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  • SAS Training: Data Analytics and Research Lab

    SAS Training & Certification Programme by India’s Most Preferred Institute of Data Analysis and Research. Register for free demo. Online and Offline accessible classes. Drop a mail to info@aclm.in or call us directly at +91-72899 89188 to book a free demo class. Proven record of 90% placements.

    SAS Training Course Duration: 2 Months, Course Fee: 20,000/-

    SAS Training (Statistical Analysis System), the world’s fastest and powerful statistical package for data analysis. It comprises multi engine architecture for better data management and reporting. This training will prepare students for rewarding and very well paying career as SAS analyst, programmer, developer or consultant. SAS Training is distributed under two parts SAS Base & SAS Advance.

    The content of this course is designed, explained and demonstrated with examples by professionals who all have come together for a single purpose; to share their experience and to help you become an expert. ACLM Institute of professional studies, offering SAS (BASE & Advance) training for the professionals from Vaishali, Indirapuram, Kaushambi, Ghaziabad, Sahibabad, Vasundhara including Delhi NCR region.

    SAS Training and its Importance

    SAS TrainingIn this era of big data, it is a known fact that data volumes continue to grow and organizations are dealing with complex business issues with heightened global competition. Recognizing the importance of near real-time advanced analytics for solving complex business problems is crucial due to the speed of change in the market place which demands the need for making business decisions – faster

    SAS Training Benefits by ACLM

    • Act quickly and confidently
    • Expand the use of advanced analytics
    • Gain insights at breakthrough speeds
    • Ask and answer new business questions
    • Take full advantage of a highly scalable

    SAS Training: Topics Covered by ACLM

    INTRODUCTION TO SAS
    • An Overview of the SAS System, SAS Tasks, Output Produced by the System, SAS Tools(SAS Program – Data step and Proc step), A Sample SAS Program, Explore SAS Windowing Environment Navigation
    DATA ACCESS & DATA MANAGEMENT
    • SAS Data Libraries, Rules for Writing SAS Programs / Statements, Datasets & Variable Name, Getting Familiar with SAS Dataset, Data Portion of the SAS Dataset, Attributes of a variable (Numeric / Character), System Options, Dataset Options, Flow of Data Step Processing – Compilation & Execution Phase, Input Buffer, Program Data Vector (PDV), Descriptor Information of a SAS Dataset
    DATA TRANSFORMATIONS
    • SAS Data Values, Length Statement, Creating Multiple output SAS datasets for singe input SAS datasets, Conditionally writing observation to one or more datasets, Output Multiple Observation (Implicit Output), Selecting Variables and observations (DROP or KEEP Statement and DROP= or KEEP= Datasets options), Controlling which Observations are read (OBS= FIRSTOBS = Options), The Data Statement_Null_, The_N_Automatic Variable, Creating Subset of Observations:- Conditional Processing using IF-THEN and ELSE Statement, IF—THEN DO: —-END,ELSE DO:—-END, DO WHILE Statement, DO UNTIL Statement, Iterative