle. Data with a lot of fields (columns) has more predictive strength, while data with a lot of attributes or columns has a higher false discovery rate. Data capture, storage, processing, search, sharing, transition, visualisation, querying, updating, information protection, and data source are all problems in big data analysis. The three main concepts of big data were originally associated with three key concepts: volume, variety, and velocity.

1. What is the process of cleaning and analyzing data to derive insights and value from it?

  1. Machine Learning
  2. Exploratory Research
  3. Data Science
  4. Predictive Modeling
  5. Decision Trees

2. What is the search engine used by Walmart?

  1. JSON
  2. HBase
  3. ZooKeeper
  4. Polaris
  5. Poisson

3. An example of visualizing Big Data is___________?

  1. Hadoop
  2. Integration
  3. Agile Governance
  4. Temperature on a map
  5. Closing your eyes and imagining it

4. What is the term used to describe an holistic approach that takes into account all available and meaningful information about a customer to drive better engagement, revenue and long term loyalty?

  1. Enhanced 360-degree view
  2. Big Data Exploration
  3. End to End
  4. Operations Analysis
  5. Customer Retention

5. What can help organizations to find new associations or uncover patterns and facts to significantly improve intelligence, security and law enforcement?

  1. Using local servers
  2. Analyzing data in-motion and at rest
  3. Satellite data
  4. GPS coordinates
  5. Using XML

6. In Operations Analysis, we focus on what type of data?

  1. Location Data
  2. Machine Data
  3. Binary Data
  4. Social Media Data
  5. Structured Data

7. What is a method of storing data to support the analysis of originally disparate sources of data?

  1. Data Lakes
  2. Data Mining
  3. Predictive Analytics
  4. Data Analytics
  5. Deep Learning

8. Data Warehouses provide online analytic processing: True/False

  1. False
  2. True

9. What does ‘OLAP’ stand for?

  1. Online Analytical Prediction
  2. Online Analytical Platform
  3. Online Analytical Processing
  4. Online Advanced Prediction
  5. Online Advanced Programming

10. What is a common use of big data that is used by companies like Netflix, Spotify, Facebook and Amazon?

  1. Recommendation Engines
  2. Data Lakes
  3. Clusters
  4. The Cloud
  5. Sensors

11. Is one byte binary? True/False

  1. False
  2. True

12. What has highly contributed to the launch of the Big Data era?

  1. Clusters
  2. Spark
  3. Cloud Computing
  4. Zetabytes
  5. Data Scientists

13. A data scientist is a person who is qualified to derive insights from data by using skills and experience from computer science, business or science, and statistics. True/False

  1. False
  2. True

14. ‘HDFS’ stands for ____________________?

  1. Hadoop Data Fraud System
  2. High Data File System
  3. Hadoop Distributed File System
  4. High Distribution Frequency System
  5. High Definition Frequency Sensors

15. Data privacy is a critical part of the big data era. Businesses and individuals must give great thought to how data is _____________________________.

  1. collected, retained, used, and disclosed
  2. bought, sold, stored and analyzed
  3. secured, sold, downloaded and uploaded
  4. aggregated, compiled, saved and stored
  5. stored, analyzed, read and written

16. In the Hadoop framework, a rack is a collection of ____________?

  1. Yarn
  2. Networks
  3. Bits
  4. Nodes
  5. Distributed files

17. What is a method of storing data to support the analysis of originally disparate sources of data?

  1. Spark
  2. Data Warehouse
  3. Yarn
  4. Data Repository
  5. Data Lake

18. The Hadoop framework is mostly written in the Java programming language. True/False

  1. False
  2. True

19. What is the term referring to a database that must be processed by means other than just the SQL Query Language.

  1. Spark
  2. NoSQL
  3. Python
  4. SQL
  5. Hadoop

20. Name one of the drivers of Volume in the Big Data Era?

  1. Scalable infrastructure
  2. An increase in cost to store data
  3. Competitive advantage
  4. FinTech
  5. Research and development

21. Value from Big Data can be _____________?

  1. Profits
  2. Veracity
  3. Petabytes
  4. Technical ability
  5. Infrastructure

22. In the video, 2.5 Quintillion Bytes of data are equivalent to how many blue ray DVDs?

  1. 1 Billion
  2. 10 million
  3. 100 million
  4. 5 million
  5. 1 Trillion

23. How many petabytes make up an Exabyte

  1. 32
  2. 2020
  3. 64
  4. 1024
  5. 8

24. What is an example of a source of Semi-Structured Big data?

  1. Cameras files
  2. Relational databases
  3. Satellite files
  4. Spreadsheet file
  5. JSON files

25. When is it estimated that the data we create and copy will reach around 35 zettabytes?

We have already surpassed this mark

  1. 2050
  2. 2030
  3. 2040
  4. 2020

The process of systematically applying statistical and/or logical methods to explain and demonstrate, condense and recap, and analyse data is known as data analysis. Indeed, in the data collection process, researchers look for trends in observations (Savenye, Robinson, 2004). Cleaning, evaluating, understanding, and visualising data to uncover useful insights that make smarter and more efficient business decisions is known as data analysis. Data analysis tools derive valuable information from business data and aid in the data analysis process.

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