it_user357489

55 POINTS3 YEARS
Job function
Business Intelligence Specialist
Company size
501-1,000 Employees
Industry
Software R&D Company
Years of experience
5-10 years
Since Dec 2015, it_user357489's postings have been viewed 119 times on IT Central Station.
Bio

7+ years of experience in Database administration and Developing Data related products using SSAS , SSIS , SSRS , Hadoop and R.
Strong understanding of multiple RDBMS systems – SQL Server, Oracle , Teradata, and MySQL
Exploratory Data analysis using R , Matlab , Excel, Power Pivot , Powerview , Sharepoint
Experience building ETL packages from a variety of source systems( Web services , CRM , ERP)
Designing One Customer View using data from various systems (CRM, ERP, Licensing Sytems , Professional Services automation tools , Support Tools , Helpdesk Management tools etc )
Designing tools for Resource Planning and effective Resource to get best ROI.
Provisioning, installing, configuring, monitoring, and maintaining Hadoop Instance.Connectivity between HDFS to Reporting tools like Tableau, Qlikview, etc .
Strong analytical skills and high attention to detail including ability to review, analyse and manipulate data to produce quality management reports and maintain quality control.
Strong experience in Big Data Ecosystems: Hadoop, MapReduce, HDFS, HBase, Zookeeper, Hive, Impala, Pig, Sqoop, Oozie and Flume.
Experience working with very large data sets, how to build programs that leverage the parallel capabilities of Hadoop and MPP platforms
Build and deploy cubes using SSAS in an efficient, scalable, and repeatable manner checking in code into source control systems
Model, organize and prepare data using RDBMS Tools (T-SQL, PL/SQL) as well as distributed programming frameworks (MapReduce)
Deep experience in Business Intelligence cube design approaches
SSAS, cube development with very large dataset, high data volume ETL experience.
Sentiment analysis using Social media platforms such as Twitter , Facebook, Linkedin , Foursquare
Customer Centricity , Customer Segmentation , Customer Trends
Web scrapping, text mining and predictive modeling using R


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