DO loop Processing, Where statement OR Where condition (dataset), Deciding whether to use a here statement or Sub setting IF statement, Accumulating Totals for a Group of Data ( BY- Group Processing ( First & Last), Multiple BY Variables, DATASETS Procedure, Reading SAS datasets and Creating Variables, Creating an Accumulating Variables (The RETAIN Statement), The DELETE Statement, The SUM Statement, the RENAME = Data Set option, Combining SAS Datasets, Concatenating SAS Data Sets Using SET statement in DATA Step, Inter Leaving SAS Data Sets, merging SAS Data Sets:= Match-Merge, Using Merge Statement, THE IN = Data Set option, Additional Features of Merging SAS datasets One to Many Merging, Many to Many Merging
    READING RAW DATA FROM EXTERNAL FILE
    • Introduction to Raw data, Factors considered to Examine the Raw data, Reading Unaligned Data (List Input), Reading Data aligned  to Columns (Columns Input), Reading Data that requires Special Instructions (Formatted Input), Controlling the Position of the pointer in Formatted Input:- Absolute – Column Pointer Control, Relative Column Pointer Control, Mixed Style Input (Mixing List, Input, Formatted Input Style in one INPUT Statement, Using Colon (:) modifier to specific an informant in the INPUT Statement, Recognize delimiter in the raw data file (Using DLM = option in INFILE Statement), Missing data at the end of row (Using MISSOVER option in INFILE statement), Reading a raw data file with multiple records er observation (Column pointer controls) :- Using Multiple INPUT statement, Using Line Pointer Control (/), Reading variable from multiple records in any order (#n), Line Hold Specifies in INPUT statement :- the Single Trailing @, The Double Trailing @@ (Multiple Observations per Record), Methods of Control in INFILE Statement:- FLOWOVER, STOPOVER, MISSOVER, TURNOVER, Writing to an external File (FILE & PUT Statement), Reading Excel Spreadsheets (IMPORT Wizard / IMPORT Procedure)
    SAS FUNCTIONS
    • Manipulating Character values ( SUB STRING / RIGHT/ LEFT/ SCAN/ CONCATENATION TRIM / FIND / INDEX / UP CASE / LOW CASE / COMPRESS / LENGTH), Manipulating Numeric Values (ROUND / CEIL / FLOOR / INT / SUM / MEAN / MIN / MAX), Manipulating Numeric Values based on DATES (MDY / TODAY / INTCK / YRDIF), Converting Variable Types :- INPUT (Character-to-Numeric), PUT (Numeric-to-Character), Debugging SAS program (DEBUG Option), SAS VARIABLES Lists, SAS Arrays, Enhancing Report Output :- Defining Titles & Footnotes, Formatting Data value (Date, Character & Numeric values), Creating User-Defined Formats (Proc Contents), Formats & Infomats
    ANALYSIS & PRESENTATION
    • Descriptor portion of the SAS Data Set (Proc Contents), Producing List Reports (Proc.Print) Sequencing and Grouping Observations (Proc Sort), Producing Summary Reports:- PROC FREQ – ( one Way & Two-Way Frequencies, PROC MEANS, PROC REPORT, PROC TABULATE, PROC SUMMARY, PROC PRINTO, PROC APPEND, PROC TRANSPOSE, PROC COPY, PROC COMPARE, PROC DATASETS, Regression Procedure, Analysis-of-Variance Procedures, Univariate / multivariate Procedures, ranking Procedure, Producing bard and Pie Charts, producing Plots, The Output Delivery System (SAS/ODS);- Creating HTML Reports, Creating text Reports, Creating PDF Reports, Creating CSV Files

