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See why over 25,000+ Students choose ACTE
Curriculum Designed By Experts
Expertly designed curriculum for future-ready professionals.
Industry Oriented Curriculum
An exhaustive curriculum designed by our industry experts which will help you to get placed in your dream IT company
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30+ Case Studies & Projects
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9+ Engaging Projects
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10+ Years Of Experience
Big data Analytics Training Projects
Become a Big data Analytics Expert With Practical and Engaging Projects.
- Practice essential Tools
- Designed by Industry experts
- Get Real-world Experience
Data Cleaning
Work with a raw dataset (e.g., sales data) and preprocess and data clean, filter, and structure it for analysis using Python or R.
Basic Data Visualization
Use tools like Tableau or Power BI to create interactive dashboards displaying key insights from a dataset (e.g., customer purchase trends).
Simple SQL Analytics
Perform SQL queries on a relational database to extract meaningful insights, such as customer segmentation or sales growth patterns.
Sentiment Analysis on Social Media Data
Analyze Twitter or Facebook data using NLP techniques to classify customer sentiments toward a brand.
Real-Time Data Processing with Apache Kafka
Build a Data Processing Communicate a real-time streaming pipeline that ingests, processes, and visualizes data.
Predictive Analytics on Sales Data
Use machine learning models like linear regression to predict future sales based on historical data.
Recommendation System for E-Commerce
Develop a collaborative filtering-based recommendation engine for an online shopping platform.
Fraud Detection in Financial Transactions
Implement anomaly detection algorithms on transactional data to identify fraudulent activities.
Big Data Pipeline with Hadoop and Spark
Build an end-to-end data pipeline using Hadoop, Spark, and Hive for large-scale data processing.
Key Features
Practical Training
Global Certifications
Flexible Timing
Trainer Support
Study Material
Placement Support
Mock Interviews
Resume Building
Batch Schedule
Weekdays Regular (Class 1Hr - 1:30Hrs) / Per Session
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10 - Nov - 2025 Starts Coming Monday ( Monday - Friday) 08:00 AM (IST)
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12 - Nov - 2025 Starts Coming Wednesday ( Monday - Friday) 10:00 AM (IST)
Weekend Regular (Class 3Hrs) / Per Session
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15 - Nov - 2025 Starts Coming Saturday ( Saturday - Sunday) 10:00 AM (IST)
Weekend Fast-track (Class 6Hrs - 7Hrs) / Per Session
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16 - Nov - 2025 Starts Coming Saturday ( Saturday - Sunday) 10:00 AM (IST)
Enquiry Form
- Learning strategies that are appropriate and tailored to your company's requirements.
- Live projects guided by instructors are a characteristic of the virtual learning environment.
- The curriculum includes of full-day lectures, practical exercises, and case studies.
Big data Analytics Training Overview
Big data Analytics Training in Velachery with Career Paths
A career in Big Data Analytics Training Center in Velachery opens doors to numerous opportunities in data-driven industries. Professionals can pursue roles such as Data Analyst, Big Data Engineer, Data Scientist, Machine Learning Engineer, Business Intelligence Analyst, and AI Specialist. These roles involve working with massive datasets, uncovering insights, and leveraging advanced analytics for decision-making. Industries like finance, healthcare, e-commerce, and marketing are continuously seeking skilled big data professionals to optimize operations and enhance customer experiences.
The Requirements for a Big Data Analytics Course Training in Velachery
- Programming Knowledge: A basic understanding of programming is essential for working with big data. Languages like Python, R, Java, or SQL are widely used in data analytics for data manipulation, querying, and statistical analysis.
- Understanding of Databases: Since big data involves handling vast amounts of structured and unstructured data, knowledge of databases is crucial. SQL databases such as MySQL and PostgreSQL are useful for managing structured data, while NoSQL databases like MongoDB.
- Big Data Frameworks & Tools: Professionals working in big data analytics need to be familiar with frameworks such as Apache Hadoop, Apache Spark, and Kafka. These tools help process, analyze, and manage large datasets efficiently across distributed computing environments.
- Analytical & Statistical Skills: A strong foundation in statistics, probability, and data analytics is necessary for extracting insights from big data. Knowledge of techniques such as regression analysis, clustering, hypothesis testing, and predictive modeling helps analyze trends.
- System & Technical Requirements: To work with big data tools, learners should have access to a system with at least 8GB RAM, a modern processor, and a stable internet connection for cloud-based analytics platforms.
Reasons to Consider Enrolling in a Big data Analytics Training in Velachery
Big Data Analytics Placement Training in Velachery is a rapidly expanding field, offering high demand and lucrative career opportunities. Companies increasingly rely on data-driven decision-making, making professionals with big data expertise highly valuable. Enrolling in a Big Data Analytics course helps you gain hands-on experience with real-world datasets, machine learning applications, and cloud-based analytics platforms. Additionally, certification enhances job prospects, allowing candidates to stand out in competitive job markets.
Techniques and Trends in Big Data Analytics Course Development in Velachery
- Real-Time Data Processing: With the increasing demand for instant insights, real-time data processing has become a crucial aspect of big data analytics. Technologies like Apache Kafka, Apache Flink, and Spark Streaming enable businesses to process and analyze streaming data from various sources in real time. This is particularly useful in applications such as fraud detection, recommendation systems, and IoT data processing.
- Predictive Analytics & Machine Learning: Machine learning and predictive analytics are transforming big data by providing businesses with valuable foresight into future trends. Implementing AI-driven models helps companies analyze historical data and make informed decisions about customer behavior, market fluctuations, and operational efficiencies.
