Big Data, Python & R
Big Data, Python, and R are closely associated with the field of data science and analytics.
Advantage @DGU
Level & Duration
Level
Certificate
Duration
1 Year
Big Data
Definition
Big Data refers to extremely large and complex datasets that traditional data processing tools and methods may struggle to handle. It involves managing, processing, and extracting valuable insights from massive volumes of structured and unstructured data.
Characteristics
Volume - Big Data involves vast amounts of data, often ranging from terabytes to petabytes or more.
Velocity - Data is generated at high speed, often in real-time or near real-time.
Variety - Data comes in various formats, including text, images, videos, and more.
Veracity - The reliability and quality of the data can vary.
Value - Extracting meaningful insights from Big Data can provide significant value for businesses and decision-making.
Technologies and Tools
Hadoop - An open-source framework for distributed storage and processing of large datasets.
Spark - A fast and general-purpose cluster-computing system for Big Data processing.
NoSQL Databases - Database systems like MongoDB, Cassandra, and HBase designed to handle large volumes of unstructured data.
Data Lakes - Repositories that store vast amounts of raw data in its native format until needed.
Applications
Big Data is used in various industries, including finance, healthcare, e-commerce, and more, for purposes such as predictive analytics, fraud detection, and personalized recommendations.
Python
Programming Language
Python is a versatile, high-level programming language known for its readability and ease of use.
Data Science and Analytics
Python has become one of the most popular programming languages in the field of data science and analytics.
Libraries for Data Science
NumPy and Pandas - For numerical computing and data manipulation.
Matplotlib and Seaborn - For data visualization.
Scikit-learn - For machine learning algorithms and modeling.
TensorFlow and PyTorch - For deep learning.
Integration with Big Data Tools
Python is widely used in Big Data processing with tools like PySpark (Python API for Apache Spark) and integration with Hadoop.
Web Development and Automation
Python is extensively used in web development frameworks (Django, Flask) and for automation tasks.
Community and Ecosystem
Python has a large and active community, contributing to a rich ecosystem of libraries and frameworks.
R
Statistical Programming Language
R is a programming language and environment designed for statistical computing and graphics.
Data Analysis and Visualization
R is widely used for statistical analysis, data visualization, and exploratory data analysis.
Libraries for Statistics
dplyr and tidyr - For data manipulation and cleaning.
ggplot2 - For creating sophisticated data visualizations.
lm() and glm() - For linear and generalized linear modeling.
Integration with Big Data Tools
R has connectors and packages that enable integration with Big Data platforms, such as Rhipe for Hadoop.
Bioinformatics and Research
R is commonly used in fields like bioinformatics and academic research for statistical analysis.
Shiny
Shiny is an R package that allows interactive web applications to be created directly from R scripts.
Community and Packages
R has a strong community of statisticians and data scientists, and it offers a vast collection of packages for various statistical analyses.
Python vs R
Flexibility
Python is a general-purpose language used in various domains, while R is specialized for statistical computing.
Syntax
Python has a straightforward and readable syntax, making it easy for beginners. R is focused on statistical analysis, and its syntax reflects this specialization.
Ecosystem
Python has a broader ecosystem, including extensive libraries for web development, automation, and machine learning. R excels in statistics and data visualization.
Community
Both Python and R have active communities, and the choice between them often depends on specific project requirements and personal preferences.
In the field of data science, both Python and R are widely used, and the choice between them depends on factors such as the nature of the analysis, the available libraries, and the preferences of the data scientists and analysts involved. Many professionals in the field use a combination of both languages based on the task at hand.
Placements
Enjoy Everyday while Ensuring Great Career
Thanks to DGU’s mock interviews, value‑added courses, and hands‑on projects I developed confidence, communication skills and real-world business sense. The practical exposure and industry-aligned learning helped me step into Indigo Paints Limited ready to perform and grow.
From engaging campus activities to hands-on projects, DGU made learning practical and exciting. This experience helped me step into Reliance Retail ready to make an impact.
One thing that really helped me during the placement season was the confidence I gained from the mock sessions. My professors pointed out mistakes I hadn’t even realized I was making and gave me valuable tips that made the process smoother. This foundation prepared me well for my role at Asian Paints Ltd.
The mix of interactive learning, practical projects, and expert guidance shaped my skills effectively. It gave me the confidence to start my professional journey with Tech Mahindra.
Hands-on learning, value-added courses, and supportive faculty prepared me for real-world challenges. These experiences helped me confidently join Hafele India Pvt Ltd and contribute from day one.
DBS Global University’s rigorous learning environment and hands-on experiences challenged me to grow constantly. This preparation gave me the confidence and skills to step into Grant Thornton Bharat LLP with readiness.
DBS Global University’s competitive and dynamic environment pushed me to perform at my best every day. This energy, combined with practical learning and guidance from faculty, helped me secure my role at MyGetWellStore.
DBS Global University’s practical projects and faculty guidance helped me build real-world skills and confidence. This preparation enabled me to step into Prism Johnson ready to contribute effectively.
At DBS Global University, engaging in practical projects and hands-on learning enhanced my skills and confidence, equipping me to step into my role at Phronesis Partners with clear direction and focus.
Through DBS Global University’s hands-on projects and skill-focused sessions, I gained practical experience and strengthened my confidence. These opportunities equipped me to make meaningful contributions at Digital Marveled Private Limited.
DGU helped me grow into someone who can take on challenges with confidence and clarity. My placement at Extramarks Education feels like the right step toward building a meaningful career.
DGU shaped my skills through constant guidance, practical exposure, and a supportive environment. Getting placed at High Beam Global feels like a strong beginning to my professional journey.
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Study Abroad Opportunities for Global Careers
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Through strategic partnerships with institutions across Australia, USA, Europe, Malaysia, Singapore, Dubai, Thailand, Indonesia, Turkey, Hong Kong and Russia, students benefit from internationally benchmarked curricula, industry exposure, multicultural classrooms, and cross-cultural learning. These experiences integrate academics with experiential learning, global networking, and real-world insights—empowering students with a global mindset, enhanced employability, and the skills required for successful international careers.
