Mainframe 5 Modules - TSO/ISPF, JCL , VSAM, SDSF, Z/OS-UNIX

Explore how to connect to the mainframe using emulators, establish an internet connection and login ID, and preview the mainframe modules such as TSO/ISPF, JCL, VSAM, SDSF, and Z/OS UNIX.

Connect to the mainframe via an emulator and internet, log in with your mainframe ID, and use TSO/ISPF to access interactive panels, menus, and commands.

Explore JCL, the job control language, and how it orchestrates batch COBOL programs from compile to execution, and manages input data and datasets.

Discover COBOL, a common business oriented language, used to build banking, insurance, and other applications; learn its structured, English-like syntax and mainframe usage for reporting and data processing.

Learn how VSAM, a mainframe storage access method, functions as a COBOL data store, using aliases and VSAM files to create, access, and delete data via batch and online processes.

This lecture explains DB2 on the mainframe as IBM's rdbms, contrasts it with sequential files, and shows COBOL online access to data in DB2 and files.

Discover how CICS, an online system for customer information control, delivers instant results through SCADA-like screens and transactions, with COBOL maps and ATM-style interactions.

Discover mainframe tools for core basics, including version control, debugging aids, and file handling, and see how COBOL programs are managed in production with change tracking.

Explore mainframe applications by contrasting batch processes, a single-task sequential data flow for reports and file copies, with online processes delivering multitask, instant results, such as ATMs and statement printing.

Explore mainframe program types, distinguishing batch and online programs, and show how COBOL can access data from VSAM files using DeVita queries and related facilities.

Install a mainframe emulator on your computer, obtain a mainframe ID from a vendor, enter the provided IP address, and connect to the mainframe for hands-on practice.

Learn to connect and log in to a mainframe using your emulator, entering the ip address, user id, and password, and manage disconnects and reconnects.

Explore the mainframe home screen and the ISP primary option, navigate with function keys, access settings, and learn how to view, edit data, and use utilities for EPF parameters.

Explore how the mainframe uses data sets instead of files, including sequential data sets, flat files, partitioned data sets with members, generation data groups, and VSAM files.

Explore mainframe dataset formats like fixed block and variable block files, and learn naming conventions, qualifiers, and how to allocate and catalog datasets.

Discover how to insert data into a mainframe dataset, edit and save records, and use i for insert and r for repeat with line commands, including blank lines.

Explore how function keys like F7, F8, F11, and F3 help navigate large data sets in a mainframe editor, move between records, adjust columns, and jump to top or bottom.

Master three copy options in datasets—copy one line, copy multiple lines, or copy a group of lines—then paste after or before specific records using C, A, and B commands.

Master the move line command in the mainframe editor to relocate single or multiple records after or before a target position, using M, A, and B options.

Learn how to delete a single record, a set of records, or a group of records in a dataset using ISPF edit, including counting records and the B command.

Rename a dataset in ISPF/TSO by using the forward slash to select actions, switch between edit and view modes, and save changes when renaming type 1 to type 2.

Demonstrates how to use scroll values in a dataset, including page and half window modes, cursor-based positioning, and adjusting the screen window to view specific records in a mainframe dataset.

Learn how to navigate wider datasets in mainframe ISPF by using locate to jump to a specific record, adjust column view, and move to a target line for debugging.

Explore line commands from the dataset list to copy and move datasets, view dataset information, and manage properties across type one and type three datasets.

Create a partitioned data set (PDS) to store members in a library, configure directory blocks and member limits, and optimize memory use for faster retrieval in mainframe environments.

Create a PDS member with the ISPF editor, ensuring an eight-byte name that starts with a letter, then save and verify; rename or delete as needed.

Learn to copy data from one physical sequential dataset to another using mainframe utilities, creating a new dataset when needed, and verifying that the record counts match.

Demonstrate copying a PDS member from one PDS to another using the mainframe interface, showing single-member copy and bulk copy, with destination warnings and verification.

Connect to a Unix environment from the IBM mainframe to run Unix programs and transfer files back and forth, using Unix commands and exploring the / directory.

Navigate the unix file system by listing with ls and ls -l, using cd and pwd, creating directories and files, and setting permissions with chmod 777 input1.

connect to unix from the isp shell, open the mainframe ispf screen with oedit, navigate directories, and create, edit, compile, and run simple c, cobol, or c++ programs.

Demonstrates copying data from Unix to the mainframe by navigating directories, selecting a file, and using an ISPF screen (press F6) to allocate and transfer the data.

