Introduction computers data processing

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Data Stage Course Content at Traning at learning hub Magarpatta city /FC Road Pune (+91-93257-93756) www.learninghub.co.in Data Stage Data Stage Course Content at Learning Hub Contents • Introduction about Data Stage • Difference between Server Jobs and Parallel Jobs • Difference between Pipeline Parallelisms • Partition techniques (Round Robin, Random, Hash, Entire, Same, Modules,Range,DB2,Auto) • Configuration File • Difference between SMP/MPD architecture • Data Stage Components (Server components/Client Components) • Package Installer Data Stage Administrator • Creating project, Editing project and Deleting project • Permissions to user • .Apt Config file • Environment variable creation, permission Data stage director • Introduction to Data stage Director • Job status View • View logs • Scheduling • Batches Creation Designer • Introduction about Designer • Repository • Palatte • Types of Links • File Stages • Sequential File • Data set File • Lookup file set • Difference between Sequential file/Dataset/File set • Database stages • Dynamic RDBMS • Oracle Enterprise • ODBC Enterprise • Stored Procedure Processing stages • Change Capture (Caption) • Compare stage • Difference Stage • Aggregate Stage • Transformer Stage • Surrogate Generator Stage • Join Generator Stage • Merge Generator Stage • Lookup Generator Stage • Difference between join/Lookup/Merge • Difference between join/Lookup • Remove Duplicates • Switch • Pivot • Modify • Funnel Debugging stage • Head • Tail • Pea • Row Generator • Column Generator • Sample • Job Parameters Manager • Introduction About Data stage Manager • Importing the Job • Exporting the Job • Importing Table Definition • Importing Flat File Definition • Routines Containers • Difference between Local Container and Shared Container • Local Container • Shared Container Please Contact- Learning Hub, S-12,Destination Centre, 2nd Floor, Above HDFC Bank, Next to Noble Polyclinic, MAGARPATTA CITY, PUNE – 411013, PH: +91- 93257-93756. Skype id : learning.hub01 Email: learninghub01@gmail.com www.learninghub.co.in Data Stage Online Training, Data Stage Class Room Training, Data Stage Training in Magarpatta City, Data Stage Jobs and Placement, Data Stage Remote Support, Data Stage Online Help,Data Stage Videos training, Data Stage training by Learning Hub, Fast track classes in Data Stage, Best Data Stage training institutes in Pune, Best Faculty in Data Stage, Best online Faculty in Data Stage, Professional classroom training in Data Stage, Professional online training in Data Stage,Data Stage Certification, Data Stage training in Dubai, Data StageTraining in Melbourne, Data Stage Training in Dubai, Data Stage Training, Data Stage Training,Data Stage Training, Data StageOnline Training, Data Stage certfication and suppor

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DATA STAGE TRAINING IN CHENNAI FOR MNC PROFESSIONALS Peridot Systems is only Data stage training In Chennai delivering the best training for students and also a carrier oriented training. Peridot Systems is a pioneer name in Training, Development, and provides one stop IT professional trainings. We provide trainings in ERP, Java,.net, SQT, SharePoint, Linux, Ms-BI, Cloud computing and all other latest technologies. Peridot Systems aspires to facilitate the creation of a network of IT Training Institutes worldwide to empower the workforce with job oriented skills. Selected Individuals and companies that share the passion and vision of Peridot Systems. Preferable Timinings Free Software Installation One Year Tech Support Real Time Trainers Data Stage Course Content Data ware housing concepts v About data warehousing v History of data warehousing v Data warehousing architecture v Different Data marts v Advantages of DWH v Properties of DWH v OLTP VS OLAP v DWH Approaches v Data Modeling v Star, Snowflake & Galaxy Schemas v Dimension tables v Fact Tables Data Stage Contents Introduction about Data Stage IBM Information server overview IBM Web sphere Data stage and information Analyzer IBM Web sphere Quality stage Difference between Server Jobs and Parallel Jobs Difference between Pipeline and partitioning Parallelisms Partition techniques (Round Robin, Random, Hash, Entire, Same, Modules, Range, DB2, Auto) Configuration File Difference between SMP, MPP, Cluster architecture Data Stage Components (Server components/Client Components) Package Installer 1.Data Stage Administrator • 2.Data stage director 3.Designer 4.Processing stages For Further Details Please Contact Venue Details: Peridot Systems Kamatchi Krupa Apts, No: 84/8, Ground Floor, Venkatarathinam main street, Venkatarathinam Nagar, LB Road, Adyar, Chennai. Tamil Nadu - .

