Big Data and Industrial Revolutions Overview
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Questions and Answers

What is the primary function of Apache Hadoop's storage system?

  • To provide a schema for relational databases
  • To store small amounts of data efficiently
  • To split and distribute large data across nodes (correct)
  • To process data in real time

Which programming model is primarily associated with distributed data processing in Big Data technologies?

  • Event-Driven Processing
  • Sequential Processing
  • Object-Oriented Processing
  • MapReduce (correct)

What advantage does NoSQL databases provide over traditional relational databases?

  • Enhanced data normalization
  • Faster transaction processing
  • Ability to handle unstructured data efficiently (correct)
  • Support for rigid data schemas

How does Apache Spark improve upon the traditional MapReduce engine?

<p>By offering faster processing speeds up to one hundred times that of MapReduce (B)</p> Signup and view all the answers

What role has become trending and emerging in the market due to the rise of Big Data technologies?

<p>Data Scientist/Analyst (D)</p> Signup and view all the answers

What percentage of all informatics data does structured data represent?

<p>5 to 10% (C)</p> Signup and view all the answers

Which type of data is characterized by the ability to fit into a strict data model structure?

<p>Structured Data (C)</p> Signup and view all the answers

What is a key characteristic of unstructured data?

<p>Represents around 80% of data (C)</p> Signup and view all the answers

What distinguishes semi-structured data from structured data?

<p>It lacks a strict data model structure (A)</p> Signup and view all the answers

What does the term 'Big Data' refer to?

<p>Collection of data sets too large and complex for traditional processing (B)</p> Signup and view all the answers

Which of the following does not represent a type of digital data?

<p>Encoded Data (C)</p> Signup and view all the answers

What is implied by the statement 'DATA is the NEW OIL'?

<p>Data needs refinement to be useful (A)</p> Signup and view all the answers

Which technique is NOT typically associated with data mining?

<p>Random Sampling (D)</p> Signup and view all the answers

What are the characteristics that define 'Big Data'?

<p>Volume, Velocity, Variety, Veracity, and Variability (A)</p> Signup and view all the answers

Which of the following is NOT a challenge associated with Big Data?

<p>Data needs to be standardized across all platforms (B)</p> Signup and view all the answers

Which factor contributes to the growth of Big Data?

<p>Increase in storage capacities (D)</p> Signup and view all the answers

What is one benefit of combining Big Data with high-powered analytics?

<p>It enables the recalculation of entire risk portfolios in minutes (D)</p> Signup and view all the answers

How much data is created every day?

<p>2.5 quintillion bytes (A)</p> Signup and view all the answers

Which of the following is NOT an importance of Big Data?

<p>Elimination of competition (B)</p> Signup and view all the answers

From where can data that contributes to Big Data be sourced?

<p>Various fields including science, industry, and legacy systems (D)</p> Signup and view all the answers

What is a primary reason traditional data management technologies were inadequate for handling Big Data?

<p>They cannot manage the scale and diversity of data. (A)</p> Signup and view all the answers

Which sector is NOT typically mentioned as a user of Big Data technology?

<p>Telecommunication (D)</p> Signup and view all the answers

What is the primary goal of Big Data analytics?

<p>To identify new opportunities and improve business operations (B)</p> Signup and view all the answers

In predictive analytics, what distinguishes supervised analytics from unsupervised analytics?

<p>Supervised analytics uses historical data to make predictions. (B)</p> Signup and view all the answers

What type of data model is NOT mentioned in the overview of Big Data stores?

<p>Relational (C)</p> Signup and view all the answers

Which of the following is a characteristic of Business Intelligence (BI)?

<p>It is a technology-driven process for data analysis. (D)</p> Signup and view all the answers

What is NOT a function of descriptive analysis?

<p>Making predictions about future trends (D)</p> Signup and view all the answers

Which technology is part of the Big Data storage overview?

<p>Hadoop Distributed File System (B)</p> Signup and view all the answers

What is an example of unsupervised analytics?

<p>Segmenting students based on exam scores and attendance (D)</p> Signup and view all the answers

Flashcards

What is Data?

Any set of characters that has been collected and translated for a specific purpose, usually analysis. It can include text, numbers, pictures, sound, or video.

What is Digital Data?

Discrete, discontinuous representations of information or work, often expressed in binary language.

Structured Data

Data that resides in a fixed field within a record or file. It follows the ACID properties, ensuring consistency and reliability.

Unstructured Data

Data that doesn't fit easily into a structured format. It's often messy and unorganized.

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Semi-structured Data

A cross between structured and unstructured data. It has some organizational properties but lacks the strict structure of a database.

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What is Big Data?

The collection of data sets so vast and complex that traditional data processing tools struggle to handle it.

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What is the Composition of Data?

A data set's structure, type, and nature. It helps understand the organization and composition of data.

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What is the Condition of Data?

The state of the data and whether it needs to be cleansed or processed before analysis.

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Big Data

The enormous amount of data that is generated and collected every day. This data often comes from various sources, including social media, sensors, online transactions, and more.

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Velocity

The speed at which data is generated and processed. Big data needs to be analyzed quickly to be useful.

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Variety

Refers to the different types of data that are collected, including structured data (tables, spreadsheets), unstructured data (text, images), and semi-structured data.

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Veracity

The trustworthiness and reliability of the data. It's important to ensure that data is accurate and reliable for effective analysis.

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Variability

Data that is constantly changing, requiring flexible and dynamic analysis techniques. This includes real-time data changes and updates.

