Big Data Professional Program

Build a foundational understanding of Big Data – its core concepts, technologies, processing frameworks, storage models, and real-world applications across industries.

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Payment Schedule of Big Data Course

50% of the course fee is due at the time of registration.
25% is payable after 60 days from the start of your classes.
The remaining 25% is due after 120 days from the start of your classes.
This allows you to split your payments while continuing your course without interruption.

Big Data Course Highlights

Makes Big Data easy to understand for non-technical learners.
Helps you explore career paths in data engineering, data analytics, and data science.
Improves your analytical skills and job readiness for IT and business roles alike.

About The Big Data Online Course

Entry-level program designed for beginners with no prior data experience.
Core coverage: Big Data fundamentals, data processing frameworks (Hadoop, Spark), storage systems (HDFS, NoSQL, Data Lakes).
Tools overview: Introduction to Hadoop ecosystem, Apache Spark, and modern data platforms.

Starting date - Saturday, September 13, 2025
Training Duration : 6 months (144 hrs).

Duration : 3 hours.
Class Mode : Online.

Schedule : Weekend.
Saturday & Sunday : 10 AM to 1 PM.

Course Overview and Curriculum Outline

Month 1: Foundations & Architecture (Weeks 1–4)

Week 1 : Introduction to Big Data Concepts, Industry Case Studies & Applications

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Saturday: Introduction to Big Data Concepts
What is Big Data?	0–30 min
The 5 V’s – Volume, Velocity, Variety, Veracity, Value	30–60 min
Importance of Big Data in Modern Enterprises	60–90 min
Evolution from Traditional Databases to Big Data	90–120 min
Use Cases in Finance, Retail, and Healthcare	120–150 min
Recap + Q&A	150–180 min

Sunday: Industry Case Studies & Applications
Case Study – Big Data in Banking	0–30 min
Case Study – Retail and Customer Analytics	30–60 min
Case Study – Healthcare Data Insights	60–90 min
Role of Big Data in Decision Making	90–120 min
Assignment Discussion – Industry Analysis	120–150 min
Recap + Q&A	150–180 min

Week 2 : Big Data Ecosystem & Frameworks, Big Data Architecture Overview

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Saturday: Big Data Ecosystem & Frameworks
Components of Big Data Ecosystem	0–30 min
Hadoop Framework Overview	30–60 min
MapReduce Concepts	60–90 min
Big Data Analytics Lifecycle	90–120 min
Tools Overview – Spark, Hive, HBase	120–150 min
Recap + Q&A	150–180 min

Sunday: Big Data Architecture Overview
Layers of Big Data Architecture	0–30 min
Data Ingestion and ETL Process	30–60 min
Real-time vs Batch Processing	60–90 min
Architecture Components – Storage, Processing, Access	90–120 min
Hands-on: Simple Data Flow Design	120–150 min
Recap + Q&A	150–180 min

Week 3 : Data Types & Storage Systems, NoSQL Databases & Hive Overview

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Saturday: Data Types & Storage Systems
Structured, Semi-Structured, and Unstructured Data	0–30 min
HDFS Architecture and Components	30–60 min
Blocks, Namenode, Datanode Concept	60–90 min
Data Replication and Fault Tolerance	90–120 min
Hands-on: Understanding HDFS Commands	120–150 min
Recap + Q&A	150–180 min

Sunday: NoSQL Databases & Hive Overview
What is NoSQL?	0–30 min
Types of NoSQL – Key-Value, Document, Column	30–60 min
Overview of Hive and HBase	60–90 min
Querying Data with HiveQL	90–120 min:
Hands-on: Hive Table Creation and Queries	120–150 min
Recap + Q&A	150–180 min

Week 4 : Distributed Systems & Cloud Storage, Review, Hands-on, Mock Test & Interview Prep

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Saturday: Distributed Systems & Cloud Storage
Introduction to Distributed File Systems	0–30 min
How Data is Distributed Across Nodes	30–60 min
Cloud-based Storage – AWS S3, Azure Blob	60–90 min
Integrating Cloud with Hadoop	90–120 min
Hands-on: Store and Retrieve Data from Cloud	120–150 min
Recap + Q&A	150–180 min