BASE SAS MODULES Day 1: Introduction to the SAS System Components of Base SAS Software Output Produced by the SAS System Ways to Run SAS Programs Running Programs in the SAS Windowing Environment Introduction to DATA Step Processing The SAS Data Set introduction How the DATA Step Works: A Basic Introduction Supplying Information to Create a SAS Data Set Introduction to Raw Data Examine the Structure of the Raw Data: Factors to Consider Reading Unaligned Data Reading Data That Is Aligned in Columns Reading Data That Requires Special Instructions Reading Unaligned Data with More Flexibility Mixing Styles of Input Day 2: Introduction to Beyond the Basics with Raw Data Using INFILE statement and various options. Testing a Condition before Creating an Observation Creating Multiple Observations from a Single Record Reading Multiple Records to Create a Single Observation Problem Solving: When an Input Record Unexpectedly Does Not have enough values Day 3: Introduction to Starting with SAS Data Sets Understanding the Basics Input SAS Data Set for Examples Reading Selected Observations Reading Selected Variables Creating More Than One Data Set in a Single DATA Step Using the DROP=, KEEP= and WHERE= Data Set Options for Efficiency Introduction to DATA Step Processing Input SAS Data Set for Examples Adding Information to a SAS Data Set Defining Enough Storage Space for Variables Conditionally Deleting an Observation Day 4: Introduction to Working with Numeric Variables About Numeric Variables in SAS Input SAS Data Set for Examples Calculating with Numeric Variables Comparing Numeric Variables Storing Numeric Variables Efficiently Numeric Functions. Day 5: Introduction to Working with Character Variables Input SAS Data Set for Examples Identifying Character Variables and Expressing Character Values Handling Missing Values Creating New Character Values Saving Storage Space by Treating Numbers as Characters Character Functions Day 6: Introduction to Acting on Selected Observations Input SAS Data Set for Examples Selecting Observations Constructing Conditions Comparing Characters Introduction to Creating Subsets of Observations Input SAS Data Set for Examples Selecting Observations for a New SAS Data Set Conditionally Writing Observations to One or More SAS Data Sets Day 7: Introduction to Working with Grouped or Sorted Observations Input SAS Data Set for Examples Working with Grouped Data Working with Sorted Data Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Day 8: Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Introduction to Working with Dates Understanding How SAS Handles Dates Input File and SAS Data Set for Examples Entering Dates Displaying Dates Using Dates in Calculations Using SAS Date Functions Comparing Durations and SAS Date Values Day 9: Introduction to Combining SAS Data Sets Definition of Concatenating Definition of Interleaving Definition of Merging Definition of Updating Definition of Modifying 237 Comparing Modifying, Merging, and Updating Data Sets Day 10: Introduction to Concatenating SAS Data Sets Concatenating Data Sets with the SET Statement Concatenating Data Sets Using the APPEND Procedure Choosing between the SET Statement and the APPEND Procedure. Introduction to Interleaving SAS Data Sets Understanding BY-Group Processing Concepts Interleaving Data Sets Day 11: Introduction to Merging SAS Data Sets Understanding the MERGE Statement One-to-One Merging Match-Merging Choosing between One-to-One Merging and Match-Merging Introduction to Updating SAS Data Sets Understanding the UPDATE Statement Understanding How to Sel

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SAP Warehouse Management Course Content Introduction to Warehouse Management • Organization Data • Master Data • Transactions • Reports Organization Data Define Warehouse Structure • Warehouse Number • Storage Type • Storage Section • Storage Unit Master Data • Material Master • Storage Bin Transfer Requirement • Create Transfer Requirement Automatically • Create Transfer Requirement Manually • Create Transfer Requirement for Storage Type • Create Transfer Requirement for Material Posting change notice • Create Posting change notice Transfer Order • Number Range for TO • Create TO w.r.t Transfer Requirement • Create TO w.r.t Posting Change Notice No • Create TO w.r.t Storage Unit Number • Create TO w.r.t Material Document • Create TO w.r.t Inbound/Out Bound Delivery • Confirm the Transfer Order • Cancel the Transfer Order Put away Strategies • Next to Empty Bin • Addition to Existing Bin • Bulk Storage • Fixed Bin Strategy • Storage Unit Type Picking Strategies • Shelf Life Expired • FIFO • LIFO • Stringent Picking Business Scenario’s • Goods Receipt Processing with Inbound Delivery • Goods Receipt Processing with out Inbound Delivery • Goods Issue with out Bound Delivery • Goods Issue for Internal Consumption • Stock Transfer from Warehouse Store to Non-Warehouse Store • Stock Transfer from Warehouse to Warehouse Store • Stock Transfer from Non