Question Paper Solutions of chapter Introduction of Big Data of Big Data Analysis, 8th Semester , Information Technology

Introduction

Big Data Statistics: Big Data Statistics involves the gathering, analysis, and interpretation of large volumes of data from diverse sources, including social media, sensors, online transactions, and digital devices. As businesses increasingly adopt data-driven strategies, the role of big data becomes more crucial.

By applying advanced statistical methods and leveraging powerful computing technologies, organizations can uncover valuable patterns, trends, and insights that fuel innovation and enhance competitive positioning. The growth of technologies such as machine learning, artificial intelligence, and cloud computing has enabled more efficient processing and analysis of massive datasets, leading to improvements in customer experience, operational efficiency, and strategic decision-making.

The global market for big data analytics is expected to grow rapidly, with sectors like healthcare, finance, retail, and manufacturing leading the way in adopting big data solutions.

The Big

## Overview

The Big is a dataset for object detection tasks - it contains Fire Smoke annotations for 2,247 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The global tourism big data analytics market (2025 USD 18.4 billion) is projected to double in size to USD 41.9 billion by 2035, growing at a CAGR of 8.6%. Tourism stakeholders are moving away from post-trip surveys or guesswork. Instead, they are leveraging real-time analytics to gain insights into travelerbehavior, streamline operations and create hyper-personalized experiences.

Country-wise Visitor Data Integration Projects

Big Dataset Food

## Overview

Big Dataset Food is a dataset for object detection tasks - it contains Food annotations for 528 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Natural history museums often contain large collections of the same species and therefore, are a resource for studying intraspecific variation. This module uses 172 images of rock pocket mouse skulls from the UTEP Biodiversity Collections to introduce students to collecting data from images and principles of basic statistics. This module resource focuses on immersing students into the development of study design, analysis, discussion, and communication without overwhelming them. Students enter their data into a Google sheet app that combines data entry, statistical analysis, and presentation all in one. The collaborative framework asks students to work together, share resources, and develop their own questions while learning the principles behind taking measurements from images of museum specimens.

Introduction

Global Big Data in Healthcare Market size is expected to be worth around USD 145.8 Billion by 2033 from USD 42.2 Billion in 2023, growing at a CAGR of 13.2% during the forecast period from 2024 to 2033.

Big data in healthcare encompasses vast amounts of diverse, unstructured data sourced from medical journals, biometric sensors, electronic medical records (EMRs), Internet of Medical Things (IoMT), social media platforms, payer records, omics research, and data repositories. Integrating this unstructured data into traditional systems presents considerable challenges, primarily in data structuring and standardization. Effective data structuring is essential for ensuring compatibility across systems and enabling robust analytical processes.

However, advancements in big data analytics, artificial intelligence, and machine learning have significantly enhanced the ability to convert complex healthcare data into actionable insights. These advancements have transformed healthcare, driving informed decision-making, enabling early and accurate diagnostics, facilitating precision medicine, and enhancing patient engagement through digital self-service platforms, including online portals, mobile applications, and wearable health devices.

The role of big data in pharmaceutical R&D has become increasingly central, as analytics tools streamline drug discovery, accelerate clinical trial processes, and identify potential therapeutic targets more efficiently. The demand for business intelligence solutions within healthcare is rising, fueled by the surge of unstructured data and the focus on developing tailored treatment protocols. As a result, the global market for big data in healthcare is projected to grow steadily during the forecast period.

Lbw Big

## Overview

Lbw Big is a dataset for object detection tasks - it contains Ball In Air annotations for 691 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The Big Data Services market is booming, projected to reach $32.51 billion by 2025 with a 27.81% CAGR. Discover key trends, drivers, and restraints shaping this rapidly evolving sector, including insights into cloud adoption, regional market shares, and leading companies. Recent developments include: May 2023 : Microsoft has introduced Microsft fabric an softend-to-end, Unified Analytics Platform, which enables organisations to integrate all data and analytical tools they need, Where By making it possible for data and business professionals to unlock their potential, as well as lay the foundation for an era of Artificial Intelligence, fabric creates a single unified product that brings together technologies like Azure Data Factory, Azure Synapse Analytics, and Power BI., November 2022: Amazon Web Services, Inc. (AWS) released five new features in its database and analytics portfolios. These updates enable users to manage and analyze data at a petabyte scale more efficiently and quickly, simplifying the process for customers to operate the high-performance database and analytics workloads at scale., October 2022: Oracle introduced the Oracle Network Analytics Suite, which includes a new cloud-native portfolio of analytics tools. This suite enables operators to make more automated and informed decisions regarding the performance and stability of their entire 5G network core by combining network function data with machine learning and artificial intelligence.. Key drivers for this market are: Increasing Cloud Adoption And Rise In The Data Volume Generated, Increasing Demand For Improving Organization's Internal Efficiency; Growing Adoption of Private Cloud. Potential restraints include: Data Security Concerns. Notable trends are: Growing Adoption of Private Cloud is Driving the Market.