Sunday: Review, Hands-on, Mock Test & Interview Prep
Recap of Big Data Foundations & Architecture	0–60 min
Hands-on: Set up Hadoop HDFS Cluster and Query in Hive/MongoDB	60–120 min
Mock Test + Interview Q&A: “Explain the Big Data Ecosystem”	120–180 min

Month 2: Big Data Processing & Analytics (Weeks 5–8)

Week 5 : Hadoop MapReduce Fundamentals, Advanced MapReduce Concepts

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Saturday: Hadoop MapReduce Fundamentals
Advanced MapReduce Concepts	0–30 min
Understanding Map and Reduce Functions	30–60 min
Job Execution Flow in Hadoop	60–90 min
WordCount Example Walkthrough	90–120 min
Hands-on: Create a Simple MapReduce Job	120–150 min
Recap + Q&A	150–180 min

Sunday: Advanced MapReduce Concepts
Combiner and Partitioner Functions	0–30 min
Custom Input and Output Formats	30–60 min
Job Configuration and Tuning	60–90 min
Handling Large Datasets with MapReduce	90–120 min
Hands-on: Analyze Large Log Files	120–150 min
Recap + Q&A	150–180 min

Week 6 : Apache Spark – Introduction, Spark SQL and DataFrames

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Saturday: Apache Spark – Introduction
What is Apache Spark and Why It’s Popular	0–30 min
Spark Architecture – Driver, Executors, Cluster Manager	30–60 min
Understanding RDD (Resilient Distributed Dataset)	60–90 min
Transformations and Actions	90–120 min
Hands-on: WordCount in Spark	120–150 min
Recap + Q&A	150–180 min

Sunday: Spark SQL and DataFrames
Introduction to Spark SQL	0–30 min
Creating DataFrames from CSV and JSON Files	30–60 min
DataFrame Operations and Filters	60–90 min
SQL Queries on Spark Data	90–120 min
Hands-on: Query Dataset using Spark SQL	120–150 min
Recap + Q&A	150–180 min

Week 7 : Data Processing Pipelines in Spark, Spark Streaming and Real-time Processing

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Saturday: Data Processing Pipelines in Spark
Understanding ETL Process in Big Data	0–30 min
Data Transformation using Spark	30–60 min
Joins, GroupBy, and Aggregations	60–90 min
Handling Missing and Skewed Data	90–120 min
Hands-on: Build Spark ETL Pipeline	120–150 min
Recap + Q&A	150–180 min

Sunday: Spark Streaming and Real-time Processing
Introduction to Spark Streaming	0–30 min
DStreams and Micro-batching	30–60 min
Integrating Kafka with Spark Streaming	60–90 min
Window Operations and Stateful Processing	90–120 min
Hands-on: Stream Processing Example	120–150 min
Recap + Q&A	150–180 min

Week 8 : Big Data Analytics & Visualization, Review, Hands-on, Mock Test & Interview Prep

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Saturday: Big Data Analytics & Visualization
Introduction to Data Analytics on Big Data	0–30 min
Connecting Spark with BI Tools	30–60 min
Using Tableau for Data Exploration	60–90 min
Interactive Dashboards and Visual Reports	90–120 min
Hands-on: Visualize Spark Results in Tableau	120–150 min
Recap + Q&A	150–180 min

Sunday: Review, Hands-on, Mock Test & Interview Prep
Recap of Spark, MapReduce, and Data Processing Concepts	0–60 min
Hands-on: Create End-to-End Big Data Pipeline	60–120 min
Mock Test + Interview Q&A: “Explain the Difference Between Hadoop and Spark”	120–180 min

Month 3: Processing Frameworks (Weeks 9–12)

Week 9 : Data Ingestion – ETL Concepts, ETL Tools and Workflow Management

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Saturday: Data Ingestion – ETL Concepts
Introduction to Data Ingestion and ETL	0–30 min
Types of ETL Processes – Batch vs Stream	30–60 min
Data Flow Design for Ingestion	60–90 min
Extract and Transform Techniques	90–120 min
Hands-on: Build Simple ETL Pipeline	120–150 min
Recap + Q&A	150–180 min

Sunday: ETL Tools and Workflow Management
ETL in the Big Data Ecosystem	0–30 min
Overview of Apache NiFi and Airflow	30–60 min
Scheduling and Automation of ETL Jobs	60–90 min
Hands-on: NiFi Flow for CSV Data	90–120 min
Integration of Data Sources	120–150 min
Recap + Q&A	150–180 min