Open a copied file on the mainframe, switch between mainframe and Unix environments, view the file structure, and edit the copied file to confirm successful transfer.

Master the process of copying a mainframe text file to Unix by connecting to Unix, selecting the mainframe dataset, executing the copy, and verifying the successful transfer.

Open the copied file on Unix to verify the same mainframe input is now available in the Unix environment, and browse the data to confirm copying from mainframe.

Sort data across Unix and mainframe pipelines by using ISPF mode commands to sort by columns, ascending or descending, and selectively delete, copy, or cut records.

Learn the basics of job control language (JCL), including statements, parameters, and utilities, and see how to automate batch jobs, manage datasets, and execute programs.

Learn how to run third-party and ibm-provided programs on the mainframe using jcl, and perform batch processing to transfer large data between datasets, test cobol programs, and generate printed reports.

Learn how to prepare jcl by defining job level, exec level, and dataset statements, creating a job card and dcl for dataset creation, and specifying keyword and positional parameters.

Identify JCL by its three sections—the job, the exec, and the data steps—and by recognizing the job name, accounting info, comments with star, and end marker //.

Explore positional parameters at the job and exec levels, including mandatory accounting information, and learn how to pass a date or true or false value to programs.

Explore keyword parameters at the job level, including message class, message level, priority, notify, and typewrite, and see how exec level and other parameters guide job execution.

Use the class parameter to categorize mainframe jobs by environment and cpu time, with classes such as A to Z or 029. Consult system programmers for the appropriate class.

Discover how the MSGCLASS keyword parameter routes diagnostic messages to a specific destination, such as a spool or printer, and how it helps assess job success or failure.

Explore how the keyword parameter msglevel controls message volume and job status, with default 1,1 and values 0 0, 0 1, 1 1 indicating normal or abnormal termination.

Explore the keyword parameter PRTY to prioritize mainframe jobs, understand priority ranges from 0 to 14, and apply high priority during production support to accelerate critical jobs.

Explore the notify keyword parameter to send job status notifications to a specific user or your own id, indicating completion and exit codes zero, four, or eight.

Learn how the keyword parameter typrun scans your DCL to identify syntax and semantic errors, validating the job card before submission to the mainframe.

Explore keyword parameters in this practical session, focusing on class and message level to control log routing, job monitoring, and error details, with hands-on submission and viewing of job logs.

Learn how to write JCL comments to document job cards, steps, and actions—using star comments to describe dataset creation and COBOL program execution for clarity.

Master exec statements in mainframe jobs by using DCL to execute data copy steps, run user defined and COBOL programs, and manage datasets with IBM utilities.

Explore the dd statement, its use for activity, data processing, or data definition, and learn keyword parameters like dcb and record format, plus system and user defined names.

Explore the DSN statement, detailing keyword and positional parameters, including filename criteria (up to 44 characters, starts with a letter) and eight-byte qualifiers, with DCB and unit notes.

Understand the dd statement with space attributes, specifying auxiliary storage space in tracks, blocks, bytes, or cylinders, and distinguishing between primary and secondary memory.

Discover how release frees unused storage when creating data sets and how the dcb specifies dataset organization, including block size, record format, and primary or secondary allocation.

Explore the dd statement with disp, detailing status options for creating new datasets or using older ones, and how normal and abnormal dispositions govern cataloging, pass, and deletion.

Discover how to create a temporary dataset for a utility, grasp its scope limited to the batch job, and use ampersand to name and manage the temporary file.

Explore using the IBM utility IEFBR14 to create and delete a dataset via batch job, detailing cataloging, memory, block size, and record format, and how to review job logs.

Learn how to use the IEBGENER utility to copy data from an input dataset to an output dataset, creating backups and ensuring matching properties for real-time data transfer.

IEBCOPY copies members from one PDS to another using input and output PDS, a defined job, and program IEBCOPY, with online and batch options and include or exclude controls.

Use iebcopy with include to copy only specific PDS members from one place to another. Pass parameters to the program, use copy and select member, and verify the submitted job.

Explore how iebcopy uses the exclude option alongside select member scenarios to copy all members from one dataset to another while excluding specified members and handling existing members.

Demonstrate using the IBM utility Colbie and IEBCOPY to compress to reclaim space, manage PDS members, monitor utilization, and extend available memory.

This lecture demonstrates IEBCOPY Compress - 2, showing an alternate way to compress a copy, handle society dataset names, submit the job, and verify compression across members.