    SAS Training: SAS MACRO LANGUAGE

    INTRODUCTION TO THE MACRO FACILITY
    • Purpose of the Macro Facility, Generate SAS code using Macros (% Macro & % Mend), Writing Macro-Based Programs, Replacing Text Strings using Macros Variable (% Let)
    MACRO PROGRAMS
    • Defining a Macro ( %Macro & % Mend), macro Compilation, Monitoring Macro Compilation (M COMPILE NOTE OPTION), Calling a Macro (%Macro-Name), Macro Execution, Monitoring Macro Execution (M LOGIC OPTION), Viewing the generates SAS Code in the Log form Macro Program (M PRINT OPTION), Macro Storage, macro Parameters: Macro parameters Lists, Macro with Positional Parameters, Macro with Keyword Parameters, Arithmetic and logical Operations, Conditional Processing:- % IF expression % THEN text; %ELSE: %DO;, Stored Complied Macros, % INCLUDE Statement, Macro Processing: Tokens, Macro Triggers, How to Macro processor works, Macro variable Concepts:- Referencing a Macro Variable, Displaying Macro Variable Valur\e in the SAS log (SYSBOLGEN OPTION), Automatic Macro Variables:- System-Defined Macro Variables (_AUTOMATIC_), User-Defined Macro Variable (_USER_), %LET Statement, Global Macro Variables, Lacal Macro Variables, Deleting User-Defined Macro Variable (%SYMDEL). Macro Functions:- Character Strings, Other SAS Functions :- %SSFUNC, %STR, Combining Macro Variable References with Text, macro Variable Name Delimiter, Quoting, Creating Macro variables in the Data Step (CALL SYMPUT ROUTINE), Obtaining Variable value during Macro Execution (SYMGET FUNCTION), Creating Macro Variables during PROC SQL Execution (INTO Clause), Creating a delimited list of Values.
    SAS SQL PROCESSING
    • Introduction to the SQL Procedure, terminology, Features of PROC SQL, PROC SQL Syntax(SELECT, FROM, WHERE, GROUP BY, HAVING, ORDER BY), VALIDATE Keyword, NOEXEC Option, Added PROC SQL Statements (ALTER, CREATE, DELETE, DESCRIBE, DROP), FEEDBACK OPTION, PROC SQL and DATA Step Comparisons
    QUERIES
    • Retrieving Data from a Table, Identify All Row in a table, Remove Duplicate Rows, Sub Setting using WHERE clause, Sub setting with Calculated Values, Ordering Data, Enhancing Query Output (LABEL, FORMAT), Grouping Data (Group By), Analyzing Groups of Data (COUNT), Updating Data Values (Update Statement), using table Alias, Creating Views, Creating Dropping Indexes, Sub Queries:- Non-Correlated Sub Query, Correlated Sub Query, Combining Tables:- Joins, Inner Joins, Outer Joins, Left Join, Right Join, Full Join, Set Operators:- EXCEPT, INTERSECT, UNION, Choosing between Data Step Merges and SQL Joins
    OVERVIEW OF METHODS FOR COMBINING SAS DATA SETS
    • DEFINITIONS, CONCATENATING, INTERLEAVING, ONE-TO- ONE READING OR ONE-TO-ONE MERGING, MATCH-MERGING, UPDATING, MODIFYING, DEFINITIONS FOR READING, COMBINING, AND MODIFYING SAS DATA SETS, READING A SAS DATA SET, COMBINING SAS DATA SETS, MODIFYING SAS DATA SETS, OVERVIEW OF TOOLS, READING SAS DATA SETS, READING A SINGLE SAS DATA SET, READING FROM MULTIPLE SAS DATA SETS, COMBINING SAS DATA SETS: BASIC CONCEPTS, ONE-TO-ONE,  ONE-TO-MANY AND MANY-TO-ONE, MANY-TO-MANY, ACCESS METHODS: SEQUENTIAL VERSUS DIRECT, SEQUENTIAL ACCESS, DIRECT ACCESS, ONE-TO-ONE READING, DATA STEP PROCESSING DURING A ONE-TO-ONE READING, ONE-TO-ONE MERGING, MATCH-MERGING, UPDATING WITH THE UPDATE AND THE MODIFY STATEMENTS, DEFINITIONS, SYNTAX OF THE UPDATE STATEMENT, SYNTAX OF THE MODIFY STATEMENT, UPDATING WITH NON MATCHED OBSERVATIONS, MISSING VALUES, AND NEW VARIABLES, USING AN INDEX WITH THE MODIFY STATEMENT
    SAS PROCEDURES
    • INTRODUCTION, THE ANATOMY OF A PROC, THE PROC STATEMENT, TITLE AND FOOTNOTE STATEMENTS, BY STATEMENT, LABEL STATEMENT, FORMAT STATEMENT, RUN OR QUIT STATEMENT, DESCRIPTION OF DATA USED IN REPORTS, SAS REPORTING PROCEDURES, PROCS FOR ALL THAT DETAIL, USING PROC PRINT, USING PROC SQL, PROC REPORT, PROCS THAT SUMMARIZE, USING PROC CHART, USING PROC FREQ, USING PROC MEANS, USING PROC UNIVARIATE, INTRODUCTION TO PROC TABULATE, DATA MANIPULATION AND MANAGEMENT PROCEDURE, PROC SORT, PROC DATASETS, PROC FORMAT, PROC CONTENTS, OTHER IMPORTANT PROCS, PROC TRANSPOSE, DEFINITIONS, PROC PRINTTO, COMPARE PROCEDURE, PROC APPEND, HOW TO IMPORT AN EXCEL FILE INTO SAS