Week 10 : Hadoop & MapReduce – Deep Dive, Hadoop Advanced Features

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Saturday: Hadoop & MapReduce – Deep Dive
Understanding Hadoop Architecture	0–30 min
MapReduce Workflow Review	30–60 min
InputSplit, Mapper, Reducer Explained	60–90 min
Data Flow Between Nodes	90–120 min
Hands-on: Build Custom MapReduce Job	120–150 min
Recap + Q&A	150–180 min

Sunday: Hadoop Advanced Features
Combiner and Partitioner Optimization	0–30 min
Distributed Caching and Counters	30–60 min
Job Configuration Tuning	60–90 min
Monitoring Hadoop Jobs with YARN	90–120 min
Hands-on: Analyze Log Data with MapReduce	120–150 min
Recap + Q&A	150–180 min

Week 11 : Apache Spark Fundamentals, Spark SQL and DataFrames

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Saturday: Apache Spark Fundamentals
Spark Ecosystem Overview	0–30 min
Spark Architecture – Driver and Executors	30–60 min
RDDs and Lazy Evaluation	60–90 min
Transformations and Actions	90–120 min
Hands-on: Spark RDD Operations	120–150 min
Recap + Q&A	150–180 min

Sunday: Spark SQL and DataFrames
Introduction to DataFrames and Datasets	0–30 min
Creating DataFrames from Multiple Sources	30–60 min
SQL Queries on Structured Data	60–90 min
Aggregations and Joins in Spark SQL	90–120 min
Hands-on: Query JSON Data with Spark	120–150 min
Recap + Q&A	150–180 min

Week 12 : Real-Time Processing – Concepts, Advanced Streaming Frameworks

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Saturday: Real-Time Processing – Concepts
Introduction to Streaming Systems	0–30 min
Kafka Overview and Architecture	30–60 min
Producers, Topics, and Consumers Explained	60–90 min
Integrating Kafka with Spark Streaming	90–120 min
Hands-on: Stream Processing Example	120–150 min
Recap + Q&A	150–180 min

Sunday: Advanced Streaming Frameworks
Introduction to Flink and Storm	0–30 min
Flink Architecture and Event Processing	30–60 min
Building Stateful Stream Applications	60–90 min
Case Study: Real-Time Log Analytics	90–120 min
Hands-on: Build Simple Flink Stream	120–150 min
Recap + Mock Test + Interview Prep	150–180 min

Month 4: Analytics & Applications (Weeks 13–16)

Week 13 : Introduction to Machine Learning on Big Data, Classification Techniques using Spark MLlib

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Saturday: Introduction to Machine Learning on Big Data
Overview of ML in Big Data Ecosystems	0–30 min
Spark MLlib Introduction	30–60 min
Understanding ML Pipelines in Spark	60–90 min
Feature Engineering for Large Datasets	90–120 min
Hands-on: Linear Regression in Spark MLlib	120–150 min
Recap + Q&A	150–180 min

Sunday: Classification Techniques using Spark MLlib
Supervised Learning Overview	0–30 min
Logistic Regression and Decision Trees	30–60 min
Random Forests and Gradient Boosting	60–90 min
Model Evaluation and Cross-Validation	90–120 min
Hands-on: Classification on a Big Data Set	120–150 min
Recap + Q&A	150–180 min

Week 14 : Clustering and Unsupervised Learning in Spark, Predictive Analytics on Large Datasets

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Saturday: Clustering and Unsupervised Learning in Spark
Unsupervised Learning Concepts	0–30 min
K-Means Clustering Algorithm	30–60 min
Hierarchical Clustering in Big Data	60–90 min
Dimensionality Reduction with PCA	90–120 min
Hands-on: Customer Segmentation using K-Means	120–150 min
Recap + Q&A	150–180 min

Sunday: Predictive Analytics on Large Datasets
What is Predictive Modeling?	0–30 min
Time Series Forecasting with Spark	30–60 min
Handling Model Scalability in Distributed Environments	60–90 min
Performance Optimization Techniques	90–120 min
Hands-on: Forecasting Use Case	120–150 min
Recap + Q&A	150–180 min