YOLO Big Dataset

## Overview

YOLO Big Dataset is a dataset for object detection tasks - it contains Lol annotations for 245 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

According to Cognitive Market Research, the global Big Data marketsize is USD 40.5 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 12.9% from 2024 to 2031. Market Dynamics of Big Data Market

Key Drivers for Big Data Market

Increasing demand for decision-making based on data - One of the main reasons the Big Data market is growing is due to the increasing demand for decision-making based on data. Organizations understand the strategic benefit of using data insights to make accurate and informed decisions in the current competitive scenario. This change marks a break from conventional decision-making paradigms as companies depend more and more on big data analytics to maximize performance, reduce risk, and open up prospects. Real-time processing, analysis, and extraction of actionable insights from large datasets enables businesses to react quickly to consumer preferences and market trends.
The increasing need to maximize performance, reduce risk, and open up prospects is anticipated to drive the Big Data market's expansion in the years ahead.

Key Restraints for Big Data Market

The lack of integrator and interoperability poses a serious threat to the Big Data industry.
The market also faces significant difficulties because of the realization of its full potential.

Introduction of the Big Data Market

Big data software is a category of software used for gathering, storing, and processing large amounts of heterogeneous, dynamic data produced by humans, machines, and other technologies. It is concentrated on offering effective analytics for extraordinarily massive datasets, which help the organization obtain a profound understanding by transforming the data into superior knowledge relevant to the business scenario. Additionally, the programmer assists in identifying obscure correlations, market trends, customer preferences, hidden patterns, and other valuable information from a wide range of data sets. Due to the widespread use of digital solutions in sectors such as finance, healthcare, BFSI, retail, agriculture, telecommunications, and media, data is increasing dramatically on a worldwide scale. Smart devices, soil sensors, and GPS-enabled tractors generate massive amounts of data. Large data sets, such as supply tracks, natural trends, optimal crop conditions, sophisticated risk assessment, and more, are analyzed in agriculture through the application of big data analytics.

Question Paper Solutions of chapter Introduction to Hadoop and Hadoop Architecture of Big Data Analysis, 8th Semester , Applied Electronics and Instrumentation Engineering

Introduction

Big Data Statistics: By 2025, the world is expected to generate an unimaginable 181 zettabytes of data, representing an average annual growth rate of 23.13%, with 2.5 quintillion bytes created daily. This indicates an influx of roughly 29 terabytes every second, yes, you read it right.

While over 97% of businesses are now investing in Big Data, only about 40% are truly effective at leveraging analytics. The global Big Data analytics market, valued at approximately $348.21 billion in 2024, is on a trajectory to reach over $961.89 billion by 2032, exhibiting a robust CAGR of 13.5%.

The dominance of some unstructured data, which constitutes about 90% of all global data, underscores the complex statistical challenge. Industries, from healthcare, which could save up to $300 billion annually in the US alone through data initiatives, to entertainment, where Netflix saves an estimated $1 billion per year using data-driven recommendation algorithms, which are being fundamentally changed by Big Data. So, let's dive deeper into this stats article discussing everything about big data from its current insights to future forecasts. Let’s get started.

France Hadoop Big Data Analytics Market is expected to grow during 2025-2031

Card Big

## Overview

Card Big is a dataset for object detection tasks - it contains Card annotations for 685 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

Lithuania Big Data Analytics Market is expected to grow during 2025-2031

Global Artificial Intelligence in Big Data Analysis Market is segmented by Application (Big Data_ Data Science_ Business Intelligence_ Marketing_ Research), Type (Data Mining_ Machine Learning_ Deep Learning_ Natural Language Processing_ Predictive Analytics), and Geography (North America_ LATAM_ West Europe_Central & Eastern Europe_ Northern Europe_ Southern Europe_ East Asia_ Southeast Asia_ South Asia_ Central Asia_ Oceania_ MEA)

Title: IMDB & TMDB Movie Metadata Big Dataset (>1M)

Subtitle: A Comprehensive Dataset Featuring Detailed Metadata of Movies (IMDB, TMDB). Over 1M Rows & 42 Features: Metadata, Ratings, Genres, Cast, Crew, Sentiment Analysis and many more...

Detailed Description:

Overview: This comprehensive dataset merges the extensive film data available from both IMDB and TMDB, offering a rich resource for movie enthusiasts, data scientists, and researchers. With over 1 million rows and 42 detailed features, this dataset provides in-depth information about a wide variety of movies, spanning different genres, periods, and production backgrounds.