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Business Intelligence

Analyzing big data allows businesses to find hidden patterns and insights, leading to improvements in decision-making, product development, and customer service.

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Cost Reductions

Big data technologies and techniques can help businesses reduce costs by optimizing operations, predicting demand, and even preventing potential issues.

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Time Reductions

Big data can help speed up processes by automating tasks, providing real-time insights, and optimizing workflows.

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Apache Hadoop

A free software framework designed to store massive amounts of data in a cluster, using the Hadoop Distributed File System (HDFS) for storage and MapReduce for processing.

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NoSQL Databases

Databases that handle unstructured data without a fixed schema, allowing for greater flexibility in storing and retrieving information.

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Apache Spark

An engine for processing big data within the Hadoop ecosystem, known for its speed and efficiency, often up to 100 times faster than traditional MapReduce.

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R Programming Language

An open-source programming language and software environment designed for statistical computing. Popular for its statistical analysis capabilities.

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Data Scientist/Analyst

A profession involving the analysis and interpretation of data to extract insights and knowledge, often used for decision-making and problem-solving.

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What is Big Data Analytics?

The process of examining large datasets to discover patterns, trends, and unknown correlations for informed decision-making.

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Who uses Big Data Technology?

Organizations like banks, governments, educational institutions, healthcare providers, manufacturers, and retailers leverage big data technology to gain insights from vast amounts of information.

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What are some Big Data store models?

Data models that include key-value pairs, graph structures, document formats, and column-family systems.

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What is Business Intelligence (BI)?

A technology-driven process of analyzing data to present actionable information for business decision-making by executives and managers.

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What is Descriptive Analysis?

Describing and summarizing data to highlight patterns and trends, revealing what has happened.

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What is Predictive Analysis?

Predicting future probabilities and trends based on past data, using statistical models and algorithms.

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What is Supervised Predictive Analytics?

Predictive analytics where historical data about an event is known, allowing for training and testing of models to predict future outcomes.

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What is Unsupervised Predictive Analytics?

Predictive analytics where historical data about an event is unknown, requiring pattern discovery within the data to make predictions.

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Study Notes

Big Data Overview

  • Big data is a collection of data sets, too large and complex for traditional data processing tools.
  • Key characteristics of big data include volume, velocity, variety, veracity, and variability (5Vs).
  • Volume refers to the sheer size of the data.
  • Velocity describes the speed at which data is generated.
  • Variety encompasses the different types and formats of data (structured, unstructured, semi-structured data).
  • Veracity relates to the trustworthiness and accuracy of the data.
  • Variability signifies the inconsistent flow and quality of data.

Industrial Revolutions

  • The 1st Industrial Revolution (18th Century) was steam engine based mechanization.
  • The 2nd Industrial Revolution (Early 19-20th Century) used electricity and mass production.
  • The 3rd Industrial Revolution (Latter Half of the 20th Century) focused on computer/internet technologies.
  • The 4th Industrial Revolution (Early 21st Century) uses big data, AI and IoT, hyperconnectivity.

Data Types

  • Data is any set of characters translated for analysis.
  • It includes text, numbers, images, audio, and video.
  • Structured data resides in fixed fields within records/files, supporting ACID properties. Only 5 to 10% of informatics data.
  • Unstructured data cannot be readily categorized and represents approximately 80% of data.
  • Semi-structured data sits between structured and unstructured—it has organizational properties making analysis easier but lacks a strict model structure.

Big Data Characteristics

  • Data size and complexity make it challenging for standard database management tools.
  • Data movement rate is often too fast for standard architectures.
  • Data frequently lacks structure, coming in many different formats.
  • Data trustworthiness can vary.
  • The data's inconsistency of flow and quality can make it difficult to process.

Big Data Enablers

  • Increased storage capacities.
  • Enhanced processing power.
  • Availability of data sources.

Big Data Sources

  • Science: Medical imaging, sensor data, genome sequencing, weather data, satellite feeds.
  • Industry: Finance, pharmaceutical, manufacturing, insurance, online retail.
  • Legacy: Sales data, customer behavior data, product databases, accounting data.
  • Systems: Log files, status feeds, activity stream, network messages, spam filters.

7Vs of Big Data

  • Volume: Data scale.
  • Velocity: Data processing—batch and stream.
  • Variety: Data heterogeneity—structured, semi-structured, unstructured.
  • Veracity: Data quality and accuracy.
  • Variability: Data flow inconsistency.
  • Visualization: Data readability.
  • Value: Data usefulness in decision-making.

Big Data Analytics

  • Examining large data sets to identify patterns, trends, and correlations for faster and more informed decision-making.
  • Includes Descriptive, Predictive, and Prescriptive analytics.

Big Data Tools/Technologies

  • Hadoop: Java-based framework for large-scale data storage and processing in clusters.
  • HDFS (Hadoop Distributed File System): Hadoop's storage system.
  • NoSQL: Non-relational databases—good for handling unstructured data, providing high performance.
  • Apache Spark: A fast engine for processing big data, much faster than the standard Hadoop model.
  • R: Programming language and environment for statistical computing and graphics support in analytics.
  • Cloud Platforms (e.g., Amazon Web Services, Microsoft Azure): Platform for hosting and processing big data.

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Description

This quiz covers the essentials of big data, including its key characteristics known as the 5Vs: volume, velocity, variety, veracity, and variability. Additionally, it explores the four industrial revolutions, detailing the technological advancements that have shaped modern industry. Test your knowledge on these critical topics that define our technological landscape.

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