Data analytics is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software. Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions and by scientists and researchers to verify or disprove scientific models, theories and hypotheses.
People interested in data and analysis are inquisitive, curious and creative. They can take abstract business issues and derive an analytical solution and share knowledge and clearly articulate insights to technical staff, management and decision makers. They can communicate to a diverse audience at multiple levels of the organization. In addition, they want to challenge existing best practices, explore new alternatives and introduce new initiatives.
- Programming languages such as R, Python, PHP, Ruby, Matlab, JAVA, C++, SQL, SAS, SPSS
- Multivariate statistics - regression, principal components analysis and clustering
- Data-driven predictive model development
- Large Dataset experience using Teradata, Oracle or SQL
- Business Intelligence tools including Business Objects, MicroStrategy and Tableau
- Big Data technologies including Hadoop, MapReduce, Hive, Pig, Cassandra
Some sample job titles:
- Systems Analyst
- Business Analyst
- Data Analyst
- Business Intelligence Analyst
- Health Informatics Analyst
- Data Visualization Specialist
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