Sri Raghavendra Educational Institutions Society (R)

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

www.skit.org.in

Title: What is Big Data

CO addressed: CO1

Course: BDA

Presented by: Mr. P. Kiran Kumar

Department: ISE

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28/07/2026

/skit.org.in

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

What is Big Data?

Big data refers to extremely large and complex collections of data that are difficult to process using traditional databases and software. Organizations analyze big data to discover patterns, trends, and insights that help them make better decisions.

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• Big Data includes structured, semi-structured, and unstructured data generated from multiple sources.
• It requires specialized storage, processing, and analytics technologies to handle its scale and complexity.
• The primary goal of Big Data is to extract meaningful insights that support better decision-making, innovation, and business growth.

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28/07/2026

/skit.org.in

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

Characteristics of Big Data:

1. Volume (Amount of Data)

• Refers to the enormous quantity of data generated every second.
• Measured in Terabytes (TB), Petabytes (PB), and Exabytes (EB).
• Example: Social media platforms like Instagram and Facebook generate billions of posts, photos, and videos daily.

2. Velocity (Speed of Data)

• Refers to the speed at which data is generated, transmitted, and processed.
• Many applications require real-time or near real-time processing.
• Example: Stock market trading, online payment systems, and IoT sensors.

3. Variety (Different Types of Data)

• Refers to the different formats of data collected.
• Structured Data (Databases, Excel sheets)
• Semi-Structured Data (XML, JSON)
• Unstructured Data (Images, Videos, Emails, Audio)
• Example: A shopping website stores customer details, reviews, product images, and videos.

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28/07/2026

/skit.org.in

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

4. Veracity (Data Quality)

• Refers to the accuracy, reliability, and trustworthiness of data.
• Poor-quality or inconsistent data can lead to incorrect decisions.
• Example: Duplicate customer records or fake social media accounts.

5. Value (Business Benefit)

• Refers to the useful insights and benefits obtained from analyzing data.
• The ultimate goal of Big Data is to support better decision-making and innovation.
• Example: Netflix recommends movies based on users' viewing history.

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28/07/2026

/skit.org.in

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

Evolution of Big data:

1960s–1980s: Traditional Data

• Data was stored in paper records and simple databases.
• Mainly structured data (tables and spreadsheets).
• Storage capacity and processing power were limited.

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1990s: Internet Revolution

• Rapid growth of the Internet increased digital data generation.
• Organizations started using Relational Database Management Systems (RDBMS).
• Websites and emails became major sources of data.

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28/07/2026

/skit.org.in

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

2000s: Birth of Big Data

• Social media, e-commerce, and mobile devices generated massive amounts of data.
• Traditional databases struggled to store and process such large datasets.
• Technologies like Apache Hadoop emerged to handle distributed storage and processing.

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2010s–Present: Big Data Era

• Cloud computing, IoT, Artificial Intelligence, and Machine Learning accelerated data growth.
• Organizations use frameworks such as Apache Spark, Hadoop, and NoSQL databases for large-scale analytics.
• Big Data has become essential in healthcare, banking, education, manufacturing, and smart cities.

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28/07/2026

/skit.org.in

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

Why Big Data:

• Massive Data Generation: Billions of devices, websites, and applications generate huge amounts of data every second.
• Traditional Systems are Limited: Conventional databases cannot efficiently store or process extremely large and complex datasets.
• Real-Time Decision Making: Organizations need to analyze data instantly to make quick and informed decisions.
• Business Intelligence: Big Data helps organizations identify trends, customer preferences, and market opportunities.
• Competitive Advantage: Companies use Big Data to improve products, reduce costs, optimize operations, and enhance customer experience.
• Supports AI and Machine Learning: Modern AI applications rely on large volumes of data for training accurate and intelligent models.