    INTRODUCTION TO PROC SQL
    • INTRODUCTION, WHY LEARN PROC SQL?, SELECT STATEMENT, THE SELECT STATEMENT SYNTAX, A SIMPLE PROC SQL, A COMPLEX PROC SQL, LIMITING INFORMATION ON THE SELECT, CREATING NEW VARIABLES, THE CALCULATED OPTION ON THE SELECT, USING LABELS AND FORMATS, THE CASE EXPRESSION ON THE SELECT, ADDITIONAL SELECT STATEMENT CLAUSES, EMERGING, REEMERGING FOR TOTALS, CALCULATING PERCENTAGE, SORTING THE DATA IN PROC SQL, SORT ON NEW COLUMN, SUBSETTING USING THE WHERE, INCORRECT WHERE CLAUSE, WHERE ON COMPUTED COLUMN, SELECTION ON GROUP COLUMN, USE HAVING CLAUSE, CREATING NEW TABLES, JOINING DATASETS USING PROC SQL, INNER JOIN, JOINING THREE OR MORE TABLES, OUTER JOINS, INCLUDING NONMATCHING ROWS WITH THE RIGHT OUTER JOIN, SELECTING ALL ROWS WITH THE FULL OUTER JOIN, CONCATENATING QUERY RESULTS
    AN INTRODUCTION TO SAS MACROS
    • INTRODUCTION, SAS MACRO OVERVIEW, TRADITIONAL SAS PROGRAMMING, THE SAS MACRO LANGUAGE, MACRO LANGUAGE COMPONENTS, MACRO VARIABLES, MACRO STATEMENTS, MACRO PROCESSOR FLOW, AUTOMATIC MACRO VARIABLES, MACRO DEBUGGING OPTIONS, WHAT IS A MACRO?, DEFINING AND USING MACROS, POSITIONAL MACRO PARAMETERS, KEYWORD MACRO PARAMETERS, CONDITIONAL MACRO COMPILATION, THE %DO STATEMENT, SAS DATA STEP INTERFACES
    THE OUTPUT DELIVERY SYSTEM (ODS)
    • INTRODUCTION, CREATING VARIOUS TYPES OF REPORTS LISTING OUTPUT, OTHER DESTINATIONS, HTML, PDF AND POSTSCRIPT, RTF FILES, MICROSOFT EXCEL, ADDING STYLE TO YOUR REPORTS, LOCATE EXISTING STYLES, ODS STYLE= OPTION, CUSTOMIZE YOUR REPORTS, ODS SELECT; AND ODS EXCLUDE, OTHER CUSTOMIZATIONS, ODS , PROCLABEL=, ODS PROCTITLE; AND ODS NOPROCTITLE, ADVANCED TECHNIQUES, ODS DOCUMENT, PROC TEMPLATE
    INTRODUCTION TO DIAGNOSING AND AVOIDING ERRORS
    • INTRODUCTION, UNDERSTANDING HOW THE SAS SUPERVISOR CHECKS A JOB,  UNDERSTANDING HOW SAS PROCESSES ERRORS, DISTINGUISHING TYPES OF ERRORS .SAS RECOGNIZES FOUR KINDS OF ERRORS, SYNTAX ERRORS, EXECUTION-TIME ERRORS, DATA ERRORS, SEMANTIC ERRORS, DIAGNOSING ERRORS, DIAGNOSING SYNTAX ERRORS, DIAGNOSING DATA ERRORS, USING A QUALITY CONTROL CHECKLIST
    ADVANCE TOPICS IN SAS
    • PERFORMING ADVANCED QUERIES USING PROC SQL, INTRODUCING MACRO VARIABLES, CREATING AND USING MACRO PROGRAMS, STORING MACRO PROGRAMS, CREATING SAMPLES AND INDEXES, USING LOOKUP TABLES TO MATCH DATA, MODIFYING SAS DATA SETS AND TRACKING CHANGES, INTRODUCTION TO EFFICIENT SAS PROGRAMMING

    Who Should Attend the SAS Training

    • Business & Data Analyst, Software Professional looking job in Data Analytics, Researchers
    • Entrepreneurs and Data Scientists

    Pre-requisites for SAS Training

    • Basic Knowledge of Computer
    • Basic Knowledge of Excel
    • Should be good on Statistics

    What You Need To Bring

    • Notepad, Laptop, Pen/Pencil

    Key Takeaways

    • Navigate the SAS windowing environment
    • Plan and write SAS programs to solve common data analysis problems
    • Read various types of data into SAS data sets
    • Validate and clean SAS data sets
    • Create SAS variables and subset data, Combine SAS data sets, Create and enhance listing and
    • summary reports, Using various SAS Procs, Creating fancy reports using ODS, Making your code dynamic using macros

    About Trainer

    • Over 17+ years of experience in Data Research and Analysis
    • Delivering the role of Data Sceintist
    • International Training exposure of more than 70 corporate trainings
    • Member of IFCA, AIMA
    • Contributed to several studies on financial and man-power management
    • Certifications of PMP, Six-Sigma, MS Project specialist


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