Power BI Project

Please find my relevant experience : Skills  Technologies- O365, SharePoint 2013, SharePoint 2010, MOSS 2007, WWF, SSL, COM/DCOM, ActiveX, MDAC, AJAX, SOAP. Framework- .Net Framework 2.0, 3.5, 4.0, 4.5. Languages- C#, Angular JS, HTML, DHTML, Java Script, JQuery. Tools- • Design Tool: SharePoint Designer 2007, 2010, 2013, Microsoft Visio, Nintex workflow. • Development Tool: Microsoft Visual Studio 2012/2010/2008/2005 • Testing Tools: Rational ROBO. BI Tools Performance Point Server. • Reporting Tools: Crystal Reports, SSRS, SSIS, PowerBI. • Version Control Tools: TFS, SVN. • Database- SQL Server 2005/2008/2012, MS-ACCESS. • Operating Systems- Windows Server (2008/2010/2012) Lets discuss further so that we can take this forward. Thanks.

Highly effective Data Engineer with over 8 years of Power BI experience, Andrew Kim is specialising in data integration, data conversion, data engineering, ETL, big data architect, data analytics, data visualization, data science, analytics platforms, and cloud architecture. He has an array of skills in building data platforms, analytic consulting, trend monitoring, data modelling, data governance and machine learning. SPECIALTIES TECHNICAL SKILLS • Big Data (Hortonworks and Cloudera) – Spark(PySpark, Scala), Kafka, Hive,Impala, NiFi, HDFS, Sqoop, Ranger, Yarn, Solr, SAM, Schema Registry, SuperSet • Language: Python, Scala, R, JavaScript • Data Visualization – Tableau, PowerBI, OBIEE, DOMO • Plunk & ELK Stack – ElasticSearch, Logstash, Filebeat, Kibana • AWS – S3, RefShift, DynamoDB, Athena, Kinesis, EMR, Aurora, Glue • Azure – Data Warehouse, Polybase, SQL Server, HDInsight, SSIS, SSAS • ETL – Informatica Power Centre, Informatica Big Data Management (BDM), SSIS • Data Science & Engineering – R / RStudio / SparkR Packages: dplyr, ggplot2, stringr, plyr, carrat, SparkR, NLP, tibble, TensorFlow, curl, Python / PySpark, MLLib • Libraries: MLLib, NumPy, SciPy, Pandas, Matplotlib, Seaborn, SciKit-Learn • DBMS / OLAP – Oracle, SQL Server, TeraData, MySQL, Postgres, Essbase, SSAS • Data Modelling – Kimball, Vault • Machine Learning / Statistical Modelling - Linear Regression, ?Logistic Regression, Classification and Regression Trees, Naive Bayes, ?K-Nearest Neighbors