Week 15 : Industry Applications – Domain Use Cases, Hands-on Industry Project

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Saturday: Industry Applications – Domain Use Cases
Introduction to AI in Industry	0–30 min
Fraud Detection Models using Transaction Data	30–60 min
Predictive Maintenance in Manufacturing	60–90 min
Sentiment Analysis in Retail and Social Media	90–120 min
Healthcare Analytics with Big Data	120–150 min
Recap + Q&A	150–180 min

Sunday: Hands-on Industry Project
Define Project Problem Statement	0–30 min
Identify Data Sources and Preprocessing Steps	30–60 min
Implement MLlib Models	60–90 min
Visualize Results and Performance Metrics	90–120 min
Project Discussion and Peer Review	120–150 min
Recap + Q&A	150–180 min

Week 16 : Visualization & BI Tools – Tableau and Power BI, Review, Hands-on, Mock Test & Interview Prep

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Saturday: Visualization & BI Tools – Tableau and Power BI
Introduction to Data Visualization in Big Data	0–30 min
Tableau Interface and Workflow	30–60 min
Creating Dashboards from Spark Data	60–90 min
Connecting Power BI with Big Data Sources	90–120 min
Hands-on: Build Interactive Dashboard	120–150 min
Recap + Q&A	150–180 min

Sunday: Review, Hands-on, Mock Test & Interview Prep
Recap of Spark MLlib and BI Concepts	0–60 min
Hands-on: Create End-to-End Analytics Dashboard	60–120 min
Mock Test + Interview Q&A: “How does MLlib handle distributed ML?”	120–180 min

Month 5: Tools & Ecosystem (Weeks 17–20)

Week 17 : Hadoop Ecosystem Overview, Hive and Pig Hands-on

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Saturday: Hadoop Ecosystem Overview
Introduction to Hadoop Ecosystem and Its Components	0–30 min
Overview of Pig, Hive, and Oozie	30–60 min
Sqoop for Data Transfer Between RDBMS and Hadoop	60–90 min
Introduction to Zookeeper and Workflow Management	90–120 min
Hands-on: Data Load Using Sqoop	120–150 min
Recap + Q&A	150–180 min

Sunday: Hive and Pig Hands-on
Hive Architecture and Query Language (HiveQL)	0–30 min
Creating Databases and Tables in Hive	30–60 min
Query Optimization and Partitioning in Hive	60–90 min
Introduction to Pig Scripts for Data Transformation	90–120 min
Hands-on: ETL Workflow with Hive and Pig	120–150 min
Recap + Q&A	150–180 min

Week 18 : Workflow Orchestration with Oozie & Zookeeper, Hadoop Administration Essentials

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Saturday: Workflow Orchestration with Oozie & Zookeeper
What is Workflow Scheduling?	0–30 min
Setting Up Oozie Workflows	30–60 min
Managing Jobs and Dependencies	60–90 min
Zookeeper in Coordination Services	90–120 min
Hands-on: Create an End-to-End Oozie Job	120–150 min
Recap + Q&A	150–180 min

Sunday: Hadoop Administration Essentials
Cluster Management and Configuration Files	0–30 min
Monitoring with YARN and ResourceManager	30–60 min
Troubleshooting and Log Analysis	60–90 min
Security and Access Controls in Hadoop	90–120 min
Hands-on: Manage Hadoop Cluster Nodes	120–150 min
Recap + Q&A	150–180 min

Week 19 : Cloud-Native Services Overview, Cloud Data Engineering

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Saturday: Cloud-Native Services Overview
Introduction to Cloud-based Data Platforms	0–30 min
Overview of AWS EMR, Google BigQuery, and Azure Synapse	30–60 min
Cloud Data Warehousing Concepts	60–90 min
Integrating Cloud Storage with Hadoop	90–120 min
Hands-on: Create and Query Dataset in BigQuery	120–150 min
Recap + Q&A	150–180 min

Sunday: Cloud Data Engineering
Using AWS EMR for Distributed Processing	0–30 min
Data Ingestion to Cloud Using S3 Buckets	30–60 min
Running Spark Jobs on EMR	60–90 min
Querying and Managing Data in Azure Synapse	90–120 min
Hands-on: Big Data ETL on Cloud Platform	120–150 min
Recap + Q&A	150–180 min