File Information: 1. File Size: ≈ 1GB 2. Format: CSV (Comma-Separated Values)

Column Descriptors/Key Features: 1. ID: Unique identifier for each movie. 2. Title: The official title of the movie. 3. Vote Average: Average rating received by the movie. 4. Vote Count: Number of votes the movie has received. 5. Status: Current status of the movie (e.g., Released, Post-Production). 6. Release Date: Official release date of the movie. 7. Revenue: Box office revenue generated by the movie. 8. Runtime: Duration of the movie in minutes. 9. Adult: Indicates if the movie is for adults. 10. Genres: List of genres the movie belongs to. 11. Overview Sentiment: Sentiment analysis of the movie's overview text. 12. Cast: List of main actors in the movie. 13. Crew: List of key crew members, including directors, producers, and writers. 14. Genres List: Detailed genres in list format. 15. Keywords: List of relevant keywords associated with the movie. 16. Director of Photography: Name of the cinematographer. 17. Producers: Names of the producers. 18. Music Composer: Name of the music composer.

Additional Features:

1. Unnamed 0: Index column.
2. Star1, Star2, Star3, Star4: Names of the top-billed stars.
3. Writer: Name(s) of the writer(s).
4. Original Language: Original language of the movie.
5. Original Title: Original title if different from the main title.
6. Popularity: Popularity score of the movie.
7. Budget: Budget allocated for the movie.
8. Tagline: Promotional tagline of the movie.
9. Production Companies: Companies involved in the production.
10. Production Countries: Countries where the movie was produced.
11. Spoken Languages: Languages spoken in the movie.
12. Homepage: Official website of the movie.
13. IMDB ID: Unique identifier on IMDB.
14. TMDB ID: Unique identifier on TMDB.
15. Video: Indicates if there is a video associated.
16. Poster Path: Path to the movie poster image.
17. Backdrop Path: Path to the backdrop image.
18. Release Year: Year the movie was released.
19. Collection Name: Name of the collection the movie belongs to.
20. Collection ID: Unique identifier for the collection.
21. Genres ID: Unique identifier for the genres.
22. Original Language Code: Code for the original language.
23. Overview: Brief summary of the movie.
24. All Combined Keywords: Combined keywords in a single field.

Potential Use Cases: - Sentiment Analysis: Analyze audience sentiment towards movies based on reviews and ratings. - Recommendation Systems: Build models to recommend movies based on user preferences and viewing history. - Market Analysis: Study trends in the movie industry, including genre popularity and revenue patterns. - Content Analysis: Investigate the thematic content and diversity of movies over time. - Data Visualization: Create visual representations of movie data to uncover hidden insights.

Introduction

The Global Big Data Security Market is poised for exceptional growth, expected to reach USD 300.9 billion by 2034, up from USD 30.8 billion in 2024, at a staggering CAGR of 25.6%. This surge is driven by the increasing volume of data generated globally, with businesses and governments seeking advanced security solutions to protect sensitive information. As data breaches and cyber threats continue to rise, the demand for robust data security systems is intensifying, making it a critical area of investment for organizations worldwide.

According to Cognitive Market Research, the global Hadoop big data analytics market size is USD 12.8 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 13.0% from 2024 to 2031. Market Dynamics of Hadoop Big Data Analytics Market Key Drivers for Hadoop Big Data Analytics Market Increasing the use of internet transactions- The market for Hadoop big data analytics is expanding because more and more transactions are being made online. Digital financial transactions are any monetary transfers that take place through digital devices or internet-based sites. The huge amounts of data created throughout interactions are processed, managed, and analyzed in an effective and accessible manner using Hadoop and large-scale analytics, which are also used in online payments to improve speed, safety, and customization of payment options. As a result, the Hadoop big data analytics industry is expanding due to the growing use of online payments. The global pharmaceutical industry's adoption of Hadoop big data analytics is driving the industry's expansion. Key Restraints for Hadoop Big Data Analytics Market The growing internet risk is the main factor impeding the worldwide Hadoop Big Data Analytics industry's expansion. Inadequate recognition in low-income nations is also hampering the market growth. Introduction of the Hadoop Big Data Analytics Market Hadoop big data analytics is the practice of utilizing the Hadoop computing system to examine massive amounts of data in all its forms. Hadoop is an operating system for storing, processing, and evaluating large amounts of diverse data used for large-scale processing that is portable, inexpensive, and flexible. Because of its capacity to effectively manage and evaluate massive amounts of statistics, it is utilized for an extensive number of applications in a variety of businesses and areas. The goal of this technique is to help various businesses stay competing in the demand and obtain more information about the business sector. The need for a single, standardized infrastructure for maintaining data will support the expansion of the Hadoop big data analytics market.