Description
Course Name: Certificate in Big Data Analytics (Hadoop)
Course Id: CBDA/Q0001.
Eligibility: 10th Grade (high school) or Equivalent.
Objective: A Certificate in Big Data Analytics (Hadoop) course provides individuals with the skills and knowledge to analyze and manage large datasets using the Hadoop framework. The course covers data processing, distributed storage, and tools within the Hadoop ecosystem to extract insights from big data. It is ideal for aspiring data analysts, data scientists, and IT professionals who want to specialize in big data technologies.
Duration: One Month.
How You will Get Diploma Certificate:
Step 1- Select your Course for Certification.
Step 2- Click on Enroll Now.
Step 3- Proceed to Enroll Now.
Step 4- Fill Your Billing Details and Proceed to Pay.
Step 5- You Will be Redirected to Payment Gateway, Pay Course and Exam Fee by Following Options.
Card(Debit/Credit), Wallet, Paytm, Net banking, UPI and Google pay.
Step 6-After Payment You will get Study Material Login id and Password on your email id.
Step 7- After Completion of Course Study give Online Examination.
Step 8- After Online Examination you will get Diploma Certificate soft copy(Scan Copy) and Hard Copy(Original With Seal and Sign).
Step 9- After Certification you will receive Prospect Job Opportunities as per your Interest Area.
Online Examination Detail:
Duration- 60 minutes.
No. of Questions- 30. (Multiple Choice Questions).
Maximum Marks- 100, Passing Marks- 40%.
There is no negative marking in this module.
| Marking System: | ||||||
| S.No. | No. of Questions | Marks Each Question | Total Marks | |||
| 1 | 10 | 5 | 50 | |||
| 2 | 5 | 4 | 20 | |||
| 3 | 5 | 3 | 15 | |||
| 4 | 5 | 2 | 10 | |||
| 5 | 5 | 1 | 5 | |||
| 30 | 100 | |||||
| How Students will be Graded: | ||||||
| S.No. | Marks | Grade | ||||
| 1 | 91-100 | O (Outstanding) | ||||
| 2 | 81-90 | A+ (Excellent) | ||||
| 3 | 71-80 | A (Very Good) | ||||
| 4 | 61-70 | B (Good) | ||||
| 5 | 51-60 | C (Average) | ||||
| 6 | 40-50 | P (Pass) | ||||
| 7 | 0-40 | F (Fail) | ||||
Benefits of Certification:
- Government Authorized Assessment Agency Certification.
- Certificate Valid for Lifetime.
- Lifetime Verification of Certificate.
- Free Job Assistance as per your Interest Area.
Syllabus
Introduction to Big Data and Hadoop: Definition and Characteristics of Big Data, Importance and Challenges of Big Data, Evolution of Big Data Technologies, Hadoop Ecosystem Overview, Key Components of Hadoop, Hadoop vs. Traditional Databases, Applications of Big Data Analytics, Real-World Use Cases of Hadoop, Big Data Storage and Processing, Introduction to Distributed Computing.
Hadoop Architecture and HDFS: Hadoop Core Components Overview, Hadoop Distributed File System (HDFS), NameNode and DataNode Functionality, HDFS Read and Write Operations, Replication and Fault Tolerance in HDFS, Hadoop Cluster Setup and Configuration, HDFS Commands and File Operations, Data Storage Formats in Hadoop, Data Compression in HDFS, HDFS Performance Optimization.
Hadoop MapReduce Framework: Introduction to MapReduce Programming Model, Key-Value Pair Processing in MapReduce, Map and Reduce Function Execution, Input and Output Formats in MapReduce, Writing and Running MapReduce Jobs, Combiner and Partitioner in MapReduce, Advanced MapReduce Programming Concepts, Performance Tuning in MapReduce, Hands-on MapReduce Programming, Limitations of MapReduce and Alternatives.
Apache Hive and Data Warehousing in Hadoop: Introduction to Apache Hive, Hive Architecture and Components, Hive Query Language (HQL), Hive Tables and Partitioning, Hive Data Types and File Formats, Hive Optimization Techniques, Integrating Hive with HDFS, Managing Data in Hive, Hive vs. Traditional RDBMS, Hands-on Exercises with Hive.
