Bundle Course - ETL Tools (Talend, SAP Data Services, SAS)

Uplatz offers this comprehensive bundle course on ETL Tools consisting of a combo of video courses on all topics that are associated with ETL Tools & Technologies. You will be awarded Course Completion Certificate at the end of the course.

This Bundle – ETL Tools course includes the following courses:

1. Talend
2. SAP Data Services (BODS)
3. SAS

A typical ETL (Extract, Transform, Load) process collects and refines different types of data, then delivers the data to a data warehouse such as Redshift, Azure, or BigQuery. ETL also makes it possible to migrate data between a variety of sources, destinations, and analysis tools. As a result, the ETL process plays a critical role in producing business intelligence and executing broader data management strategies.

Few businesses rely on a single data type or system. Most manage data from a variety of sources and use a number of data analysis tools to produce business intelligence. To make a complex data strategy like this work, the data must be able to travel freely between systems and apps. Before data can be moved to a new destination, it must first be extracted from its source. In this first step of the ETL process, structured and unstructured data is imported and consolidated into a single repository. Raw data can be extracted from a wide range of sources.

1. Talend: Talend is an ETL tool for Data Integration. It provides software solutions for data preparation, data quality, data integration, application integration, data management and big data. Talend has a separate product for all these solutions. Data integration and big data products are widely used.
2. SAP Data Services (BODS): SAP BO Data Services (BODS) is an ETL tool used for data integration, data quality, data profiling and data processing. It allows you to integrate, transform trusted data-to-data warehouse system for analytical reporting.
3. SAS: Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep your customers coming back. SAS provides a Data Management platform consisting of more than twenty tools from the various SAS Data Integration, Data Quality, and Master Data Management products. The Data Management platform's focus is on data integration and includes an "Advanced" offering as well. Companies use the SAS Data Management platform to manage, transform, integrate, cleanse, and secure data from legacy/hadoop systems as well as cloud-based or on-premise data sources.

• Bundle Course - ETL Tools - Course Syllabus - download

Bundle Course – ETL Tools – Course Syllabus

Talend - Course Curriculum

1. Role of Open Source ETL Technologies in Big Data

• Overview on: TOS (Talend Open Studio) for Data Integration
• ETL concepts
• Data warehousing concepts

1. Talend

• Why Talend?
• Features
• Advantages
• Talend Installation/System Requirements
• GUI layout (designer)
• Understanding it's Basic Features
• Comparison with other market leader tools in ETL domain
• Important areas in Talend Architecture: Project
• Workspace
• Job
• Metadata
• Propagation
• Linking components

1. Talend: Read & Write various Types of Source/Target System

• Data Source Connection
• File as Source
• Create meta data
• Database as source
• Create metadata
• Using MySQL database (create tables, Insert, Update Data from Talend)
• Read and write into excel files, into multiple tabs
• View data
• How to capture log and navigate around basic errors
• Role of tLogrow and how it makes developers life easy

1. Talend: How to Transform Your Business: Basic

• Using Advanced components like: tMap, tJoin, tFilter, tSortRow, tAggregateRow, tReplicate, tSplit, Lookup, tRowGenerator

1. Talend: How to Transform Your Business: Advanced 1

• Trigger (types) and Row Types
• Context Variables (parameterization)
• Functions (basic to advanced functions to transform business rules such as string, date, mathematical etc.)
• Accessing job level / component level information within the job

1. Talend: How to Transform Your Business: Advanced 2

• Type Casting (convert data types among source-target platforms)
• Looping components (like tLoop, tFor)
• tFileList
• tRunJob
• How to schedule and run talend DI jobs externally (not in GUI)

1. Working with Hierarchical File Structures

• Read and Write an XML file, configure the schema and XPath expression to parse an XML file
• Read and Write a JSON file, configure the schema and JSONPath expression to parse a JSON file
• Read and write delimited, fixed width files.

1. Context Variables and Global Variables

• Create context/global variables
• Use context/global variables in the configuration of Talend components
• Load context variables from a flow

1. Best practices

• Working with databases and implementing data warehousing concepts
• Working with files (excel, delimited, JSON, XML etc.)

