MBA_IM_unit 3_week 8_seq 4_Big data_magesh

Apr 18, 2026 02:36 · 6:45 · English · Whisper Turbo · 1 Altofalantes

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0:00

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

Welcome to the session on Big Data. Objective. In this session, we will understand about Big Data in Information Systems. Introduction to Big Data. Definition. Large, complex data sets that traditional data processing software can't handle. Components, volume, velocity, variety, veracity, and value.

0:36

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

purpose extract valuable insights and information example social media data and sensor data importance drives decision making and innovation trend growing exponentially in various sectors characteristics of big data volume massive amounts of data generated every second velocity

1:04

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

Speed at which new data is generated and processed. Variety, different types of data, i.e. structured, unstructured, and semi-structured. Veracity, quality and accuracy of data. Value, extracting meaningful insights. Example, petabytes of data generated by social media platforms. Sources of big data.

1:36

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

social media, posts, tweets, likes and comments, IoT devices, sensor data from connected devices, transactional data, online purchases and financial transactions, web blogs, data from website visits and interactions, multimedia, images, video and audio files. Example, data from e-commerce websites like Amazon.

2:07

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

Technologies for Big Data Processing. Hadoo, Distributed Storage and Processing Framework. Spark, Fast Data Processing Engine. NoSQL Databases. MongoDB, Cassandra for Unstructured Data. Data Lakes, Centralized Repository for Raw Data. Cloud Services. AWS, Google Cloud, Azure for Scalable Storage. Example.

2:38

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

using Hadoop for distributed data processing. Big data analytics. Descriptive analytics. Summarizes past data. Predictive analytics. Forecast future trends. Perspective analytics. Suggest action based on predictions. Real-time analytics. Analysis data as it generated. Visualization, graphs, charts for data interpretation.

3:08

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

Example, predictive maintenance in manufacturing using big data, applications of big data, healthcare, predictive analytics for patient care, finance, fraud detection and risk management, retail, personalized marketing and inventory management, transportation.

3:30

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

Route optimization and traffic management, government, public safety, smart city initiatives. Example, targeted advertising based on consumer behavior. Benefits of big data. Improved decision making. Data-driven insights for better decisions. Operational efficiency. Streamlined processes and reduced costs. Customer insights. Better understanding of customer preferences.

4:00

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

Benefits of big data. Innovation identifies new opportunities and trends. Competitive advantage. Leverages data to outperform the competitors. Example, Netflix using data to recommend shows to users. Challenges of big data. Data quality, ensuring accuracy and reliability. Storage, managing large volumes of data. Security.

4:31

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

protecting sensitive information integration combining data from different sources skills gap need for expertise in data analytics example implementing robust security measures for data protection conclusion definition big data involves large complex data sets

4:56

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

characteristics, volume, velocity, variety, veracity and value, sources, social media, IoT, transaction, web blocks and multimedia, technologies, Hadoop, Spark, NoSQL, data lakes and cloud services, analytics, descriptive, predictive.

5:19

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

prospective, and real-time applications, healthcare, finance, retail, transportation, and government. Benefits, improved decisions, efficiency, customer insights, and innovation. Challenges, data quality, storage, security, integration, and skills gap. Now, let us break for questions. Verify your learnings.

5:50

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

Which characteristics of big data refers to the speed at which new data is generated? Option A, Volume. Option B, Velocity. Option C, Velocity. And Option D, Veracity. The correct answer is Option C, Velocity. Verify your learnings. Which technology is commonly used for distributed data processing in big data? Option A, SQL. Option B, Hadoop.

6:21

S… Speaker 1 (MBA_IM_unit 3_week 8_seq 4_Big data_magesh)

option C, Excel, and option D, Access. The correct answer is option B, Hadoo. Summary. In this session, we have understood about big data in information systems. Happy learning. Thank you.

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