Warehouse-to-Warehouse Store • Stock Transfer from Bin to Bin • Stock Transfer from Stock Type to Stock Type • Multiple Picking Process for TR's/Outbound Deliveries • Two Step Picking and Wave Picks Storage unit management • Define Storage Types with Storage Unit Management • Put away and Picking Strategies with Storage Unit Management • Create Transfer Order with Storage Unit Number Physical Inventory • Create Physical Inventory Record • Enter Count Results • Clear the Difference in WM • Clear the Difference in IM Warehouse movement types • Define Reference Movement Types for WM • Assign Reference Movement Types to WM Movement Types • Define WM Movement Types Search Strategies • Storage Type Search Strategies • Storage Section Search Strategies • Storage Bin Type Search Strategies RFID Overview All Training reference Materials would be provided as a part of the course. SAP ECC 6.0 EHP 5 Server will also be configured as part of this training.(Hands on)

WARM WELCOME FROM VELGRO TECHNOLOGIES!!! We are providing training for DATA WAREHOUSE Training is provided by well experienced (REAL TIME) Faculty!!! Fee structure Course fees: RS./- Data Warehouse The Compelling Need for Data Warehousing • Escalating Need for Strategic Information • Failures of Past Decision-Support Systems • Operational Versus Decision-Support Systems • Datawarehousing—The Only Viable Solution • Datawarehouse Defined • The Datawarehousing Movement • Evolution of Business Intelligence Data Warehouse: The Building Blocks • Review formal definitions of a data warehouse • Discuss the defining features • Distinguish between data warehouses and data marts • Study each component or building block that makes up a data warehouse • Introduce metadata and highlight its significance Trends in Data Warehousing • Data Warehouse Do-Overs • Proliferation of Data Sources • Outsourcing • Hub Versus Relational Databases • Active Data Warehouses • Fusion with CRM • Growing Number of End Users • More Complex Queries • Integrated Customer View • Exploding Data Volumes Planning and Project Management • Phases in project management • Inception • Elaboration • Construction • Transition Defining the Business Requirements • To gain agreement with stakeholders • To provide a foundation to communicate to a technology service provider what the solution needs to do to satisfy the customer’s and business’ needs • To provide input into the next phase for this project • To describe what not how the customer/business needs will be met by the solution Requirements as the driving force for data warehousing • Understand why business requirements are the driving force • Discuss how requirements drive every development phase • Specifically learn how requirements influence data design • Review the impact of requirements on architecture • Note the special considerations for ETL and metadata • Examine how requirements shape information delivery The Architectural Components • Overall Architecture • Data Warehouse Database • Sourcing, Acquisition, Cleanup and Transformation Tools • Meta data • Data Marts • Data Warehouse Administration and Management Infrastructure as the Foundation for Data Warehousing • Understand the distinction between architecture and infrastructure • Find out how the data warehouse infrastructure supports its architecture • Gain an insight into the components of the physical infrastructure • Review hardware and operating systems for the data warehouse • Study parallel processing options as applicable to the data warehouse • Discuss the server options in detail • Learn how to select the DBMS • Review the types of tools needed for the data warehouse • Study the concept and use of data warehouse appliances The Significant Role of Metadata • Find out why metadata is so important • Understand who needs metadata and what types they need • Review metadata types by the three functional areas • Discuss business metadata and technical metadata in detail • Examine all the requirements metadata must satisfy • Understand the challenges for metadata management • Study options for providing metadata Principles of Dimensional Modelling • Clearly understand how the requirements definition determines data design • Introduce dimensional modelling and contrast it with entity-relationship modelling • Review the basics of the STAR schema • Find out what is inside the fact table and inside the dimension tables • Determine the advantages of the STAR schema for data warehouses Dimensional Modelling: Advanced Topics • Discuss and get a good grasp of slowly changing dimensions • Understand large dimensions and how to deal with them • Examine the snowflake schema in detail • Learn about aggregate tables and determine when to use them • Completely survey families of STARS and their application Data Extraction, Transformation, and Loading • Part I: When to build your data warehouse • Part II: Building a new schema • Part III: Location of your data warehouse The Physical Design Process in DWH • Distinguish between physical design