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Confluent Kafka Developer & Architect with Admin training

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40 Hours

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Course offered by Amit Raj

237 reviews

Confluent Kafka architect and development using events for banking /Retails Learn Basic Kafka – Confluent Note: most of the course outline is taken from confluent directly. Total hours: 30- 35 hrs - POC will be done by the students as core development work for events. - Admin and security: lab can be tested only when infra is available with confluent Kafka. - Use case and project will be part of implementation analysis with solution approach for events in the project. - Students can select 3 to 4 POC and 1 Project module case study to analyze implementation and code logic for events .

 

Sl. No Subject Area Descriptions Comments 1 KSQL transformation for simple schemas Transform using KSQLDB. Confluent : discussion on solution using Confluent 2 DLQ configuration and testing in sink connectors Config DLQ in Sink connectors Confluent : discussion on solution using Confluent 3 HDFS sink connector configuration and testing Loading the data to HDFS using Sink Connector. Confluent : discussion on solution using Confluent 4 MQ testing with Rfh util and confluent kafka sink connector Loading data into MQ using sink connector Confluent : discussion on solution using Confluent 5 DB2 sink connector configuration and testing Data loading into DB2 using sink connector Confluent : discussion on solution using Confluent 6 Oracle sink connector configuration and testing Data loading into Oracle using sink connector Confluent : discussion on solution using Confluent 7 Writing data from confluent kafka topic to HDFS (CDP ) Loading the data to HDFS using Sink Connector. Confluent : discussion on solution using Confluent 8 Notification alerts in Confluent - Configure triggers and actions to track status of consumers/connectors Triggers and actions to track status of consumers/ connectors Confluent : discussion on solution using Confluent 9 Configure/Test retry scenario in MQSink connector in case IBM MQ is down Test MQSink connector in case IBM MQ is down Confluent : discussion on solution using Confluent 10 Configure/test retry scenario in case Database is down in custom connector Test Database is down in custom connector Confluent : discussion on solution using Confluent 11 Divide one topic data to different topic through KSQL for Sample schema Divide the topic using KSQLDB Confluent : discussion on solution using Confluent 12 Publishing single to multiple topic Spliting the data from single topic to multiple topics based on eventType Confluent : discussion on solution using Confluent. 
Student will learn how to handle real time streaming on the fly 

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About the Trainer

Amit Raj picture

4.8 Avg Rating

237 Reviews

348 Students

12 Courses

Amit Raj

MSCIT

18 Years of Experience

About Me :
• Overall total 14.5+ years of Experience years of Experience in Application Design, Development & Deployment of Hadoop Eco System/Java/J2EE systems with good exposure to Enterprise Architectures.
• Relevant Experience 8.2 yrs into Big Data technologies working on multiple clients and domain knowledges.
• Experienced in Cassandra data modelling, cluster setup and data management.
• Experienced in working with Spark-RDD, Spark SQL and Spark Data Frame using MLIb to analyze structure data queries.
• Experienced to design solution using Spark Streaming and Kafka Streaming for Payment Gateway / point of sales events.
• Individual Contribution (Kafka Architect) : Delivered UAT and PROD Cluster within the timeline for Kafka cluster using Cloudera 6.x, CSP 2.0 .
• Implemented unified data platform to gather data from different sources using Kafka Producers and consumers in Scala and java.
• Solid background in Object-Oriented analysis & design, UML and various design patterns.
• Worked using Azure cloud(Blob,EventHub),kubernetes ,docker with Spark, scala ,Schema Registry , Avro Schema with home security application for Honeywell
• Implemented KSQL ,KTable and KStream using Confluent Kafka along with Kafka Connect .
• Hands on Data bricks - Databricks Clusters , Data Lakehouse , Delta lake , DBFS, EXPLORE, Analyze, Clean, Transform and Load Data in Databricks.
• Hands on Azure service - ADF ,ADLS ,Event hub, Security , NoSQL
• Motivated Technical Architect with 5 years of progressive experience.
• Energetic self-starter and team builder. Navigates high-stress situations and achieves goals on time and under budget.
• Effectively manages assignments and team members.
• Dedicated to self-development to provide expectation-exceeding service. Customer-focused , successfully contributing to company profits by improving team efficiency and productivity.
• Utilizes excellent organizational skill to enhance efficiency and lead teams to achieve outstanding delivery.

SKILLS
• Database architecture
• Database architecture development
• Data architecture
• Big Data ETL
• Technical solution development
• Azure data solutions
• Data insight provision
• Technical guidance
• IT architecture
• Technical solutions
• Big data frameworks

Technical Skills:

Hortonworks2.5, Cloudera5/6, Apache Hadoop2/3 ,Spark2/3,Apache Kafka, Confluent Kafka, Hive 2/3,Impala,Sqoop,OOZie,Zookeeper, Apache NiFI, Splunk ,Snowflake, Data Build tool (DBT) , HBase, Apache Cassandra /DataStax Cassandra , Data bricks , Azure Cloud , AWS cloud ,Airflow etc. .
Programming Language Python ,Scala & Java
Other Tools Kibana,Logstash,ElasticSearch,ELK-Hadoop,SBT, Elassandra, Tableau,

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