Talend Data Integration with 13 Assignments (From Azam)

Explore what data schema means in file and data management, define columns and data types, and compare manual schema definition with reading large files using metadata in Talend.

Demonstrates automatic schema retrieval for complex files in Talend Data Integration, using metadata and repository-based schema to auto-detect data types, read the file, and propagate updates through central connections.

Explore how schema enforces consistency by filtering records that match data types and lengths, routing clean data to a pipeline and bad data to a reject path, with logging.

Use the tSchemaComplianceCheck component in Talend data integration to enforce schema rules, detect length violations, and route clean versus rejected records for remediation.

Parse comma-delimited flat files in Talend data integration, auto-deducing schema from centralized metadata, trim spaces, handle quotes, and validate data with length checks and rejection handling.

Parse Microsoft Excel files by selecting sheets via exact names, positions, or regular expressions; specify starting and ending columns, apply a total limit across sheets, and centralize the schema.

Parse a simple json file with a store object containing name, address, and goods such as book and bicycle, using absolute addresses and loops for normalization.

Explains how to parse multi schema files with positional, delimited, and Ximo parsers, identifying schemas and producing separate outputs.

Open a database connection in the pre job, reuse it through the integration, and close in the post job while reading, mapping, and writing with insert, update, or delete actions.

Explore Talend database bulk components for inserts. Use bulk to write data to a file, bulk execute to insert into the database, and bulk output when no transformations are needed.

Perform ELT with SQL templates in Delane, transforming data directly in the database to aggregate fees and filter students, minimizing components while moving data between tables.

Use the Delane utility to retrieve and import table schemas from multiple tables into your database project, then work with the loaded schema in your creation jobs.

Discover how to use Talend's built-in SQL editor to test queries, explore tables, and view database schemas with auto-suggestions, before integrating into components.

Learn to use context and global variables in SQL queries within Talend data integration, including referencing context variables and globalMap.get for parameterized statements.

Execute multiple SQL statements in a single Talend database component by wrapping them in a begin...end block, enabling create, insert, and update statements to run together and streamline design.

Update multiple student records by using a database row component to apply full names to the existing first names, referencing row data and executing an update query to set student_name.

Explore the standard database joins in Talend, including inner, left, and right joins, plus outer join variants, and learn how to tune components to perform these joins.

Perform an inner join between the customer and orders tables using the customer_id key, mapping inputs with the dematte and deep map components to produce a combined, matched output.

Discover how to perform an inner join left table reject in Talend data integration using the Dematte component to extract left table rejections after joining customers and orders.

Perform an inner join with the right table to retrieve rejected records, using customer id to map the left-hand side as the data source to the right lookup.

Apply a left outer join in Talend to include all left-table records, show matching right-side data, and display nulls for non-matches.

Learn to perform a right join in Talend data integration, returning all right-side records and nulls for nonmatches on the left, with hash output components for uniting results.

Learn to map, transform, and join data with the tMap component in Talend Data Integration, using lookups, expression builder, and multiple input/output configurations.

Explore how a parent job controls child integration jobs and transfers data via global and context variables, enabling parallel execution of complex tasks.

Explore a divide-and-conquer approach by transferring data from child jobs to a parent job, using a data dump and bofill components to merge independent results.

View and manage the parent–child job hierarchy in Talend Data Integration by opening the job hierarchy to see the master and child jobs, and grandchildren, helping you handle project complexity.

Learn custom Java code components in Talend data integration, including standalone D component and DRL auto component, with examples of uppercasing names and assigning numbers from 100.

Compare in-memory data storage using Buffett and hash components, showing how to write to and read from memory, manage multiple hash maps, and transfer data via buffers between jobs.

Explore how to manage for and while loops in Talend data integration, using the loop component to control boundaries, sub jobs, and context variables, with practical examples and break conditions.

Learn to use the for each loop component to iterate over a list, access the current value in each iteration, and output results to the console in Talend data integration.

Learn to create an infinite loop inside a finite loop component, with a two-second delay per iteration and a break condition using a context variable or trigger.

Convert a data flow to an iterate flow by using the trade component to process each row individually, store values in a global variable, and feed results to downstream components.

Convert an iterate flow to a data flow with a trade to flow component that reads all files in a directory and outputs absolute file paths.

Learn data normalization by turning a multi-valued sports column into separate rows to reduce redundancy, enable reporting and aggregation, and compare normalization with denormalization.

Learn how denormalization consolidates repeating columns into a single delimiter-separated column to reduce data redundancy and memory usage, illustrated with sports and city data and a merge duplicates option.

Discover how multicasting copies a data flow to multiple targets with the same schema, using a replicate component and a unique component to remove duplicates before writing to a database.

Learn how to remove duplicates in Talend using a unique component that evaluates three attributes (id, name, sport) case-sensitively, and review or log duplicates separate from uniques.

Learn how to combine multiple data flows in Talend data integration into a single unified pipeline by aligning schemas, transforming data types, and merging inputs from multiple files.

Learn how to pivot columns to rows in Talend data integration by using a custom Talend exchange component, converting id, name, gender, and surgery into pivot key–value pairs.

Learn exception handling and error management in Talend data integration using die and locator components. Log warnings, tailor messages, and control job flow with optional email alerts.

Discover Talend Exchange, a community platform where developers share free components, upload their own, and easily integrate them into Talend, offering more than 900 components for global use.

Sign in to Talend Exchange to download a component, extract the zip, place it in the Delane plug ins directory, and restart Delane to use the component in data flows.

Explore executing a custom Talend Exchange component to pivot data by turning columns into rows, using a unique identifier, with schema configuration and pivot key/value outputs.