Talend Advanced for Big Data, Cloud and Database Integration

Install Talend Open Studio for big data by verifying Java 11, downloading and extracting the zip, starting the app, installing libraries, and creating a simple demo job.

Import the Talend advanced course project by downloading the archive and importing it into Talend Studio. Then explore how sections map to job designs to compare component settings.

Download and extract the talendAdvancedSampleFiles.zip, then configure the global context in Talend Open Studio to point to the downloaded folders and propagate changes to all jobs for a quick start.

Create a database connection in Talend using tDBConnection for multiple databases, test and adjust parameters, then implement a pre-job and post-job workflow to open and close the connection.

Handle database schemas in Talend by retrieving tables, views, and custom queries, map database metadata to Java types, and convert schemas into tDBInput and tLogRow components.

Explore bulk loads in Talend using tDBOutputBulkExec, or the two-step approach with tDBOutputBulk and tDBBulkExec; generate data with RowGenerator and load into the bulkDemo table.

Learn how to build ELT jobs in Talend by loading data into a database and transforming in-database using ELT components, including mapping, self-joins, and generated SQL.

Explore how to build slowly changing dimensions (scd) in Talend using the dbscd component, modeling type 0, type 1, type 2 and salary history with staff_history.

Implement transactional data flows in Talend by wiring master and child tables with commit and rollback, using extend insert and last_insert_id to propagate IDs.

Demonstrates capturing database rejects in Talend by wiring a DB output with a reject link to a log row, disabling extend insert to reveal unique constraint rejects and final results.

Learn to integrate Apache Kafka with Talend using the quickstart, creating a Kafka consumer and producer, configuring zookeeper and brokers, and exchanging messages on the quickstart-events topic.

Explains how to use Apache Cassandra with Talend Open Studio to connect, read from and write to the store keyspace's shopping_cart table, including docker setup and cqlsh validation.

Learn to connect Talend to MongoDB, via a local Docker container, perform write and read operations, and query data using MongoDB syntax.

Learn how Talend integrates with Google BigQuery to generate data, write to BigQuery via Google Storage, and query a subset with a where clause.

Learn how to connect to Amazon S3, upload a local file to a bucket, and list bucket objects with S3List, using static credentials in a Talend job workflow.

Learn to send and read emails in Talend using the tSendMail component, configure Gmail app passwords and SMTP settings, and explore the optional POP and FileInputMail readers.

Learn data type conversions in Talend and Java, including widening and narrowing conversions, precision concerns with doubles and floats, and using BigDecimal plus string formatting.

Learn to convert strings in Talend by leveraging Java's string methods, such as length, toLowercase, trim, and strip, in tJava and tMap workflows.

Learn to handle nulls in Talend using the ternary operator and tMap to avoid NullPointerException, substituting empty strings or not available when data is missing.

Master date and time routines in Talend by using the TalendDate class to parseDate dates, format with SimpleDateFormat, and perform dateAdd, dateDiff, and diff calculations in tMap.

Explore arithmetic operations using Talend's mathematical routine. Learn to add, subtract, multiply, divide, and compare numeric and string inputs in tMap and tJava components.

learn to handle currencies in talend using BigDecimal for precision, convert doubles to BigDecimal, and apply setScale with half-even rounding to two decimals.

Create and use custom routines in Talend by converting system routines to user defined ones, test them in a Java main method, and deploy in a Talend job.

Learn to use the tJava component in Talend to run Java code inside a job, with examples of printing, random numbers, for loops, and if conditions.

Use the tJavaRow component to convert a boolean flag to an int in a data-flow, mapping true to 1 and false to 0 with an if-else or ternary.

Explore how to create per-row formatted output using the tJavaFlex component in Talend, including start, loop, and end code that processes each input row.

Learn to use and access system and Java properties in Talend, including retrieving user names, environment variables, and file separators, to adapt jobs across OSes and environments.

Learn to load an external Java library in Talend using the library load component from a Maven repository or internal source; apply string utils to reverse, capitalize, and handle nulls.

Learn to use external components in Talend by downloading the tOutputPDF from the exchange marketplace, loading it in Studio, and generating a PDF from your data.

Explore parallel executions in Talend by enabling multi-thread and multi-site execution, tuning iterations and parallelism to process 10,000-row batches via hash inputs and outputs.

Explore nested conditions in Talend by using the ternary operator in tMap and an if statement in tJavaRow to categorize names into A-H, I-P, Q-Z with null handling.

read large XML files quickly in Talend using a three step approach: read head and tail, define metadata, then load with the SAX parser into a database.

Convert euros to USD using a rest service in Talend by calling the api layer convert endpoint with current exchange rate, and processing the json response using an api key.

Learn to access the previous row in a Talend data flow by using variables in tMap, storing current values, and exposing prev id and prev name outputs for each row.

Learn to add a file header and footer in Talend, including header lines, a separator, and a meta footer for multiple data sets using a single output file.

Learn how to create and run data tests in Talend to validate transformations. Use input data, per-row assertions, and console output to compare actual and expected results.