Talend Data Quality
Talend Data Quality is malleable and open source data analyst tool, which delivers error free information by eliminating inaccurate data, implementing rules and generating relevant information through standardization. It enables organizations to access the data enclosed in their databases, and enable to choose an action to be taken to eliminate encountered error. It turns the data into trusted sanctioned and smart assets. Business and IT users become more productive by work together to understand, collect, enrich, standardized and control data for any data domain such as financial, customer, or transaction.
|Course Name||Talend Data Quality Online Training|
|Contents||Fundamentals and Concepts of Talend Data Quality|
|Duration||30 Hours with Flexible timings|
|Delivery||Instructor Led-Live Online Training|
|Ideal For||Fresher, Aspiring job seekers in the field of Java programming or Database|
|Next Batch||Please visit the schedule section|
- Integrate to a data source and run data analyses.
- Perform a data analysis using the Schema and Catalog analysis tools.
- Set basic data validation rules.
- Create a data model.
- Configure and manage users.
- Define display properties for the web user interface.
- Use a custom or built-in pattern to test data quality.
- Generate a regular expression to test data quality.
- Examine the contents of a data source connection.
- Manage Tasks in the Talend Studio.
- Define role-based security.
- Navigate Talend Studio for Data Quality in order to access the desired functionality.
PR-EREQUISITES: Basic Knowledge of Databases and SQL Concepts
MODULE 1: GETTING STARTED WITH TALEND
TOPICS: Functioning Of Talend, Overview Of Talend Open Studio, Where To Employ Talend?, What Is Meta Data?
MODULE 2: JOBS
TOPICS: Creating A New Job, Using Meta Data And Its Significance, Concept And Creation Of Delimited File, Creating Jobs Using T-Filter Row And String Filter, What Is Propagation?, Input Delimation File Creation, Data Integration Schema
MODULE 3: OVERVIEW OF SCHEMA AND AGGREGATION
TOPICS: Job Design And Its Features, Data Aggregation, What Is A T Map?, Significance And Working Of Tlog, T Map And Its Properties, Introduction To Triplicate And Its Working
MODULE 4: CONNECTIVITY WITH DATASOURCE
TOPICS: Source And Target In Database, Extracting Data From The Source, Importing Schema Or Metadata, Creating A Connection
MODULE 5: GETTING STARTED WITH ROUTINES/FUNCTIONS
TOPICS: What Are Routines?, Use Of Xml File In Talend, Calling And Using Functions, What Is Type Casting?, Working Of Format Data Functions
MODULE 6: DATA TRANSFORMATION
TOPICS: Defining Context Variable, Define And Implement Sorting, Learning Parameterization In Etl, What Is An Aggregator?, Writing An Example Using Throw Generator, Running Job In A Loop, Using T Flow For Publishing Data
MODULE 7: CONNECTIVITY WITH HADOOP
TOPICS: Define Etl Method, Learn To Start Trish Server, Connectivity Of Etl Tool Connects With Hadoop, Implementation Of Hive, Components Of Etl, An Example Of Partitioning In Hive, Hive Vs. Pig, Data Import Into Hive With An Example, Data Loading Using Demo Customer, Reason Behind No Customer Table Overwriting?, Parallel Data Execution, Etl Tool
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