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Chapter 08 Understanding Big Data and Its Impact on Business True / False Questions 1.Big data is a collection of large, complex data sets, including structured and unstructured data, that cannot be analyzed using traditional database methods and tools. True False 2.The four common characteristics of big data are variety, veracity, volume, velocity. True False 3.Variety includes different forms of structured and unstructured data. True False 4.Veracity includes the uncertainty of data, including biases, noise, and abnormalities. True False 5.Volume includes the scale of data. True False 6.Velocity includes the analysis of streaming data as it travels around the Internet. True False 7. Velocity includes different forms of structured and unstructured data. True False 8.Volume includes the uncertainty of data, including biases, noise, and abnormalities. True False 9.Distributed computing processes and manages algorithms across many machines in a computing environment. True False 8-1 Copyright © 2018 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill Education. 29 June 2021 6 min read IBM Cloud Education, IBM Cloud Education All data is not created equal. Some data is structured, but most of it is unstructured. Structured and unstructured data
is sourced, collected and scaled in different ways, and each one resides in a different type of database. In this article, we’ll take a deep dive into both types so that you can get the most out of your data. What is structured data?Structured data — typically categorized as quantitative data — is highly organized and easily decipherable by machine learning algorithms. Developed by IBM in 1974, structured query language (SQL) is the programming language used to manage structured data. By using a relational (SQL) database, business users can quickly input, search and manipulate structured data. Pros and cons of structured dataExamples of structured data include dates, names, addresses, credit card numbers, etc. Their benefits are tied to ease of use and access, while liabilities revolve around data inflexibility: Pros
Cons
Structured data tools
Use cases for structured data
What is unstructured data?Unstructured data, typically categorized as qualitative data, cannot be processed and analyzed via conventional data tools and methods. Since unstructured data does not have a predefined data model, it is best managed in non-relational (NoSQL) databases. Another way to manage unstructured data is to use data lakes to preserve it in raw form. The importance of unstructured data is rapidly increasing. Recent projections indicate that unstructured data is over 80% of all enterprise data, while 95% of businesses prioritize unstructured data management. Pros and cons of unstructured dataExamples of unstructured data include text, mobile activity, social media posts, Internet of Things (IoT) sensor data, etc. Their benefits involve advantages in format, speed and storage, while liabilities revolve around expertise and available resources: Pros
Cons
Unstructured data tools
Use cases for unstructured data
What are the key differences between structured and unstructured data?While structured (quantitative) data gives a “birds-eye view” of customers, unstructured (qualitative) data provides a deeper understanding of customer behavior and intent. Let’s explore some of the key areas of difference and their implications:
What is semi-structured data?Semi-structured data (e.g., JSON, CSV, XML) is the “bridge” between structured and unstructured data. It does not have a predefined data model and is more complex than structured data, yet easier to store than unstructured data. Semi-structured data uses “metadata” (e.g., tags and semantic markers) to identify specific data characteristics and scale data into records and preset fields. Metadata ultimately enables semi-structured data to be better cataloged, searched and analyzed than unstructured data.
The future of dataRecent developments in artificial intelligence (AI) and machine learning (ML) are driving the future wave of data, which is enhancing business intelligence and advancing industrial innovation. In particular, the data formats and models covered in this article are helping business users to do the following:
Furthermore, smart and efficient usage of data formats and models can help you with the following:
Structured and unstructured data and IBMWhether you are a seasoned data expert or a novice business owner, being able to handle all forms of data is conducive to your success. By leveraging structured, semi-structured and unstructured data options, you can perform optimal data management that will ultimately benefit your mission. To better understand data storage options for whatever kind of data best serves you, check out IBM Cloud Databases. Follow IBM CloudBe the first to hear about news, product updates, and innovation from IBM Cloud. Email subscribeRSS Related ArticlesBe the first to hear about news, product updates, and innovation from IBM Cloud Which big data term describes different forms of structured and unstructured data multiple choice question?Velocity includes different forms of structured and unstructured data. Volume includes the uncertainty of data, including biases, noise, and abnormalities.
Is big data structured or unstructured?Big Data includes huge volume, high velocity, and extensible variety of data. These are 3 types: Structured data, Semi-structured data, and Unstructured data. Structured data is data whose elements are addressable for effective analysis. It has been organized into a formatted repository that is typically a database.
Which characteristic of big data describes different types of datasets that include both structured and unstructured data?Variety is one of the important characteristics of big data. The traditional types of data are structured and also fit well in relational databases. With the rise of big data, the data now comes in the form of new unstructured types.
What is unstructured data in big data?Unstructured simply means that it is datasets (typical large collections of files) that aren't stored in a structured database format. Unstructured data has an internal structure, but it's not predefined through data models. It might be human generated, or machine generated in a textual or a non-textual format.
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