Use the IP compare utility to compare two PDS members, such as development and model environments, and interpret results for equality, extra records, or data differences.

Learn how to compare dubious files with IEBCOMPR two PS files, using batch or online utilities to detect added, deleted, or changed records and view detailed comparison results.

Learn how to concatenate two or more datasets using the IBM data set utility, creating a single merged dataset that preserves properties like fixed block and record length.

Explore generation data group (gdg) as a collection of sequential datasets with the same attributes, enabling versioned backups and efficient data access via base and generation steps.

Create the gdg base, add datasets to it, and define generations using the decamps utility. Enforce a five-generation limit with scratch or no scratch and uncatalogued old generations when reached.

Create a GDG generation and copy the daily payment file to a new generation, exploring scratch vs no-scratch behavior and weekly data retention in Z/OS datasets.

Learn to access GDG generations in a mainframe environment by using present (zero) and prior generations (minus one, minus two), and copy the latest data to a target dataset.

Delete a GDG base and its generations using the Ideograms utility, applying force deletes to remove the base and all generations, and explore the purge option.

practice jcl through hands-on tasks: create datasets with 133 and 80 byte record lengths, copy between files, and use IBM utilities to access and delete datasets.

Learn how to bypass specific JCL steps using conditional parameters, restart parameters, and other bypass techniques, interpreting return codes to control job flow.

Learn to use if statements as a bypass technique to conditionally execute steps based on a condition, such as step zero one returning zero, and bypass others when not met.

Explore conditional parameters in JCL that decide step execution at the job or activity level using a written code and a relational operator, including can equal to only.

Explore conditional parameters in JCL, using written code with relational operators and activity level checks to control step execution, bypass, and file operations.

Explain how, in JCL, the conditional parameter cannot be used at the job level, and how using 0 0 runs only the first step and bypasses the rest.

Learn how to use the restart parameter in JCL to restart a job from a specified step, bypassing completed steps and avoiding errors from existing files.

Learn how to use restart to bypass steps and jump to a specific step, and apply precautions for if conditions and temporary datasets to ensure correct step execution.

Learn how to use sort cards in jcl to sort and copy mainframe data, apply filters and conditions, and place records in specific output locations.

Sort data in ascending or descending order by specifying the start position, length, and data type, and apply the sort to fields like names or zip codes.

Learn to use copy and stop after to copy only a subset of records, skip initial records, and control processing steps to speed handling of large data volumes.

Discover how to skip duplicate records using a mainframe sort, copying only unique data, applying conditions, and using the xsum option to move duplicates to a separate file.

Sort and skip the duplicate records, then copy them to another file or dataset, using an exemption or alternative utility to handle version-based behavior.

Discover how to use inrec and outrec in sort to copy specific fields from input to output, before or after sorting, by specifying start positions and lengths with practical examples.

Explore the sort include condition to copy only records that meet byte-position and length criteria, such as name Abel or Ohio state records, and practice applying these filters.

Learn to control costs by turning repeated code into reusable control cards and PBS members for cross-job reuse. Align datasets with development, production, and release environments.

Learn about procs, reusable components that group statements and steps for reuse across activities. Compare instream procs and catalog procs and their use across environments.

Explore catalog proc fundamentals, using stream procs to define steps that create datasets and override symbolic parameters, and learn how to call procs and manage dataset names.

Learn how to create and call a catalog proc within DCL, reuse code across jobs, and manage symbolic parameters to generate input and output datasets for multiple environments.

Learn how to use the sort card type 1 with copy to duplicate data from input to output, manage datasets via catalog delete and recreate, and verify the copied results.

Learn to sort mainframe data with sort card type 2, choosing ascending or descending order by specific fields, such as account numbers or balances, including multi-field sorts.

Learn to use the skip records option in sort to copy the remaining records while ignoring the first n records, enabling efficient selective data processing.

Sort the data by a specified field, skip records, and copy only five records from a 21-record set, illustrating type 4 skip and stop after.

Apply sort card type 5 to remove duplicate records from the input file, using fields equal to one and none, and write a deduplicated output file.

Learn how to remove duplicates with sort card type 6, and copy the duplicates to a separate dataset using a control card, with practical notes on environment limitations.

Use sort card type 7 conditions to copy records from input to output when the name field starts at column 7 with 5 bytes and equals Weegee or goomar.

Apply sort card type 8 to omit records based on conditions, such as excluding records with the name Vijay. Learn to use omit conditions to filter records in real time.