Week 20 : Emerging Data Technologies, Review, Hands-on, Mock Test & Interview Prep

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Saturday: Emerging Data Technologies
Introduction to Databricks and Unified Analytics	0–30 min
Delta Lake Concepts and Architecture	30–60 min
Apache Iceberg for Table Format Management	60–90 min
Real-time Data Lakehouse Architecture	90–120 min
Hands-on: Implement Delta Lake Pipeline	120–150 min
Recap + Q&A	150–180 min

Sunday: Review, Hands-on, Mock Test & Interview Prep
Recap of Hadoop, Cloud Services, and Emerging Tools	0–60 min
Hands-on: End-to-End Data Workflow with Cloud + Delta Lake	60–120 min
Mock Test + Interview Q&A: “Compare Hadoop and Cloud-Native Data Solutions”	120–180 min

Month 6: Security & Governance (Weeks 21–24)

Week 21 : Introduction to Big Data Security Frameworks, Authentication & Authorization in Big Data

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Saturday: Introduction to Big Data Security Frameworks
Why Big Data Security Matters	0–30 min
Common Threats in Big Data Environments	30–60 min
Overview of Security Layers – Data, Access, Network	60–90 min
Compliance Requirements – GDPR, HIPAA, DPDP	90–120 min
Security Policy Design in Big Data Architecture	120–150 min
Recap + Q&A	150–180 min

Sunday: Authentication & Authorization in Big Data
Identity and Access Control Models	0–30 min
Understanding Role-Based Access Control (RBAC)	30–60 min
Integrating Cloud IAM (AWS & Azure)	60–90 min
Multi-Factor Authentication and Token-based Access	90–120 min
Hands-on: Configure IAM Roles for Data Access	120–150 min
Recap + Q&A	150–180 min

Week 22 : Apache Ranger and Knox Implementation, Secure Gateway with Apache Knox

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Saturday: Apache Ranger and Knox Implementation
Introduction to Apache Ranger	0–30 min
Policy-based Access Control	30–60 min
Ranger Plugins and Auditing Features	60–90 min
Hands-on: Configure Ranger for HDFS and Hive	90–120 min
Integration of Ranger with Kerberos	120–150 min
Recap + Q&A	150–180 min

Sunday: Secure Gateway with Apache Knox
Introduction to Knox Gateway	0–30 min
Configuring REST APIs through Knox	30–60 min
Integrating Knox with Hadoop Cluster	60–90 min
SSL/TLS Configuration for Secure Communication	90–120 min
Hands-on: Enable Knox Authentication Layer	120–150 min
Recap + Q&A	150–180 min

Week 23 : Kerberos Authentication Systems, Metadata Management & Data Catalogs

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Saturday: Kerberos Authentication Systems
Overview of Kerberos Protocol	0–30 min
Key Distribution Center (KDC) Explained	30–60 min
Integrating Kerberos with Hadoop Cluster	60–90 min
Hands-on: Configure Kerberos Authentication	90–120 min
Troubleshooting Common Kerberos Issues	120–150 min
Recap + Q&A	150–180 min

Sunday: Metadata Management & Data Catalogs
Importance of Metadata in Big Data	0–30 min
Apache Atlas Overview	30–60 min
Metadata Lineage Tracking	60–90 min
Data Cataloging and Discovery	90–120 min
Hands-on: Create and Query Metadata in Atlas	120–150 min
Recap + Q&A	150–180 min

Week 24 : Cloud IAM Integration & Data Governance, Review, Hands-on, Mock Test & Interview Prep

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Saturday: Cloud IAM Integration & Data Governance
Introduction to Cloud IAM (AWS, Azure)	0–30 min
IAM Policies, Permissions, and Role Hierarchies	30–60 min
Data Governance Models for Enterprises	60–90 min
Aligning IAM with Compliance Requirements	90–120 min
Hands-on: Configure IAM Roles in AWS/Azure	120–150 min
Recap + Q&A	150–180 min

Sunday: Review, Hands-on, Mock Test & Interview Prep
Recap of Ranger, Knox, and Kerberos	0–60 min
Hands-on: End-to-End Secure Big Data Architecture	60–120 min
Mock Test + Interview Q&A: “How is Big Data Security Managed in Enterprises?”	120–180 min

The world is driven by data. From social media interactions to enterprise operations, vast amounts of information are being generated every second. This explosion of data has transformed how organizations make decisions, innovate, and deliver value. For aspiring IT professionals, analysts, and graduates, understanding Big Data is no longer optional—it’s essential. At Viewsoft Academy, we’ve designed a comprehensive Fundamentals of Big Data program to equip you with the skills and knowledge needed to thrive in this data-driven world.

