Analytics Gurukul

Data Analytics

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SAS (Statistical Analysis System)

data

SAS (Statistical Analysis System) Course Modules:

Day 1

  • Overview of SAS System and SAS Tools
  • Different windows in SAS Windows
  • Sample SAS program
  • DATA step and PROC step
  • SAS Data Libraries
  • Rules for writing SAS programs/Statements/Dataset/Variables
  • Attributes of Dataset – Character and Numeric

Day 2

  • Options (OBS FIRSTOBS NOBS)
  • Input Buffer – Program Data Vector
  • Datalines/cards
  • Creating libraries
  • Proc Print
  • _NULL_ dataset

Day 3

  • Length /Delete/Rename /Sum/Retain statements
  • Creating multiple datasets from single input SAS dataset
  • Conditionally writing to diff datasets from a single input dataset -> IF THEN ELSE
  • Vertical sub-setting (IF – WHERE) and Horizontal sub-setting (KEEP – DROP)
  • Proc SORT
  • Functions – SUBSTR – RIGHT – LEFT – SCAN – ROUND – CEIL – FLOOR – INT – SUM

– MEAN – MIN – MAX

Day 4

  • FIRST DOT and LAST DOT concept
  • Proc CONTENTS/DATASETS
  • Functions – CAT – FIND – INDEX – LOWCASE – UPCASE – COMPRESS – LENGTH

Day 5

  • DO LOOP – DO WHILE – DO UNTIL
  • SAS Format/In-formats
  • Functions – MDY – TODAY – INTCK – INTNX – YRDIF – PUT – INPUT

Day 6

  • SAS Arrays
  • Proc Format
  • 1-1 MERGE without By variable
  • Match merging –

o 1-1

  • 1-Many
  • Many-1
  • Few-Many
  • Many-Few

Day 7

  • Proc Import
  • Reading raw data(Text and CSV files)
  • LIST Input – Column Input – Formatted Input
  • Use of @,@@ AND Use of /, +
  • Using multiple Input statement with #
  • Use of : modifier to specify and in-format in the input statement
  • Use of DLM, DSD, Miss-over, Truncover, Stop-over
  • Writing to an external file

Day 8

  • Proc Summary
  • The Output Delivery System – ODS

ADVANCE

Day 9

  • Difference in BASE SAS and PROC SQL
  • SELECT – FROM – WHERE – GROUPBY – HAVING – ORDERBY
  • Table alias
  • Sub-setting using Where and Calculated values
  • Use of LABEL – FORMAT
  • VALIDATE – NOEXEC – ALTER – CREATE – DELETE – DESCRIBE – DROP – FEEDBACK options
  • COUNT Scenario
  • Dictionary views
  • Sub-Queries – Related and Non-Related
  • Joins (Cross – Outer – Inner)
  • Remove duplicate rows
  • Set Operators
  • Similarity and choosing between merges and Joins

Day 10

  • Defining macro and writing SAS Code using Macro – %macro and %mend
  • Replacing text variables using %LET
  • Calling a Macro
  • Macro execution
  • Arithmetic and Logical operators
  • %Include statement
  • Macro Suffix and Prefix
  • %Macro with indirect Parametrization
  • %Macro with direct Parametrization
  • %Macro with Proc SQL
  • %Macro with DO LOOPS
  • %Macro with %LOCAL
  • %Macro with %GLOBAL
  • Indirect referencing
  • Macro functions
  • Macro processing – Triggers – how Macro processor works
  • MLOGIC – MPRINT – SYMBOLGEN
  • Macro debugging – %PUT – _all_ – _user_ – _automatic_ – _local_ – _global_

Day 11

Project

Duration 24 Hours

Master the Art of SAS (Statistical Analysis System)

Effective communication is at the core of leadership

Leading with Vision and Purpose

Our coaching focuses on developing a clear vision and purpose

We are making our students masters in every aspects Whether it is communication skills, Data Visualization or so on.

Effective Data Collection and Statistical Analysis is the core strength of Data Analytics

Data Visualization

Creating visual representations of data to communicate complex findings effectively. Scientists use tools like charts, graphs

Communication Skills:

Effectively communicating findings and insights to non-technical stakeholders, such as business leaders or decision-makers.

Continuous Learning

Staying updated on the latest developments in data science, machine learning, and related fields.

Optimization and Tuning

Fine-tuning machine learning models to improve their performance, often through hyperparameter tuning