iPaaS stands for "Integration Platform as a Service" is a platform that helps in building the data integration with the cloud and between the cloud and enterprises, such that it removes the requirement of any physical hardware as the enterprises can access the application through the cloud.
Union transformation is just like the UNION ALL set operation, which is a multi-input group transformation used to merge the data from multiple pipelines into a single pipeline.
Aggregator transformation performs aggregate calculations like sum, average, etc. using a temporary placeholder to store the records of operation performed over the rows. To perform this, aggregator cache memory is used.
Lookup transformation is a passive transformation that is used as a join operation in between the source table and lookup table. It is generally used to look up the source in order to get the relevant data.
ETL stands for Extract Transform Load. It is basically a data integration tool that is used to first extract data from sources, then transform it to make it compatible, and then load it into the destined system.
Informatica Cloud Data Quality enables our organizations to take up a comprehensive approach for managing data quality and helps us to identify the data quality problems and fix them in your business applications.
Set up two industry regulations in a change. Initially, utilize the All Fields policy to embrace all industries. Generate a Fields by Datatypes policy to omit regions through data type and choose Date/Time as the data style to skip.
When Source is configured, create the application with the fundamental resource desk to disperse the areas to downstream transformations. Use Named Fields as the Field Selection Criteria after Input in the below improvement, then comprise all the essential fields in the Incoming Fields portion of the switch. After that, transform the Source contest into a specification. The resource fields are still preserved in the downstream change when the places are not on call in the source makeover after parameterizing the Source.
The data can be passed from one Mapping task to another in Informatica Cloud Data Integration through a Task flow using parameters. The Mapping Task which passes the data should have an In-Out Parameter defined using SetVariable functions. The Mapping Task which receives the data should either have an Input parameter or an In-Out Parameter defined in the mapping to read the data passed from upstream task.
Partitioning is nothing but enabling the parallel processing of the data through separate pipelines. With the Partitioning enabled, you can select the number of partitions for the mapping. The DTM process then creates a reader thread, transformation thread and writer thread for each partition allowing the data to be processed concurrently, thereby reducing the execution time of the task. Partitions can be enabled by configuring the Source transformation in mapping designer.
There are two major partitioning methods supported in Informatica Cloud Data Integration.
1. Key Range Partitioning distributes the data into multiple partitions based on the partitioning key selected and range of the values defined for it. You must select a field as a partitioning key and defined the start and end ranges of the value.
2. Fixed Partitioning can be enabled for sources which are not relational or support key range partitioning. You must select the number of partitions by passing a value.
Sequence generator can be used in two different ways in Informatica cloud. One with Incoming fields disabled and the other with incoming fields not disabled.
The difference between the sequence generator with incoming fields enabled and disabled is, when NEXTVAL field is mapped to multiple transformations,
→ Sequence generator with incoming fields not disabled will generate same sequence of numbers for each downstream transformation.
→ Sequence generator with incoming fields disabled will generate Unique sequence of numbers for each downstream transformation.
IICS provides access to following system variables which can be used as a data filter variables to filter newly inserted or updated records.
$LastRunTime returns the last time when the task ran successfully.
$LastRunDate returns only the last date on which the task ran successfully. The values of $LastRunDate and $Lastruntime get stored in Informatica Cloud repository/server and it is not possible to override the values of these parameters. These parameters store the datetime value in UTC time zone.
The Informatica cloud is a lightweight program that is installed & configured on top of a server. This helps in establishing connectivity between on-premises and the cloud and supports data exchange between these two. The secure agent provides a secure environment to process data locally. The Informatica cloud eliminates the manual interaction by automatically updating and restarting the secure agent software. This helps organizations in focusing on developing applications without worrying about administration.
The secure agent majorly executes the following services on the server:
* Data integration service
* Process integration services
* Executes batch commands or shell scripts in a command flow.
The handling of multiple resource documents sequentially possessing similar structure and properties in applying is Indirect File Loading. Indirect loading in IICS can easily be performed by deciding on the File List under the Source Type building of a source change.
The Preprocessing and postprocessing commands are available in the Schedule tab of tasks to perform additional jobs using SQL commands or Operating system commands. The task runs preprocessing commands before it reads the source. It runs postprocessing commands after it writes to the target. The task fails if If any command in the preprocessing or postprocessing scripts fail.
One of the biggest problems solved by the Informatica cloud is the “data integration” problem. This problem generally occurs when you try to move your data from the legacy architecture to the cloud-based architecture.
Informatica Cloud Data Integration assists in exporting the duties as a zip file. The metadata is saved in the JSON format inside the zip report.
You can also download and install an XML variation of the tasks, imported as workflows in Powercenter. It will not support the immensity export of jobs in XML layout at a time. All at once, you can easily transport numerous activities in JSON in a singular export zip data.
In earlier variations of Informatica Cloud, the Union transformation makes it possible for merely a pair of groups to be specified; hence if three different basis teams need to be mapped to aim, the individual needs to use two Union improvements. The result of the initial pair of groups to Union1. The production of Union1 as well as group3 to Union2.
In the most recent variation, Informatica Cloud is sustaining multiple teams. All the input teams can be taken care of in a singular Union improvement.
Yes. Here is a Powercenter task on call in Informatica Cloud. The user needs to load up the XML report transported from Powercenter in Data Integration and operate the task as a Powercenter duty. You can improve a prevailing PowerCenter task to utilize various PowerCenter XML documents. Still, you can not help make adjustments to an imported XML.