It’s more than just another course-it’s your gateway to a high-impact career in data. We’ve built a clear, practical curriculum that simplifies complex Big Data concepts, technologies, and real-world applications. Whether you’re a recent graduate aiming to stand out or a working professional looking to upskill or reskill, this program offers the perfect launchpad into the world of Big Data and analytics.

Why Big Data is the Future?

The words Big Data are no longer just a buzzword—they represent the foundation of modern business intelligence and decision-making. Organizations of all sizes now rely on data-driven insights to enhance efficiency, predict trends, and gain a competitive edge. This growing dependence on data has created a massive demand for professionals who can collect, process, and analyze large-scale data effectively.

Earning a Big Data certification is one of the most powerful ways to demonstrate your expertise and stand out in the job market. It validates your ability to handle real-world data challenges and leverage advanced tools to uncover insights. Our program prepares you for industry-recognized certifications, such as Cloudera Certified Associate (CCA) and Databricks Data Engineer, while giving you the strong foundational knowledge needed to pursue specialized Big Data and analytics credentials with confidence.

Why is the Viewsoft Academy Program the Right One?

At Viewsoft Academy, we believe in practical, hands-on learning. Our Big Data curriculum is designed and delivered by industry professionals who have led large-scale data projects and implemented enterprise analytics solutions. We don’t just teach theory—we demonstrate real-world applications and help you build the skills to practice them confidently.

Multifaceted Curriculum: Our Big Data Fundamentals course covers everything from data collection and storage to processing and analytics. You’ll explore distributed computing frameworks like Hadoop and Spark, data storage systems such as HDFS, NoSQL, and Data Lakes, along with essentials of data pipelines, visualization, and governance.

Relevant Industry Content: We continually update our course content to reflect the latest industry trends and technologies, ensuring that what you learn is immediately applicable in real-world data environments.

Skilled Instructors: Learn from experienced data professionals who bring practical insights and case studies from domains like finance, healthcare, and e-commerce—making your learning journey engaging and industry-relevant.

Flexible Learning: Designed to fit your schedule, our program offers online access to lectures, labs, and assignments, allowing you to learn anytime, anywhere, and at your own pace.

Who is to take part in this Program?

This program is perfect for:

IT Professionals who want to transition into data-driven roles or manage large-scale data systems. The Viewsoft Academy Certificate in Big Data validates your competence and opens doors to advanced career opportunities in analytics and data engineering.

Computer Science and Information Technology Graduates, as well as those from related fields, who wish to strengthen their technical resumes with a recognized Big Data certification, making them more attractive to top technology employers.

Beginners and career changers looking to build a strong foundation in data technologies and launch a successful career in one of today’s fastest-growing and most impactful fields.

The Ultimate Guide to Highest Certifications and your future.

Although this course focuses on the fundamentals of Big Data, it also serves as a powerful stepping stone toward more advanced and specialized areas in data engineering and analytics. The concepts and tools covered here directly align with major industry-recognized Big Data certifications. For instance, our program acts as a strong foundation for credentials such as the Cloudera Certified Associate (CCA), Databricks Data Engineer, and Google Cloud Data Engineer certifications.

As the Big Data landscape continues to evolve, certifications in technologies like Apache Spark, Hadoop, and AWS Big Data are gaining increasing recognition. Our curriculum is carefully designed to remain vendor-neutral, giving you a comprehensive understanding of Big Data principles and systems that can be applied across platforms. By the end of this course, you’ll have the clarity, competence, and confidence to pursue the most relevant Big Data certifications aligned with your career goals.

Why This is the Opportunity You can not Afford to Miss.

