PROC SQL In SAS | Data Science Tutorial | Simplilearn
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<a href="http://tng.pw//196708/">PROC SQL In SAS | Data Science Tutorial | Simplilearn</a>
A PROC SQL view is a stored query that is executed when you use the view in a SAS procedure, DATA step, or function. A view contains only the descriptor and other information required to retrieve the data values from other SAS files (SAS data files, DATA step views, or other PROC SQL views) or external files (DBMS data files). When executed, a PROC SQL view's output can be a subset or superset of one or more underlying files. A view contains no data, but describes or defines data that is stored elsewhere.
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The data science with SAS certification training is designed to impart an in-depth knowledge of SAS programming language, SAS tools, and various advanced analytics techniques. The training provides a solid base for implementing these techniques. The course is packed with real-life projects and case studies to give a hands-on and practical experience to the participants.
Mastering SAS and related tools: The course covers PROC SQL, SAS Macros, and various statistical procedures like PROC UNIVARIATE, PROC MEANS, PROC FREQ, and PROC CORP. You will learn how to use SAS for data exploration and data optimization.
Mastering advanced analytics concepts: The course also covers advanced analytics techniques like clustering, decision tree, and regression. The course covers time series, it's modeling, and implementation using SAS.
As a part of the course, you are provided with 4 real-life industry projects on customer segmentation, macro calls, attrition analysis, and retail analysis.
Who should take this course?
There is an increasing demand for skilled data scientists across all industries that makes this course suitable for participants at all levels of experience. We recommend this Data Science training especially for the following professionals:
1. Analytics professionals who want to work with SAS
2. IT professionals looking for a career switch in the fields of analytics
3. Software developers interested in pursuing a career in analytics
4. Graduates looking to build a career in Analytics and Data Science
5. Experienced professionals who would like to harness data science in their fields
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