BIG DATA ANALYTICS
Course 2309
4 Hours
$299
Big data holds the answers to tomorrow’s challenges. This 4-hour course teaches professionals how to harness the power of massive datasets, explore key technologies like Hadoop and Spark, and transform insights into action across industries.
Target Audience
- Data analysts and aspiring data scientists
- IT professionals working with large datasets
- Managers and decision-makers leveraging big data for strategy
- Professionals seeking to understand and utilize big data analytics
Course Format:
- Live or Pre-Recorded Lectures: Delivered by big data analytics experts.
- Interactive Activities: Hands-on exercises, real-world case studies, and group discussions.
- Resources Provided: Access to sample datasets, tool guides, and a list of additional learning resources.
Payment Information: We accept credit card payments.
Course Objectives
- Understand the concepts and importance of big data analytics.
- Learn about big data technologies such as Hadoop, Spark, and cloud-based platforms.
- Gain hands-on experience processing and analyzing large datasets.
- Develop skills to apply big data insights in business decision-making.
Course Structure:
Introduction to Big Data Analytics
- What is big data? Characteristics (volume, velocity, variety, veracity, and value).
- The role of big data analytics in driving business transformation.
- Overview of big data architecture and tools.
Tools and Technologies for Big Data
- Overview of key technologies: Hadoop, Apache Spark, and cloud platforms (e.g., AWS, Azure, GCP).
- Choosing the right tool for specific business needs.
- Introduction to data lakes, warehouses, and real-time analytics.
Analyzing Big Data
- Techniques for analyzing structured, semi-structured, and unstructured data.
- Introduction to machine learning for big data analysis.
- Building scalable data pipelines for analytics.
Applying Big Data Insights
- Translating analytics into actionable business strategies.
- Best practices for data visualization in big data analytics.
Group Rates Available!
Bring your team and save – perfect for healthcare organizations looking to train multiple leaders.
Discounts available for organizations enrolling 5+ participants.
Class Schedule
Rates below are for each participant.
Who is this course for?
Who is this course for?
This course is designed for data analysts, IT professionals, managers, and decision-makers who want to understand and leverage big data analytics to drive business success.
What will I learn in this course?
You’ll learn about:
- The fundamentals of big data and its key characteristics.
- Tools like Hadoop, Apache Spark, and cloud-based platforms for big data analytics.
- Techniques for processing and analyzing large datasets.
- How to translate insights into actionable strategies for business decision-making.
Do I need prior experience with data analytics or programming?
While prior experience in basic data analytics or programming is helpful, this course introduces concepts and tools in a step-by-step manner, making it accessible to beginners.
What tools and platforms will I use in this course?
You’ll gain exposure to:
- Hadoop and Apache Spark for big data processing.
- Cloud-based platforms like AWS, Azure, or Google Cloud for data analysis.
- Tools for data visualization and reporting.
How does big data analytics differ from traditional data analytics?
Big data analytics focuses on handling and analyzing massive datasets that traditional analytics tools may not process efficiently. It involves advanced tools and techniques for scalability, speed, and extracting insights from diverse data types.
Can I use what I learn in this course for my industry?
Absolutely! Big data analytics has applications in various industries, including healthcare, finance, retail, manufacturing, and logistics. The course includes industry-specific case studies to showcase its versatility.
How does this course cover data visualization?
You’ll learn best practices for visualizing insights from big data, including using dashboards and advanced visualization techniques to communicate trends and results effectively.
What are some practical use cases covered in the course?
The course explores use cases like:
- Predicting customer behavior in retail.
- Optimizing resource allocation in healthcare.
- Fraud detection in finance.
- Analyzing supply chain efficiency in manufacturing.