What will you learn in Big Data Integration and Processing Course
Retrieve and query data from relational (PostgreSQL) and NoSQL (MongoDB, Aerospike) databases.
Learn data aggregation, manipulation, and analysis using Pandas and data frames.
Explore big data integration tools like Splunk and Datameer for practical insights.
Execute big data processing tasks on Hadoop and Spark platforms.
Understand when data integration is necessary in large-scale analytical applications.
Gain foundational knowledge for handling, managing, and processing large datasets efficiently.
Program Overview
Module 1: Welcome
⏳ 1 hour
Introduction to big data integration and processing concepts.
Installing Docker, working with Jupyter notebooks, and setting up hands-on materials.
3 videos, 5 readings, 1 discussion prompt.
Module 2: Retrieving Big Data (Part 1)
⏳ 1 hour
Covers relational data retrieval and querying using PostgreSQL.
5 videos, 2 readings.
Module 3: Retrieving Big Data (Part 2)
⏳ 2 hours
Explore NoSQL data retrieval, aggregation, and Pandas data frames.
Hands-on assignments with MongoDB, Aerospike, and Pandas.
5 videos, 3 readings, 2 assignments, 1 discussion prompt.
Module 4: Big Data Integration
⏳ 2 hours
Introduction to data integration using Splunk and Datameer.
Practical examples of information integration processes.
11 videos, 4 readings, 2 assignments, 1 discussion prompt.
Modules 5–7
⏳ 2–3 hours each
Focus on advanced big data processing patterns and hands-on exercises with Hadoop and Spark.
Integrate data retrieval, aggregation, and analysis skills in real-world scenarios.
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Job Outlook
Prepares learners for roles such as Big Data Analyst, Data Engineer, and Business Intelligence Specialist.
Skills applicable across tech, finance, healthcare, retail, and e-commerce industries.
Knowledge of big data integration and processing improves employability in data-driven companies.
Provides practical experience with industry-standard tools and platforms.
Explore More Learning Paths
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Related Courses
Introduction to Big Data Course – Build a strong foundation in big data concepts, tools, and industry applications to understand how large datasets are managed and analyzed.
Data Engineering, Big Data, and Machine Learning on GCP Specialization Course – Learn how to design data pipelines, process massive datasets, and develop machine learning solutions using Google Cloud technologies.
Big Data Integration and Processing Course – Master the core techniques required to integrate, clean, transform, and process big data efficiently across distributed systems.
Related Reading
Gain deeper insight into how effective data management drives modern analytics:
What Is Data Management? – Understand the key processes, tools, and strategies organizations use to govern, store, and utilize data effectively.
Specification: Big Data Integration and Processing Course
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