Real-time Events Processing

von Everlytics Data Science
Real-time Events Processing

Business Case Collect, process and analyze the events that are generated when users interact with digital radio streams from multiple broadcasters and feed this intelligence to downstream applications. Objective Process a real-time Amazon Kinesis stream using Hive/Pig and push the aggregated data to MySQL for consumption by downstream apps Stream Throughput: 16 MB/sec (4 shards) Processing mode: batch at 10-min intervals

image of username Everlytics Data Science Flag of India BANGALORE, India

Über Mich

I have 18 yoe in ML, Big Data, BI and related data science works. Focused on helping a few niche technology companies in bringing their (mostly disruptive) ideas to life. A design thinker, responsive and collaborative individual with strong background in data science. My clients engage me to architect and develop solutions that have Big Data and/or Machine Learning as differentiating components. - Predictive Analytics & ML - Big Data Backends - Streaming Data Pipelines - Good Old ETL & BI Machine Learning: Regression, Association (apriori), Classification (decision trees, random forest, logit), Clustering (k-means) Python, Scikit-learn Dataiku, RapidMiner, Azure ML Studio, SageMaker Data Visualisation: Power BI, Tableau, Qlik, Klipfolio, Kibana DW and ETL: Snowflake, BigQuery, Athena, AirFlow, SSIS Stream Processing: Spark, Flume, Kafka, Kafka Streams, Kinesis Elasticsearch (ELK) I believe in simple and future-proof design. Putting trust and satisfaction before money.

$50 USD/Std

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