Hands on Statistical and Data Visualization Tool:
Analyst/Aspirant should have fair knowledge of Quantitative Techniques/Statistical tests. They should be able to work with any of the statistical tools such as SAS (Statistical Analysis System), R, Tableau, Minitab, MS Excel etc. Analysts must understand and able to interpret Descriptive Statistics.In current scenario Aspirants have an added advantage if they have hands on SAS (SAS is market leader in analytics field) and R.
Knowledge on Computer Science Programming:
In day to day work Analysts are required to Know SAS Programming, R Programming, Python etc. Now a days R and Python are gaining lot of attention in the market as they are free / open source and tutorials on them are easily available. In day to day work Analysts are required to perform repetitive tasks such as generation of reports (fortnightly, weekly, monthly), graphs, charts, Data Management tasks etc. These tasks can be easily automated with the help of VBA Macros Programming and saves lot of time
Knowledge on at least one Database:
Many times Analysts are required to interact with databases such as MS SQL Server, Oracle, Teradata, DB2, Sybase, MySQL etc to perform manipulations with the tables such as Insert, Select ,Update, Delete records/rows from tables. This knowledge also helps to understand how the data is stored in the tables and the related functionality.
Any analysis done by Analyst is irrelevant if it is not done with respect to Country’s economy, Industry or Sector and different players or competitors operating in that domain and company’s own perspective. In such cases, Analyst must of strong Business knowledge to understand and do proper analysis.
Analytical and Logical Reasoning Skills: Analyst/Aspirant should have good problem solving, logical thinking skills and feel comfortable while working with numbers. They should have good grasping capability. They should be able to understand the flow of data /values in the project. Last but not the least, Analyst/Aspirant should be able to make inferences on the basis of data available to them.
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