Big Data professionals are in exceptionally high demand—and the opportunities are growing rapidly. Waiting too long to enter this field means missing out on high-paying roles and remarkable career growth. Our Big Data program is designed to make you market-ready quickly and effectively, equipping you with the practical skills and technical expertise needed to handle real-world data challenges and deliver measurable value to any organization.

Join the thousands of professionals who have trusted Viewsoft Academy to advance their careers. We remain committed to delivering high-quality, industry-relevant education and supporting the academic and professional success of every learner who embarks on this data-driven journey with us.

Frequently Asked Questions on The Fundamentals of Big Data By Viewsoft Academy

Question 1. Is there a prerequisite to taking the Fundamentals of Big Data?

Answer: The course is beginner-friendly and does not require any prior Big Data experience. A basic understanding of IT concepts is helpful, but the curriculum starts from the fundamentals. It is best suited for graduate students, recent graduates, or IT professionals who want to build a strong foundation in Big Data and develop valuable, industry-relevant skills.

Question 2. How much time does it take to go through the program?

Answer: The program can be self-paced, and thus, you can learn at your own pace. Students, on average, finish the course in 8-12 weeks, spending between 5-7 hours per week on video lectures and practical work in the labs. The course material is accessible to you throughout life.

Question 3. What type of certificate will I get at the end?

Answer: After successfully completing all modules and assessments, you will be eligible to receive an official Big Data certificate from Viewsoft Academy. This professional certificate validates your fundamental understanding of Big Data concepts and serves as a valuable credential to enhance your resume and professional profiles.

Question 4. Does the course assure employment or certification?

Answer: Our program does not guarantee employment, but it equips you with the essential skills and foundational knowledge required for entry-level roles in Big Data and analytics. It also serves as a stepping stone toward formal industry certifications, such as Cloudera Certified Associate (CCA) and Google Cloud Data Engineer, which are highly valued in today’s job market.

Question 5. What is the format of the practical learning?

Answer: The course includes numerous practical exercises and hands-on labs that allow you to work directly with Big Data technologies. You will apply theory to practice, developing skills in data processing, storage, analytics, and pipeline management, ensuring you are prepared to handle real-world projects and confidently tackle interview questions.

Question 6. Who are the instructors? What are their qualifications?

Answer: Our trainers are seasoned data professionals with extensive experience in designing, managing, and implementing Big Data solutions in large organizations. They bring real-world insights into the curriculum, providing practical perspectives that go beyond theory and prepare you to tackle challenges in today’s data-driven industry.

Big Data Professional Program

Payment Schedule of Big Data Course

Big Data Course Highlights

About The Big Data Online Course

Course Overview and Curriculum Outline

Month 1: Foundations & Architecture (Weeks 1–4)

Month 2: Big Data Processing & Analytics (Weeks 5–8)

Month 3: Processing Frameworks (Weeks 9–12)

Month 4: Analytics & Applications (Weeks 13–16)

Month 5: Tools & Ecosystem (Weeks 17–20)

Month 6: Security & Governance (Weeks 21–24)

Why Big Data is the Future?

Why is the Viewsoft Academy Program the Right One?

Who is to take part in this Program?

The Ultimate Guide to Highest Certifications and your future.

Why This is the Opportunity You can not Afford to Miss.

Frequently Asked Questions on The Fundamentals of Big Data By Viewsoft Academy

We don’t send spam so don’t worry.

Capability Statement

Get In Touch

Big Data Professional Program

Fill Out the Form Below to Get All the Details!

Payment Schedule of Big Data Course

Big Data Course Highlights

About The Big Data Online Course

Course Overview and Curriculum Outline

Month 1: Foundations & Architecture (Weeks 1–4)

Month 2: Big Data Processing & Analytics (Weeks 5–8)

Month 3: Processing Frameworks (Weeks 9–12)

Month 4: Analytics & Applications (Weeks 13–16)

Month 5: Tools & Ecosystem (Weeks 17–20)

Month 6: Security & Governance (Weeks 21–24)

Why Big Data is the Future?

Why is the Viewsoft Academy Program the Right One?

Who is to take part in this Program?

The Ultimate Guide to Highest Certifications and your future.

Why This is the Opportunity You can not Afford to Miss.

Frequently Asked Questions on The Fundamentals of Big Data By Viewsoft Academy

Fill Out the Form Below to Get All the Details!

We don’t send spam so don’t worry.

Capability Statement