4.9Course Overview
The BigData Foundation certification is a professional credential that recognizes individuals’ fundamental knowledge in big data concepts and technologies. It covers the principles of data mining, analysis, capture, management, and governance. Industries use this certification to validate the expertise of professionals who handle large volumes of complex data, ensuring that they possess a foundational understanding of how to effectively work with big data environments. This certification is crucial for companies seeking to harness the insights big data can provide, aiming to improve decision-making, predictive analysis, and business intelligence. It lays the groundwork for more advanced expertise in data science and analytics roles.
This is a Rare Course and it can take up to 3 weeks to arrange the training.
Learning and Objectives:
– Certified Instructor-led education
– Career enhancement with Big Data proficiency
– Tailored training programs to suit individual needs
– Unique destination training experiences
– Cost-effective learning solutions
– Recognized as a leading training institute
– Adjustable scheduling for convenience
– Online training with real-time instructor interaction
– Extensive selection of courses across technologies
– Officially accredited and approved training partner
Course Prerequisites
– Basic knowledge of computing- Understanding of core data concepts
– Familiarity with database principles
– Elementary programming skills
– Awareness of data analytics importance
– High school mathematics proficiency
Learning Options
Target Audiance
- - IT professionals seeking to understand big data concepts
- - Business analysts aiming to leverage big data insights
- - Data enthusiasts wanting a foundational knowledge of big data technologies
- - Managers overseeing data-driven projects
- - Professionals looking to transition into big data roles
Schedule Dates
Introduction and Foundations of Big Data
Introduction and Foundations of Big Data
Introduction and Foundations of Big Data
Introduction and Foundations of Big Data
Course Content
- What launched the Big Data era?
- Applications: What makes big data valuable
- Example: Saving lives with Big Data
- Example: Using Big Data to Help Patients
- Getting Started: Where Does Big Data Come From?
- Machine-Generated Data: It's Everywhere and There's a Lot!
- Machine-Generated Data: Advantages
- Big Data Generated By People: The Unstructured Challenge
- Big Data Generated By People: How Is It Being Used?
- Organization-Generated Data: Structured but often siloed
- Organization-Generated Data: Benefits Come From Combining With Other Data Types
- The Key: Integrating Diverse Data
- Exercises
- Getting Started: Characteristics Of Big Data
- Characteristics of Big Data - Volume
- Characteristics of Big Data - Variety
- Characteristics of Big Data - Velocity
- Characteristics of Big Data - Veracity
- Characteristics of Big Data - Valence
- The Sixth V: Value
- Exercises
- Data Science: Getting Value out of Big Data
- Building a Big Data Strategy
- How does big data science happen?: Five Components of Data Science
- Asking the Right Questions
- Steps in the Data Science Process
- Step 1: Acquiring Data
- Step 2-A: Exploring Data
- Step 2-B: Pre-Processing Data
- Step 3: Analyzing Data
- Step 4: Communicating Results
- Step 5: Turning Insights into Action
- Exercises
- Getting Started: Why worry about foundations?
- What is a Distributed File System?
- Scalable Computing over the Internet
- Programming Models for Big Data
- Exercises
- Hadoop: Why, Where and Who?
- The Hadoop Ecosystem: Welcome to the zoo!
- The Hadoop Distributed File System: A Storage System for Big
- YARN: A Resource Manager for Hadoop
- MapReduce: Simple Programming for Big Results
- When to Reconsider Hadoop?
- Cloud Computing: An Important Big Data Enabler
- Cloud Service Models: An Exploration of Choices
- Value From Hadoop and Pre-built Hadoop Images
- Copy your data into the Hadoop Distributed File System (HDFS
- Run the WordCount program
- Exercises
- Wrap the course up
FAQs
The “Introduction and Foundations of Big Data” course provides a comprehensive overview of Big Data concepts, technologies, and methodologies. It covers the fundamental principles of Big Data, including data generation, storage, processing, and analysis.
Participants receive access to course lectures, reading materials, case studies, and hands-on lab exercises. Additional resources such as recommended readings and online tools may also be provided.
This course provides foundational knowledge of Big Data, which is increasingly important in today’s data-driven world. Understanding Big Data can open up career opportunities in data analysis, IT, business intelligence, and more.
Yes, this course provides a strong foundation in Big Data concepts, which is beneficial for those planning to pursue advanced Big Data certifications. It serves as a stepping stone to more specialized and advanced training.
The course includes case studies and real-world examples to illustrate how Big Data is applied in various industries. These examples help participants understand the practical applications and benefits of Big Data technologies.
Yes, the course may recommend additional readings and resources, such as books, research papers, and online articles, to supplement the learning material and provide a deeper understanding of Big Data concepts.
Duration
Language
Batch Options
Upcoming Batch
Soft copy of Courseware
Certificate of Course Complition
Experienced and Professional Trainer
Lab and Exercises During Training 
Sample Questions for Exam Prepration
Mock Test on the Last Day of Training 
Exam Registration Guidance 
5-Star Training Environmment 