- Data Engineering & ETL Pipelines: Efficient data engineering is the backbone of any big data solution. Extract, Transform, and Load (ETL) processes help in automating data workflows to ensure seamless integration from multiple sources into a unified platform. Tools like Apache Airflow, Talend, and cloud-based ETL solutions allow organizations to manage large-scale data ingestion, transformation, and storage efficiently.
- Cloud-Based Big Data Solutions: With the rise of cloud computing, organizations are increasingly adopting cloud-based big data solutions for scalability, flexibility, and cost-efficiency. Platforms like AWS EMR, Google BigQuery, and Azure Synapse Analytics.
- Data Governance & Security: As data volumes grow, ensuring data privacy, security, and compliance becomes paramount. Implementing robust data governance policies and security frameworks helps organizations maintain data integrity while adhering to industry regulations such as GDPR, HIPAA, and CCPA.
The Most Recent Big Data Analytics Course Class in Velachery Tools
The latest advancements in big data analytics Certification Course in Velachery introduce powerful tools that enhance data processing and analysis. Apache Spark continues to dominate as a leading big data framework, offering high-speed processing capabilities. Delta Lake improves data reliability by adding ACID transactions to data lakes. MLflow is revolutionizing machine learning model management within big data workflows. Additionally, cloud-native big data platforms like Snowflake and Databricks are gaining popularity for their scalability and ease of integration with AI-driven analytics.
Career Opportunities After Big data Analytics Training
Big Data Engineer
A Big Data Engineer is responsible for designing, building, and maintaining large-scale data processing systems. They develop and optimize data pipelines using tools like Hadoop, Spark, and Kafka.
Data Analyst
A Data Analyst interprets complex data to help organizations make informed business decisions. They use SQL, Python, and visualization tools like Tableau or Power BI to analyze trends, patterns, and correlations in datasets.
Data Scientist
A Data Scientist applies machine learning and statistical modeling techniques to extract meaningful insights from big data. They work with Python, R, TensorFlow, and deep learning framework systems.
Business Intelligence Analyst
A Business Intelligence (BI) Analyst transforms raw data into actionable business insights. They create dashboards and reports using BI tools such as Tableau, Power BI, and QlikView performance tracking, and business growth planning.
Machine Learning Engineer
A Machine Learning Engineer develops algorithms and AI models to automate data-driven processes. They work with large datasets, train machine learning models, and deploy them in production using cloud platforms like AWS, Google Cloud, and Azure.
Data Architect
A Data Architect designs the overall structure and framework of big data systems. They establish best practices for data management, ensure data security, and optimize database performance. NoSQL databases, and distributed computing technologies.
Skill to Master
Data Processing & Transformation
Big Data Frameworks
Data Visualization
Machine Learning for Big Data
Data Warehousing & ETL
SQL & NoSQL Databases
Data Mining Techniques
Real-Time Data Processing
Cloud Computing
Programming Skills
Data Security & Governance
Business Intelligence & Decision Making
Tools to Master
Apache Hadoop
Apache Spark
Apache Flink
Apache Kafka
Tableau
Power BI
Apache Hive
MongoDB
Elasticsearch
Google BigQuery
AWS Redshift
Python (Pandas, NumPy, Scikit-learn)
Learn from certified professionals who are currently working.
Training by
Rajesh Kumar, having 12+ yrs of experience
Specialized in: Big Data Analytics, Data Engineering, Apache Spark, Hadoop, and Machine Learning.
Note: Rajesh is known for his hands-on approach in training professionals on real-world big data applications, optimizing large-scale data processing, and implementing predictive analytics.
We are proud to have participated in more than 40,000 career transfers globally.
Big data Analytics Certification
A Big Data Analytics certification validates your expertise in handling and analyzing large datasets, making you a valuable asset in today’s data-driven world. It enhances your technical skills in data processing, visualization, and machine learning, giving you a competitive edge in the job market.
While specific prerequisites vary, a basic understanding of programming (Python, SQL, or Java), statistics, and data management concepts is recommended. Knowledge of big data tools like Hadoop, Spark, or Tableau can be beneficial. Some certifications may also require prior experience in data analytics or related fields.
While real-world experience is not always mandatory, it significantly enhances your learning and job prospects. Practical experience helps apply theoretical concepts to real business scenarios, making you a more competitive candidate. Many training programs include hands-on projects to simulate industry challenges, which can be useful when seeking certification.
ACTE’s Big Data Analytics Certification can be a valuable investment if you aim to build a strong foundation in data analytics. The course provides hands-on training, industry-relevant tools, and expert mentorship, making it a great option for career growth.
Frequently Asked Questions
ACTE offers multiple flexible learning modes for the Big Data Analytics Course to suit the needs of different learners. The course is available in classroom training, where students receive in-person instruction with hands-on practice. Online Instructor-Led Training allows learners to attend live, interactive sessions from anywhere.
- Register for the Course.
- Join Live Sessions.
- Access Study Materials.
- Engage in Hands-on Projects.
- Yes, ACTE provides access to recorded sessions for students who miss a live class. Every session is recorded and uploaded to the learning portal, allowing learners to revisit lessons anytime. This ensures that students do not fall behind in their coursework and can learn at their own pace. Additionally, learners can clarify doubts during the next live session or through one-on-one support from trainers.
- Yes, ACTE offers free demo sessions to provide an overview of the course.
- You can register for a demo class by contacting the ACTE support team.
- The demo includes an introduction to the course curriculum, trainers, and teaching approach.
- It helps you understand how the training will be delivered before making a commitment.
- The duration of the Big Data Analytics Course at ACTE varies based on the chosen mode of learning. The fast-track course is completed in 4 to 6 weeks, while the regular track course takes 2 to 3 months with flexible class schedules. Weekend batches are also available for working professionals. Learners who opt for self-paced training can complete the course at their own convenience with lifetime access to materials.