1. Orchestration and Controlling Execution Flow

• Files - Use components to list, archive, and delete files from a directory
• Database – Controlling Commit and Rollback
  
  • COMMIT at end of job/ every x number of rows
  • Rollback on error

1. Shared DB connection across jobs and subjobs

• Use triggers to connect components and subJobs
• Orchestrate several jobs in master jobs.
• Handling Errors
  
  • Kill a Job on a component error
  • Implement a specific Job execution path on a component error
  • Configure the log level in the console

statement of accounts

SAP Data Services (BODS) - Course Syllabus

1) BODS overview

1. Over view of the Data services
2. Data services benefits, associated products, interfaces
3. Data services Architecture on single and distributed environment

2) BODS Designer concepts

1. Creating the repository (Local, Central repository
2. Exploring the menu options in the designer
3. Creating the project, Job flow, Data flow, Work flows etc., defining different types of Data stores (Source and destination data stores)
4. Use data store and system configurations
5. Defining file formats for flat, Excel, XML files

3) Batch Jobs

1. Creating Batch Jobs
2. Work with objects
3. Create a data flow
4. Adding the Query transform to the data flow
5. Use target tables
6. Execute the job

4) Defining Data Integrator Transforms

1. Date Generation Transform
2. Pivot Transform
3. Reverse Pivot Transform
4. XML_Pipeline Transform

5) Defining Data Platform Transforms

1. Query Transform
2. Case Transform
3. Merge Transform
4. Validation Transform
5. Row Generation Transform
6. SQL Transform

6) Defining Data Quality Transform

1. Address Cleanse
2. Geocoder

7) Implementation of SCD

1. SCD Type0
   
   • Query Transform
2. SCD Type1
   
   • Table Comparison Transform
   • Map_Operation Transform
3. SCD Type2
   
   • Table Comparison Transform
   • History Preserving Transform
   • Key Generation Transform

8) Using Functions, Scripts, and Variables

1. Define built-in functions
2. Use functions in expressions
3. Use variables and parameters
4. Create Custom functions
5. Use Data Services scripting language

9) Data Assessment

1. Using the data profiler
2. Using the validation transform

10) Setting up Error Handling

1. Set up recoverable work flows

11) Setting up Exception Handling

1. Try/Catch Techniques

12) IF Conditional

13) While-Loop Implementation

14) Capturing Changes in Data

15) Data Assessment

1. Update data over time
2. Use source-based CDC
3. Use target-based CDC
   
   • SCD Type 2

16) Multi-User Environment(Local Repo Vs Central Repo)

17) SAP Integration

1. Data extraction from ECC system to File, Table and SAP BI
2. Data extraction from ECC Extractors
3. Data Extraction from SAP BW
4. ABAP Workflows

18) SAP HANA and SAP BODS Integration

1. Introduction to SAP HANA
2. Introduction to SAP HANA Studio
3. Create Data Store for SAP HANA
4. Perform the load into SAP HANA
5. Store the data in Column Store
6. Preview the data in SQL console of SAP HANA Studio

19) Information Steward

1. Data Insight
2. Metadata management
3. Metapedia

SAS - COURSE CONTENT

• One development environment, removing the need for redundant tools and partial solutions
• Integrated process/visual job designer provides control over jobs processing
• Decision management flows via SAS Decision Manager
• Superior connectivity and data access regardless of the data source
• Support for extract, transform and load (ETL) and extract, load and transform (ELT) pipelines
• Security and compliance, data governance, and metadata management
• Data federation provides consistent business views across your disparate data sources. Query/access data across multiple systems without moving or having to re-map the source data.
• Migration and synchronization of disparate systems means solutions for dealing with issues with embedded, reusable data quality rules and real-time data services for various data sources, including database structures, enterprise applications, mainframe legacy files, SML, message queues, etc.
• Integrations/connectors for popular message queuing products
• Enhanced administration and monitoring of your various systems, all from within the platform
• SAS Metadata Bridge for Big Data
• Integration of SAS Data Loader for Hadoop

Anyone who wants to make a successful career as ETL developer/designer.

Passion and determination to achieve your goals!

• ETL Designer
• ETL Developer
• DW-ETL Architect
• Data Engineer
• Data Architect
• Talend Developer
• Talend ETL Developer
• Talend Admin
• SAP Data Services Developer
• SAS ETL Developer
• ELT/ETL Engineer
• Datawarehouse Architect/Developer

Currently there are no Q&As for this course. Be the first to ask a question.

Certificate of completion

Digital certificate - Included