and logical design as applicable to the data warehouse • Study the steps in the physical design process in detail • Understand physical design considerations and know the implications • Grasp the role of storage considerations in physical design • Examine indexing techniques for the data warehouse environment • Review and summarize all performance enhancement options • Matching Information to the Classes of Users OLAP in the Data Warehouse • OLAP (Online Analytical Processing) • Overview & Introduction • OLAP Cube • HISTORY of OLAP • OLAP Operations • DATAWAREHOUSE • ARCHITECHTURE Difference between OLAP & • OLTP & TYPES OF OLAP APPLICATIONS OF OLAP • Data Warehousing and the Web • Data Warehouse Deployment • Data Quality: A Key to Success • Data Mining Basics • Growth and Maintenance contact person: SUJITHA Venue Address: #st floor,Gandhi Road, Velachery Email Id:velgrotechnologies at gmail dot com info at velgrotechnologies dot com Website:www dot velgrotechnologies dot com

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Syllabus- Course Objective Summary During this course, you will learn: Introduction to Big Data and Hadoop Hadoop ecosystem - Concepts Hadoop Map - reduce concepts and features Developing the map - reduce Applications Pig concepts Hive concepts Oozie workflow concepts HBASE Concepts Real Life Use Cases Introduction to Big Data and Hadoop What is Big Data? What are the challenges for processing big data? What technologies support big data? What is Hadoop? Why Hadoop? History of Hadoop Use Cases of Hadoop Hadoop eco Syst em HDFS Map Reduce Statistics Understanding the Cluster Typical workflow Writing files to HDFS Reading files from HDFS Rack Awareness 5 daemons Let's talk Map Reduce Before Map reduce Map Reduce Overview Word Count Problem Word Count Flow and Solution Map Reduce Flow Algorithms for simple & Complex problems Developing the Map Reduce Application Data Types File Formats Explain the Driver, Mapper and Reducer code Configuring development environment - Eclipse Writing Unit Test Running locally Running on Cluster Hands on exercises How Map - Reduce Works Anatomy of Map Reduce Job run Job Submission Job Initialization Task Assignment Job Completion Job Scheduling Job Failures Shuffle and sort Oozie Workflows Hands on Exercises Map Reduce Types and Formats Map Reduce Types Input Formats - Input splits & records, text input, binary input, multiple inputs & database input Output Formats - text Output, binary output, multiple outputs, lazy output and database output Hands on Exercises Map Reduce Features Counters Sorting Joins - Map Side and Reduce Side Side Data Distribution MapReduce Combiner MapReduce Partitioner MapReduce Distributed Cache Hands Exercises Hive and PIG Fundamentals When to Use PIG and HIVE Concepts Hands on Exercises HBASE CAP Theorem  Introducti on to NOSQL Hbase Architecture and concepts Programming and Hands on Exercises Case Studies Discussions Certification Guidance Fee- INR+100 INR Registration Duration-45 hours(weekdays & weekends) Online training available on request Get trained on latest technology by ZEN industry expert. Technology: Java-SCJP/OCJP/Hibernate/Struts/Sprint etc.NET- VB.Net/C#/ASP.net/ MVC frarmrework etc Big data/Hadoop etc ETL/ data Stage/SQL Oracle// DBA/App / forms & reports etc C,C++ PHP/HTML5/javascript/JQuery/AJAX/AngularJS etc For other course like software testing, java, PHP, web technologies, Mobile application using Android/iOS and phone GAP please visit our office or contact us on given number Zeuristech Enterprise Networks Pvt. Ltd.,-ZEN 2nd Floor, Saikar Complex,Beside Ginger Hotel Bhumkar Chowk -pune- Land Mark- ICICI/AXIS Bank ATM Building

Introduction to Computer •Objectives •What is Computer? •Components of Computer System •Concept of Hardware and Software •Introduction •Representation of Data/Information •Concept of Data Processing •Application of IECT Introduction to GUI based Operating System •Introduction •Objectives •Basic of Operating System •The User Interface •Operating System Simple Setting •File and Directory Management •Types of File Elements of Word Processing •Introduction •Objectives •Word Processing Basics •Opening and Closing Documents •Text creation and Manipulation •Formatting the Text •Table Manipulation Spread sheet •Introduction •Objectives •Elements of Electronic Spreadsheet •Manipulation Of cells •Function and Charts Computer Communication and Internet •Introduction •Objectives •Basic of Computer Network •Internet •Services on Internet •Preparing Computer for Internet Access WWW and Web Browser •Introduction •Objectives •Web Browsing Software •Configuring Web Browser •Search Engines Communication and Collaboration •Introduction •Objectives •Basic of E-mail •Using E-mails •Advance E-mail Features •Instant Messaging and Collaboration Making Small Presentations •Introduction •Objectives •Basics •Creation Of Presentation •Preparation Of Slide •Providing Aesthetics •Presentation of Slides •Slide show For more details contact us on /.

