Enhanced profitability and research of stocks historical data using distributed system analytics.
SQL, Hadoop, Hive, HBase, PySpark, SparkSQL, Sqoop, Excel, Python, Tableau, Snowflake
- Creating pipelines for transferring data from source(RDBMS) to sink(HDFS)
- Analysis of different stocks (batch processing and online processing)
- Using Hive, PySpark batch processing and for online processing HBase, Kafka for transferring and analysing.
- Transferring output data to client(RDBMS) using SQOOP
- Using Tableau generating reports for easy and best decision making