Apache Pig and Data Processing: Overview of Apache Pig, Pig Latin Scripting Language, Pig Execution Modes and Components, Pig vs. MapReduce, Writing Pig Scripts for Data Processing, Pig UDFs (User-Defined Functions), Pig Joins, Filters, and Grouping, Debugging and Optimizing Pig Scripts, Real-World Use Cases of Pig, Hands-on Pig Script Execution.
Apache HBase and NoSQL Databases: Introduction to NoSQL Databases, Apache HBase Overview and Architecture, HBase Data Model and Schema Design, CRUD Operations in HBase, HBase vs. RDBMS, Integrating HBase with Hadoop, HBase Performance Tuning, HBase Use Cases in Big Data, Working with HBase Shell and API, Hands-on HBase Operations.
Job Opportunities after completion of Certificate in Big Data Analytics (Hadoop) course:
The Certificate in Big Data Analytics (Hadoop) program equips graduates with the essential skills to work with large datasets using Hadoop and related technologies. Big Data Analytics is a crucial aspect of modern data-driven businesses, and expertise in Hadoop—a widely used open-source framework for handling big data—can open various career opportunities. Graduates of this program are well-prepared to analyze complex data, derive insights, and work with big data platforms to support business decision-making.
Career Options for Graduates in Big Data Analytics (Hadoop):
1. Big Data Analyst
- Role: Big Data Analysts are responsible for collecting, processing, and analyzing large datasets to uncover patterns, trends, and insights that drive business decisions. They often work with Hadoop ecosystems and tools like Hive, Pig, and MapReduce.
- Industries: E-commerce, finance, healthcare, retail, telecommunications, IT companies, and research organizations.
- Salary Range: ₹4,00,000 to ₹8,00,000 per year (entry-level); ₹8,00,000 to ₹15,00,000 per year (experienced).
2. Hadoop Developer
- Role: Hadoop Developers design and implement solutions using Hadoop framework. They write code and build applications to store, process, and analyze large data sets in Hadoop clusters. They work with tools like Hive, HBase, and Spark.
- Industries: IT services, e-commerce, tech companies, banking, and finance.
- Salary Range: ₹5,00,000 to ₹9,00,000 per year (entry-level); ₹9,00,000 to ₹18,00,000 per year (experienced).
3. Data Engineer
- Role: Data Engineers design, build, and maintain data pipelines that collect and process large amounts of data. They integrate big data technologies like Hadoop with other systems and optimize the flow of data for analysis.
- Industries: IT, e-commerce, finance, media, tech startups.
- Salary Range: ₹5,50,000 to ₹10,00,000 per year (entry-level); ₹10,00,000 to ₹18,00,000 per year (experienced).
4. Big Data Architect
- Role: Big Data Architects design the architecture of big data systems and ensure they are scalable, efficient, and secure. They are responsible for setting up Hadoop clusters and managing the overall infrastructure of data storage and processing.
- Industries: IT, financial services, telecommunications, e-commerce, healthcare.
- Salary Range: ₹8,00,000 to ₹14,00,000 per year (entry-level); ₹14,00,000 to ₹30,00,000 per year (experienced).
5. Data Scientist
- Role: Data Scientists analyze large datasets to extract valuable insights that can drive business strategies. They use advanced statistical and machine learning techniques to build models. They often work with big data tools like Hadoop to handle large datasets.
- Industries: E-commerce, IT services, retail, pharmaceuticals, finance, and healthcare.
- Salary Range: ₹6,00,000 to ₹12,00,000 per year (entry-level); ₹12,00,000 to ₹25,00,000 per year (experienced).
6. Business Intelligence Analyst
- Role: Business Intelligence (BI) Analysts use data analytics tools, including Hadoop, to provide insights into business performance. They work with large datasets to create reports, dashboards, and analytics that support decision-making processes.
- Industries: E-commerce, retail, healthcare, banking, and consulting firms.
- Salary Range: ₹4,50,000 to ₹8,00,000 per year (entry-level); ₹8,00,000 to ₹15,00,000 per year (experienced).
7. Machine Learning Engineer (with Big Data Focus)
- Role: Machine Learning Engineers focus on building algorithms that can learn from and make predictions on large datasets. They often leverage Hadoop to process and analyze vast amounts of data for machine learning model training and validation.