BASE SAS MODULES Day 1: Introduction to the SAS System Components of Base SAS Software Output Produced by the SAS System Ways to Run SAS Programs Running Programs in the SAS Windowing Environment Introduction to DATA Step Processing The SAS Data Set introduction How the DATA Step Works: A Basic Introduction Supplying Information to Create a SAS Data Set Introduction to Raw Data Examine the Structure of the Raw Data: Factors to Consider Reading Unaligned Data Reading Data That Is Aligned in Columns Reading Data That Requires Special Instructions Reading Unaligned Data with More Flexibility Mixing Styles of Input Day 2: Introduction to Beyond the Basics with Raw Data Using INFILE statement and various options. Testing a Condition before Creating an Observation Creating Multiple Observations from a Single Record Reading Multiple Records to Create a Single Observation Problem Solving: When an Input Record Unexpectedly Does Not have enough values Day 3: Introduction to Starting with SAS Data Sets Understanding the Basics Input SAS Data Set for Examples Reading Selected Observations Reading Selected Variables Creating More Than One Data Set in a Single DATA Step Using the DROP=, KEEP= and WHERE= Data Set Options for Efficiency Introduction to DATA Step Processing Input SAS Data Set for Examples Adding Information to a SAS Data Set Defining Enough Storage Space for Variables Conditionally Deleting an Observation Day 4: Introduction to Working with Numeric Variables About Numeric Variables in SAS Input SAS Data Set for Examples Calculating with Numeric Variables Comparing Numeric Variables Storing Numeric Variables Efficiently Numeric Functions. Day 5: Introduction to Working with Character Variables Input SAS Data Set for Examples Identifying Character Variables and Expressing Character Values Handling Missing Values Creating New Character Values Saving Storage Space by Treating Numbers as Characters Character Functions Day 6: Introduction to Acting on Selected Observations Input SAS Data Set for Examples Selecting Observations Constructing Conditions Comparing Characters Introduction to Creating Subsets of Observations Input SAS Data Set for Examples Selecting Observations for a New SAS Data Set Conditionally Writing Observations to One or More SAS Data Sets Day 7: Introduction to Working with Grouped or Sorted Observations Input SAS Data Set for Examples Working with Grouped Data Working with Sorted Data Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Day 8: Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Introduction to Working with Dates Understanding How SAS Handles Dates Input File and SAS Data Set for Examples Entering Dates Displaying Dates Using Dates in Calculations Using SAS Date Functions Comparing Durations and SAS Date Values Day 9: Introduction to Combining SAS Data Sets Definition of Concatenating Definition of Interleaving Definition of Merging Definition of Updating Definition of Modifying 237 Comparing Modifying, Merging, and Updating Data Sets Day 10: Introduction to Concatenating SAS Data Sets Concatenating Data Sets with the SET Statement Concatenating Data Sets Using the APPEND Procedure Choosing between the SET Statement and the APPEND Procedure. Introduction to Interleaving SAS Data Sets Understanding BY-Group Processing Concepts Interleaving Data Sets Day 11: Introduction to Merging SAS Data Sets Understanding the MERGE Statement One-to-One Merging Match-Merging Choosing between One-to-One Merging and Match-Merging Introduction to Updating SAS Data Sets Understanding the UPDATE Statement Understanding How to Select BY Variables Updating a Data Set Updating with Incremental Values Understanding the Differences between Updating and Merging Handling Missing Values Day 12: Input SAS Data Set for Examples Modifying a SAS Data Set: The Simplest Case Modifying a Master Data Set with Observations from a Transaction Data Set Understanding How Duplicate BY Variables Affect File Update Handling Missing Values Introduction to Conditional Processing from Multiple SAS Data Sets Input SAS Data Sets for Examples Determining Which Data Set Contributed the Observation Combining Selected Observations from Multiple Data Sets Performing a Calculation Based on the Last Observation Day 13: Introduction to Analysing Your SAS Session with the SAS Log Understanding the SAS Log Locating the SAS Log Understanding the Log Structure Writing to the SAS Log Suppressing Information to the SAS Log Changing the Log’s Appearance Introduction to Directing SAS Output and the SAS Log Input File and SAS Data Set for Examples Routing the Output and the SAS