ElasticSearch
Skills / Capabilities: 1. Capacity planning, setting up and configuring an ES cluster with sharding and replication 2. Indexing all types of logs: Weblogs, Syslogs, DB logs, Network logs 3. Mapping RDBMS model into ES 4. Kafka-ES pipeline Case Study 1: Matching persons and addresses between census data and electoral data using text matching algorithms (Levenshtein distance algorithm/Jaccard Similarity Algorithm and Fuzzy match). Doing this in ES is 10X faster than what it takes in Spark. Case Study 2: For a client in Airline industry aiming to create disruptive tech backend: Set up the ELK stack and programmed the data ingestion layer for storing and querying 4-year historical flights data for airlines and airports across the globe (take offs, landing, cancelled flights etc.). The key requirement here was to achieve sub-second query times. Case Study 3: Built a real-time dashboard using the ElasticSearch and Kibana to visualize the results from Twitter streaming data.
O mně
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.