- Industries: E-commerce, tech startups, healthcare, finance, research, and AI companies.
- Salary Range: ₹7,00,000 to ₹14,00,000 per year (entry-level); ₹14,00,000 to ₹25,00,000 per year (experienced).
8. Data Analyst
- Role: Data Analysts extract and analyze data to identify trends, patterns, and correlations. They use tools like Excel, SQL, and Hadoop to work with large data sets and prepare data for analysis. They play a key role in business decision-making.
- Industries: E-commerce, retail, financial services, government, healthcare.
- Salary Range: ₹3,00,000 to ₹6,00,000 per year (entry-level); ₹6,00,000 to ₹12,00,000 per year (experienced).
9. Cloud Data Engineer
- Role: Cloud Data Engineers work with cloud-based big data technologies, including Hadoop, to process and analyze data stored in the cloud. They help in building scalable data pipelines, optimizing cloud resources, and ensuring data availability for analysis.
- Industries: IT services, cloud computing companies, e-commerce, finance.
- Salary Range: ₹6,00,000 to ₹12,00,000 per year (entry-level); ₹12,00,000 to ₹20,00,000 per year (experienced).
10. Data Visualization Specialist
- Role: Data Visualization Specialists transform complex data into interactive charts, graphs, and dashboards. They often use tools like Tableau, Power BI, and Hadoop for data extraction and visualization to make the insights accessible to business leaders.
- Industries: IT services, consulting, financial services, retail, marketing.
- Salary Range: ₹4,00,000 to ₹7,00,000 per year (entry-level); ₹7,00,000 to ₹15,00,000 per year (experienced).
11. ETL Developer (Extract, Transform, Load)
- Role: ETL Developers are responsible for creating systems that extract data from various sources, transform it into a suitable format, and load it into a data warehouse or Hadoop environment for analysis. They ensure data is cleaned and pre-processed before it can be analyzed.
- Industries: IT services, banking, retail, telecommunications, e-commerce.
- Salary Range: ₹5,00,000 to ₹9,00,000 per year (entry-level); ₹9,00,000 to ₹15,00,000 per year (experienced).
12. Hadoop Consultant
- Role: Hadoop Consultants provide expertise on implementing Hadoop frameworks and tools in business settings. They work with organizations to optimize their big data infrastructure and ensure that Hadoop environments are set up efficiently to handle large datasets.
- Industries: IT consulting firms, e-commerce, healthcare, and finance.
- Salary Range: ₹5,00,000 to ₹10,00,000 per year (entry-level); ₹10,00,000 to ₹20,00,000 per year (experienced).
Career Growth and Opportunities:
- Higher Demand for Big Data Professionals: As businesses generate more data and need to make data-driven decisions, the demand for professionals skilled in Hadoop and Big Data technologies continues to grow.
- Specialization: Graduates can specialize in areas like machine learning, artificial intelligence, or cloud-based data management, which are highly lucrative fields.
- Advanced Roles: With experience, professionals can move into senior roles like Big Data Architect, Data Science Lead, or even Chief Data Officer, which come with significantly higher salaries.
Factors Influencing Salaries:
- Experience: Professionals with hands-on experience in big data technologies like Hadoop typically earn higher salaries, particularly in leadership or specialized roles.
- Industry: Some industries, like finance, technology, and healthcare, tend to offer higher salaries due to the high demand for data expertise and the importance of data in these sectors.
- Skills and Tools: Knowledge of advanced tools (e.g., Apache Spark, Hive, HBase) alongside Hadoop can significantly boost a graduate’s salary potential.
- Location: Salaries for big data professionals in major cities like Bengaluru, Hyderabad, Mumbai, and Delhi tend to be higher due to the concentration of tech companies and startups.
Conclusion:
Graduates of the Certificate in Big Data Analytics (Hadoop) program can find rewarding opportunities across a variety of industries, particularly in data-driven organizations. The rapidly growing demand for professionals skilled in Big Data technologies ensures a strong job market with excellent salary potential. As the field evolves, those who stay updated with the latest tools and techniques can progress into higher-paying, specialized roles.
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