{"id":4737,"date":"2025-10-27T06:34:58","date_gmt":"2025-10-27T06:34:58","guid":{"rendered":"https:\/\/omxwebsites.com\/gammatica\/?page_id=4737"},"modified":"2025-11-07T05:46:35","modified_gmt":"2025-11-07T05:46:35","slug":"big-data-advanced","status":"publish","type":"page","link":"https:\/\/omxwebsites.com\/gammatica\/big-data-advanced\/","title":{"rendered":"Big Data – Advanced"},"content":{"rendered":"\t\t
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Big Data - Advanced<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Learning Format<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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Total training duration<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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80-90 hrs (2 months)<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Syllabus<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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Certification<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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Big Data Engineering \u2013 Advanced<\/h2>\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\t\t\t\t\t\t\t\t\tThe Advanced course focuses on building enterprise-level big data solutions using advanced tools and cloud platforms. Learners will master real-time data processing, data lake architecture, data governance, and performance optimization. It includes hands-on projects using Apache Spark, Kafka, Airflow, and cloud services (AWS\/GCP\/Azure) to design end-to-end scalable data systems.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t
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Syllabus Summary<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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Kafka Basics<\/strong><\/p>

  • Kafka architecture (topics, partitions, brokers)<\/li>
  • Producers & Consumers<\/li>
  • Hands-on:<\/strong> Ingest sample data into Kafka topics<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t
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    Kafka Integration with Spark<\/strong><\/p>

    • Kafka<\/strong> \u2192 Spark Structured Streaming ingestion<\/li>
    • Running streaming ETL jobs in PySpark<\/li>
    • Hands-on:<\/strong> Real-time pipeline from Kafka \u2192 Spark<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t
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      Databricks for Big Data Engineering<\/strong><\/p>

      • Databricks architecture (clusters, notebooks, jobs)<\/li>
      • Running PySpark jobs on Databricks<\/li>
      • Using Delta Lake in Databricks (schema enforcement, time travel)<\/li>
      • Hands-on:<\/strong> Batch ETL pipeline in Databricks<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t
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        Advanced Databricks Use Cases<\/strong><\/p>

        • Integrating Kafka streams into Databricks<\/li>
        • Optimizing Delta tables (merge, upserts, deletes)<\/li>
        • Job scheduling and monitoring in Databricks<\/li>
        • Mini Project:<\/strong> Near real-time ETL with Databricks<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t
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          Airflow Fundamentals<\/strong><\/p>

          • Airflow architecture (scheduler, webserver, workers)<\/li>
          • Writing first DAGs for Spark jobs<\/li>
          • Operators, tasks, and dependencies<\/li>
          • Hands-on:<\/strong> Simple batch workflow in Airflow<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t
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            Hive Queries & Integrations<\/strong><\/p>

            • Hive DDL\/DML commands<\/li>
            • Partitioning & Bucketing basics<\/li>
            • Performance considerations in Hive<\/li>
            • Mini Project:<\/strong> Sales dataset analysis in Hive<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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              Course Summary<\/h2>\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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              \n\t\t\t\t\t\tTech & Non-Tech Working professional, Freshers, Graduate from any domain.\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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              \n\t\t\t\t\t\tGet your queries solved with daily dedicated doubts solving sessions.\n\n\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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              \n\t\t\t\t\t\tExperts and trainer for top-tech companies.\n\n\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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              \n\t\t\t\t\t\t10+ ISO Globally recognized certified\n\n\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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              \n\t\t\t\t\t\t100% Live Learning with experienced instructors and hands-on sessions.\n\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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              \n\t\t\t\t\t\tGet practical experience with real-world projects for a career in analytics.\n\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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              Big Data – Advanced Learning Format Online mode Total training duration 80-90 hrs (2 months) Syllabus 6 Weeks Certification Yes Big Data Engineering \u2013 Advanced The Advanced course focuses on building enterprise-level big data solutions using advanced tools and cloud platforms. Learners will master real-time data processing, data lake architecture, data governance, and performance optimization. It includes hands-on projects using Apache Spark, Kafka, Airflow, and cloud services (AWS\/GCP\/Azure) to design end-to-end scalable data systems. Enroll Now Syllabus Summary Week 1 Kafka Basics Kafka architecture (topics, partitions, brokers) Producers & Consumers Hands-on: Ingest sample data into Kafka topics Week 2 Kafka Integration with Spark Kafka \u2192 Spark Structured Streaming ingestion Running streaming ETL jobs in PySpark Hands-on: Real-time pipeline from Kafka \u2192 Spark Week 3 Databricks for Big Data Engineering Databricks architecture (clusters, notebooks, jobs) Running PySpark jobs on Databricks Using Delta Lake in Databricks (schema enforcement, time travel) Hands-on: Batch ETL pipeline in Databricks Week 4 Advanced Databricks Use Cases Integrating Kafka streams into Databricks Optimizing Delta tables (merge, upserts, deletes) Job scheduling and monitoring in Databricks Mini Project: Near real-time ETL with Databricks Week 5 Airflow Fundamentals Airflow architecture (scheduler, webserver, workers) Writing first DAGs for Spark jobs Operators, tasks, and dependencies Hands-on: Simple batch workflow in Airflow Week 6 Hive Queries & Integrations Hive DDL\/DML commands Partitioning & Bucketing basics Performance considerations in Hive Mini Project: Sales dataset analysis in Hive Kafka Basics Kafka architecture (topics, partitions, brokers) Producers & Consumers Hands-on: Ingest sample data into Kafka topics Kafka Integration with Spark Kafka \u2192 Spark Structured Streaming ingestion Running streaming ETL jobs in PySpark Hands-on: Real-time pipeline from Kafka \u2192 Spark Databricks for Big Data Engineering Databricks architecture (clusters, notebooks, jobs) Running PySpark jobs on Databricks Using Delta Lake in Databricks (schema enforcement, time travel) Hands-on: Batch ETL pipeline in Databricks Advanced Databricks Use Cases Integrating Kafka streams into Databricks Optimizing Delta tables (merge, upserts, deletes) Job scheduling and monitoring in Databricks Mini Project: Near real-time ETL with Databricks Airflow Fundamentals Airflow architecture (scheduler, webserver, workers) Writing first DAGs for Spark jobs Operators, tasks, and dependencies Hands-on: Simple batch workflow in Airflow Hive Queries & Integrations Hive DDL\/DML commands Partitioning & Bucketing basics Performance considerations in Hive Mini Project: Sales dataset analysis in Hive Course Summary Eligibility Tech & Non-Tech Working professional, Freshers, Graduate from any domain. Live Doubt Solving Get your queries solved with daily dedicated doubts solving sessions. Instructor Experts and trainer for top-tech companies. Certification 10+ ISO Globally recognized certified Mode of Learning 100% Live Learning with experienced instructors and hands-on sessions. Real time projects Get practical experience with real-world projects for a career in analytics. 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