Demonstrate using sort card type 9 inrec formatting to extract specific fields from an input file, mapping fields by position and length to a targeted output dataset.

Compare type 10 formatting using outrec, formatting data before sorting versus reformatting after sorting, and note performance gains when using Indrek for large datasets.

Explore sort type 11 to split an input file into multiple output files by conditions like names or salary, and prefer a simple shortcut over full Cobol coding.

Explore SDSF, the system display and search facility, and learn how it shows job status from submission to completion, using the spool, input and output queues, and staging area.

Learn to connect to SDSF by logging into the mainframe, using SDSF or DSF commands, and access the SDSF primary options to view active users, input/output, and job status.

Submit a mainframe job with JCL, monitor progress in SDSF, review input and output queues, job status, and system messages to diagnose and fix issues like duplicate dataset names.

Explore more options on SDSF to manage mainframe jobs, view active users, monitor jobs in the input and output queues, and understand job priority, submission, and completion.

Understand how to read a mainframe job’s overall status and per-step return codes using the maximum condition code, SDSF views, and how to troubleshoot by inspecting steps and messages.

Learn how to submit a job from the spool using SDF, navigate between spool and library, and review the job creation via the message log.

Learn how to copy spool output to a sequential file using the dc command, capturing job logs for testing and environment verification, and storing results in datasets for future reference.

Learn how to cancel a submitted job in dsf, locate the job, issue the cancel command, and verify cancellation through status messages, then adjust the class and resubmit.

Purge jobs from the spool using dsf commands to delete specific or multiple job logs, especially after repeated submissions, so only fresh jobs remain visible.

Learn to scan JCL for syntax errors with dipen=scan, validate before submission, and use hold and release to control job execution in the queue.

learn how to see z/OS system information, including the operating system version, installed tools, and software, by connecting to the mainframe and using dsf/sdsf commands to view status.

Master SDSF column customization by using the question mark command to select and reorder columns, including max return code, so you can quickly see job status at a glance.

Discover VSAM, a mainframe storage method that stores data in clusters for secure, large-volume master data with random, key-based access and faster retrieval than flat files.

Contrast sequential (flat) files with VSAM, noting flat files offer only sequential access and VSAM provides random access by key, created by IDCAMS and stored in catalogs, with secure retrieval.

Explore the vsam file types: ksds, esds, and rrds, and how ksds uses an index dataset for retrieval, esds holds data, and rrds uses relative records.

Learn how IDCAMS creates a VSAM file as a cluster, detailing its name, data component, and optional index component, and when to use named versus data-only configurations.

Discover KSDS datasets, where data records with a key are stored in an index for fast random and sequential access, with data and index components, and control area structures.

Create a ksds dataset by defining a cluster with a data component and an index component, specifying cluster name, record size, min and max record lengths, and key size.

Learn to load data into a VSAM file using the repro parameter, with skip and count options, ensure proper key usage, and verify the copy via spool history.

Learn how to display data from a VSAM file using print and review the cluster listing, including index components and map keys, while loading data without duplicates.

Learn how to load data from a VSAM file to a flat file using an unload step, configuring cluster name and record length, and selecting keys to copy.

Learn to view VSAM file properties using list get entries. Inspect owner, creation and expiration dates, record and key lengths, and the control interval for both flat files and clusters.

Use the IDs utility to delete a VSAM file, removing the data component, index component, and cluster, and learn when to delete for migration or temporary work.

IDCAMS ALTER demonstrates renaming VSAM clusters and their components (cluster name, data component, and index component) using submit steps and verification.

Create an esd dataset as an entry sequential file with fixed or variable length records, noting deletions aren’t possible and data can be loaded to a flat file for removal.

Contrast KSDS and ESDS by noting KSDS has an index and data component, enabling key-based access, while ESDS stores data with a single data component and uses relative byte addresses.

Explore creating a RRDS file in VSAM, understanding its fixed eighty‑byte records, the name and data components, how duplicates are restricted, and how REPRO copies records.

Learn about LDS, the linear VSAM dataset with a data component and cluster; understand alias creation and why LDS is rarely used today, holding unstructured four gigabytes of data.

This lecture compares ksds, esds, and rrds, detailing how ksds uses a key value index for random access, while esds and rrds retrieve by record number and cluster components.

Recap VSAM on the virtual storage access method, data storage, sequential or random access, cluster data and index, repro copying between flat files and VSAM, and alter or delete operations.

Learn what an alternate index (AICS) is and how to create it to access data by non-primary keys, using examples like policy numbers and SSN.