Log with PROC PRINTTO Storing the Output and the SAS Log in the SAS Windowing Environment Redefining the Default Destination in a Batch or Non interactive Environment Introduction to Diagnosing and Avoiding Errors Understanding How the SAS Supervisor Checks a Job Understanding How SAS Processes Errors Distinguishing Types of Errors Diagnosing Errors Using a Quality Control Checklist Day 14: Introduction to Creating Detail and Summary Reports with the REPORT Procedure Understanding How to Construct a Report Input File and SAS Data Set for Examples Creating Simple Reports Creating More Sophisticated Reports Day 15: Introduction to Proc means Deriving descriptive statistics Introduction to Proc univariate and various options Day 16: Introduction to Proc freq Calculating counts using Freq Outputting the counts into a dataset Proc Transpose introduction Using VAR, ID and BY statement efficiently in transpose Reshaping the data with required variables Day 17: Introduction to Producing Charts to Summarize Variables Understanding the Charting Tools Input File and SAS Data Set for Examples Charting Frequencies with the CHART Procedure Customizing Frequency Charts Creating High-Resolution Histograms Day 18: Introduction to Writing Lines to the SAS Log or to an Output File Understanding the PUT Statement Writing Output without Creating a Data Set Writing Simple Text Introduction to the Basics of Understanding and Customizing SAS Output Understanding Output Input SAS Data Set for Examples Locating Procedure Output Making Output Informative Controlling Output Appearance Controlling the Appearance of Pages Representing Missing Values Day 19: Introduction to Customizing SAS Output by Using the Output Delivery System Input Data Set for Examples Understanding ODS Output Formats and Destinations Selecting an Output Format Creating Formatted Output Day 20: Proc Format introduction Creating format catalogue Converting catalogue to dataset Storing formats permanently and finding out formats in a library Accessing a Permanent SAS Data Set with User-Defined Formats ADVANCED SAS MODULES Day 21: Getting Started with the Macro Facility Replacing Text Strings Using Macro Variables Generating SAS Code Using Macros More Advanced Macro Techniques Other Features of the Macro Language Introduction to SAS Programs and Macro Processing How SAS Processes Statements without Macro Activity How SAS Processes Statements with Macro Activity Introduction to Macro Variables Macro Variables Defined by SAS Macro Variables Defined by Users Using Macro Variables Displaying Macro Variable Values Referencing Macro Variables Indirectly Manipulating Macro Variable Values with Macro Functions Introduction to Macro Processing Defining and Calling Macros How the Macro Processor Compiles a Macro Definition How the Macro Processor Executes a Compiled Macro Summary of Macro Processing Day 22: Introduction to the Scopes of Macro Variables Global Macro Variables Local Macro Variables Writing the Contents of Symbol Tables to the SAS Log How Macro Variables Are Assigned and Resolved Introduction to Macro Expressions Defining Arithmetic and Logical Expressions How the Macro Processor Evaluates Arithmetic Expressions Day 23: Introduction to Macro Quoting Deciding When to Use a Macro Quoting Function and Which Function to Use Using Various Macro Functions %STR and %NRSTR Functions etc Using the %BQUOTE and %NRBQUOTE Functions Referring to Already Quoted Variables Deciding How Much Text to Mask with a Macro Quoting Function Using %SUPERQ Summary of Macro Quoting Functions and the Characters They Mask Unquoting Text How Macro Quoting Works Other Functions That Perform Macro Quoting Day 24: Introduction to Storing and Reusing Macros Saving Macros in an Auto call Library Saving Macros Using the Stored Compiled Macro Facility General Macro Debugging Information Troubleshooting Your Macros Debugging Techniques Introduction to Writing Efficient and Portable Macros Keeping Efficiency in Perspective Writing Efficient Macros Writing Portable Macros PROJECT CONTENT COVERED Day Creation of Efficacy tables. Creation of Standard and safety tables. Day 28 Creation of listings Day Creation of Graphs a)Bar Charts b)Scatter plot c)Line plot d)Box plot Day 31 Creation of Analysis datasets/derived datasets Day 32 Introduction to SDTM CRF Annotation (ONLY BASICS) Introduction to mapping specification (ONLY BASICS) Introduction to SDTM dataset Creation (ONLY BASICS) Validation in Open CDISC (ONLY BASICS) Day 33 Introduction to ADAM Standards (ONLY BASICS) Mock interview and providing assistance for interview preparation Contact: