Introduction of Informatica Cloud Data Integration
Data integration technologies allow operations using different databases and formats to communicate with each other using only one interface each. We at Ides Trainings, provide Informatica Cloud Data Integration training for individuals as well as corporate batches. Informatica Cloud Data Integration Online training is provided by our real-time experts. Ides Trainings is one of the best IT Training delivering Partners , we can gather up profound trainers for all the possible latest technologies. We provide Online, Corporate and Classroom training. We provide Virtual Job Support as well. We provide classroom training at client premises like Hyderabad, Chennai, Bangalore, Delhi, Mumbai, Pune, Noida, etc.
Prerequisites of Informatica Cloud Data Integration training
To learn this course, one should have basic knowledge on
Course Outline of Informatica Cloud Data Integration training
Course Name: Informatica Cloud Data Integration Training
Mode of training: We provide Online, Corporate and Classroom training for Informatica Cloud Data Integration. We provide Virtual Job Support as well.
Duration of Course: 15 Hours (Can be customized as per the requirement)
Do you provide materials: Yes, if you register with Ides Trainings, Informatica Cloud Data Integration materials will be provided.
Course Fee: After registering with Ides Trainings, one of our coordinators will contact you.
Trainer Experience: 17+ years
Timings: According to one’s feasibility
Batch Type: Regular, Weekends and Fast track
Online Mode: WEBEX, GoToMeeting or SKYPE
Backup session: If the student misses the session, then we will provide backup session.
Course Content of Informatica Cloud Data Integration training
Topic 1: Informatica Cloud Overview
Topic 2: Runtime Environments and Connections
Topic 3: Synchronization and Data Transfer Task
Topic 4: Cloud Mapping Designer
Topic 5: Cloud Mapping Designer – Transformations
Topic 6: Mapping Parameters
Topic 7: Expression Macro and Dynamic Linking
Topic 8: Replication Task
Topic 9: Masking Task
Topic 10: Mass Ingestion Task
Topic 11: Taskflows
Topic 12: Hierarchical Connectivity
Topic 13: Intelligent Structure Model
Topic 14: Advanced Task Settings and Performance Tuning
Topic 15: Exception Handling
Topic 16: Administration
Topic 17: Automating and Monitoring Tasks
Topic 18: IICS APIs
By using a Informatica Data Integration Framework, the enterprise should derive maximum value from its investment. This has the capability to execute different styles of integration seamlessly, so that multiple products don’t need to be bought for different uses. This flexibility accelerates ROI, while ensuring scalability, flexibility and reuse.
What is Data Integration?
Data integration is the method, technique and technology that deals with the extraction, restructuring, movement and loading of data to logical data stores or repositories in order for it to be used by logical/reporting operations and systems. A framework of operations, products, techniques and technologies for providing a unified and harmonious view of enterprise-wide business data.
Goal of Data Integration
Provide consistent access to data available in multiple, independent, heterogeneous and distributed data sources
Uniform (same query interface to all sources)
Access to (queries; ultimately updates too)
Multiple (Involves multiple sources)
Autonomous (Independent result)
Heterogeneous (data models are different)
Distributed (over LAN, WAN, Internet)
Data Sources (not only databases)
Different Styles of Data Integration
Eight styles of Data Integration:
Traditional Data Warehouse: Periodically refreshed from production data sources.
Data is gathered from multiple sources to create an collected repository of information. Data can be extracted from production sources as it is generated (real-time information), or in periodic stages (latent information), making it simpler and more effective than accessing each system independently.
Real-time Data Warehouse: Constantly updated by trickle-feeding data from production data sources.
Trickle feeding the data warehouse – meaning new records are added right away. As soon as new data is entered into any one of the functional systems, it is extracted, transformed and loaded into a real-time repository. The data warehouse is updated simultaneously with functional systems, one record at a time.
Operational Data Access: A real-time view of business activity from operational data and applications.
Operational BI applications generally get their information from an automated workflow process or directly from production systems. There is low latency between when an event occurs and when the BI system is apprehensive of that event, putting business users in touch with the timelier information. Reports are generated directly from the functional system (or occasionally an exact copy of the functional system).
Data Virtualization: Provides real-time aggregation of corporate data across multiple sources.
Data virtualization refers to the real-time collection of corporate data across multiple data sources. It presents distributed data as if it exists in a single position. This distinguishes it from other types of data access technologies, since data is not permanently moved or replicated into new position or database. The source data remains intact. Data virtualization combines data from several sources, which can include functional systems and data warehouse.
Process Integration: Delivers real-time information based on a business event or as a part of a business process.
It enables operations to listen for possibility, identify them, generate them and discover which actions to take according to conditions that have been discovered in advance. Setting up triggers and alerts enables a process to interface with transaction systems and be triggered by possible occurring in those systems. There are three basic categories of process integration:
In all three cases, the operation acquires data before it ever gets loaded into a database.
Data is obtained as the business possibility occurs and is delivered even before it enters a database. Delivery targets can be any device (computer, phone or mobile device) or even another part of a process.
Search Technology: Rapidly scan index content, creating Google-style results from the data sources throughout the enterprise.
Search technology allows users to find data across disparate operations and databases, even when they don’t know what they are looking for. An enriched version of each transaction is transferred to a search engine in HTML format, in concert with the functional system. Subsequent searches link transactions to reports that will further reveal necessary information. This unleashes information that was preliminarily locked up in personal information systems. No data warehouse needed.
Data Access via Web Services: Expose or extract data from multiple sources, irrespective of underlying operating systems, applications or databases.
One of the most effective way to access data is via a web service and native APIs. Developers create web services to extract a subset of information from an internal database or operation, enabling multiple departments to access their own slices of the data. For example, the marketing department might need to tap into certain parts of a sales or finance system. A web service can reveal just the material data. Report results are attained by combining data from one or more data sources and web services. The web services are treated as relational tables.
Native APIs Cloud Data: Optimize the way cloud-based information is accessed and leveraged.
Data integration within the cloud comes in numerous forms. Two of the common synopsis include:
Leveraging cloud sources: Online databases for postal addresses, people, products or even the weather. Can also come in the form of online operations, such as Salesforce.com, which store functional data for an organization.
Storing data in the cloud: Some cloud providers offer the capability to host data offsite. When integrating with the cloud, multiple data integration patterns may be used. When used within a proper framework, cloud sources appear no differently than any other on-premise database or operation. This flexibility allows the use of different integration patterns which leverage cloud, on-premise or both similarly.
No matter which integration pattern is used or where the data is stored, the enterprise should derive maximum value from its investment by using a Data Integration Framework. The key here is the capability to execute different styles of integration seamlessly, so that multiple products don’t need to be bought for different uses. This flexibility accelerates ROI, while ensuring scalability, flexibility and reuse. Ides Trainings provides Job Oriented Hands-on experience for Informatica Cloud Data Integration training. We provide training across the globe by Informatica Cloud Data Integration professionals. We provide training for all Informatica modules like Admin, Big Data, Master Data, PowerCenter, Power Exchange, etc. For more information contact to the details provided. Register with us today to get the best Informatica Cloud Data Integration training.
Frequently Asked Questions (FAQs)
1. What skills will you learn in this Informatica Cloud Data Integration Training?
By taking Informatica Cloud Data Integration Training, you will learn:
Everything regarding Informatica and gain the overview of it
About Informatica architecture and data integration features
Cloud mapping designer
And many more
2. Who should take up this Informatica Cloud Data Integration Training?
Informatica Cloud Data Integration training can be taken up by operators, developers and individuals who wish to create a career in the field of enterprise business intelligence.
3. Which jobs can one get by learning Informatica Cloud Data Integration Training?
These are the following jobs which one can get by taking Informatica Cloud Data Integration Training:
4. Can a student attend the Demo session?
Yes, the student can attend the demo session before taking up the training.
5. What is the salary of Informatica Cloud Data Integration Professional?
The average salary of Informatica Cloud Data Integration professional is $112K.