When you post a brand-new PowerCenter XML data to an existing PowerCenter activity, the PowerCenter project erases the aged XML data and updates the PowerCenter job definition based upon new XML file information.
Hierarchical Schema is an element where we can upload a JSON or an XML file that specifies the hierarchy of the output data. Hierarchy Parser transformation transforms the input according to the Hierarchical Schema that is related to the transformation.
In the synchronization task, you should have an objective for data integration. But, a replication task will establish a target for you. The Replication task replicates a complete scheme and all the tables in it, which is impossible in the Synchronization task. A Replication task has an in-built incremental processing method. In the Synchronization task, we have to handle incremental data processing.
The synchronization task allows us to synchronize the data between the source and the target. We can build a synchronization task from the IICS UI by choosing the original and the target without using any transformations like in mappings. We can also utilize expressions for transforming the data based on the business logic or use data filters for filtering the data. Without PowerCenter mapping and transformation, we can build the synchronization tasks like UI guides.
Configure two field rules in a transformation. First, use the All Fields rule to include all the fields coming from upstream transformation. Then, create a Fields by Datatypes rule to exclude fields by data type and select Date/Time as the data type to exclude from incoming fields.
In order to propagate the fields to downstream transformations when source is parameterized, initially create the mapping with actual source table. In the downstream transformation after source, select the Field Selection Criteria as Named Fields and include all the source fields in the Incoming Fields section of the transformation. Then change the source object to a parameter. This way the source fields are still retained in the downstream transformation even when the fields are not available in source transformation after the source is parameterized.
The various status states available in IICS are
Starting: Indicates that the task is starting.
Queued: There is a predefined number set which controls how many tasks can run together in your IICS org. If the value is set to two and if two jobs are already running, the third task you trigger enters into Queued state.
Running: The job enters the Running status from Queued status once the task is triggered completely.
Success: The task completed successfully without any issues.
Warning: The task completed with some rejects.
Failed: The task failed due to some issue.
Stopped: The parent job has stopped running, so the subtask cannot start. Applies to subtasks of replication task instances.
Aborted: The job was aborted. Applies to file ingestion task instances.
Suspended: The job is paused. Applies to taskflow instances.
You can add parameters to mappings to create flexible mapping templates that developers can use to create multiple mapping configuration tasks. IICS supports two types of parameters.
Input Parameter: Similar to a parameter in Powercenter. You can define an input parameter in a mapping and set the value of the parameter when you configure a mapping task. The parameter value remains constant as the value defined in mapping task or a Parameter file through out the session run.
In-Out Parameter: Similar to a variable in Powercenter. Unlike input parameters, an In-Out parameter can change each time a task runs. When you define an In-Out parameter, you can set a default value in the mapping. However, you would typically change the value of In-Out Parameter at run time using an Expression transformation using SETVARIABLE functions. The mapping saves the latest value of the parameter after the successful completion of the task. So, when the task runs again, the mapping task compares the In-Out parameter to the saved value instead of default value.
The ability to process multiple source files of same structure and properties through a single source transformation in a mapping is called Indirect File Loading. In order to perform Indirect loading in IICS, prepare a flat file which holds the information of all source filenames which share same file structure and properties. Pass this file as source file and select the File List under Source Type property of a source transformation in a mapping. The data from all the files listed in the source file will be processed in a single run.
A Hierarchical Schema is a component where user can upload an XML or JSON sample file that define the hierarchy of output data. The Hierarchy Parser transformation converts input based on the Hierarchical schema that is associated with the transformation.
Source and Target Metadata: Each Origin and user’s metadata, containing field names, datatype, accuracy, range, and other attributes.
Connection Information: In an encoded file, the connection information to connect specified Source and target systems.
Mappings: All of the data integration tasks that have been constructed and their constraints and rules have been saved.
Schedules: The schedules you generate when you execute the designed IICS job are saved.
Logging and Monitoring Information: The outcomes of all of the jobs are saved.
JSON files are read using the Hierarchy Parser transformation present in IICS. The user needs to define a Hierarchical Schema that defines the expected hierarchy of the JSON file. The Hierarchical Schema can then be imported into Hierarchy Parser transformation while reading the data from input JSON files which converts the input based on the schema that is associated with the transformation. The Hierarchy Parser Transformation can also be used to read XML files in Informatica Cloud Data Integration
Informatica Cloud Data Integration supports exporting the tasks as a zip file where the metadata gets stored in the JSON format inside the zip file. However you can also download a XML version of the tasks also which can be imported as workflows in Powercenter. But it will not support bulk export of tasks in XML format at a time. Where as you can export multiple tasks in form of JSON in a single export zip file.
Informatica Cloud Data Integration allows you to create a new target files/tables at runtime. To use this feature in mappings, choose Create New at Runtime option in target and specify the name for the new target.
The user can choose a static filename where the target file will be replaced by a new file every time the mapping runs. The user can also choose to create a Dynamic filename so that the every time the mapping runs, target file is created with a new name.
In earlier versions of Informatica Cloud, the Union transformation allows only two groups to be defined in it. Hence if three different source groups needs to be mapped to target, the user must use two Union transformations. The output of first two groups to Union1. The output of Union1 and group3 to Union2.
In the latest version, Informatica Cloud is supporting multiple groups. So all the input groups can be handled in a single Union transformation.
There is no Update strategy transformation available in Information Cloud. In the target transformation in a mapping, Informatica Cloud Data Integration provides the option for the action to be performed on the target – Insert, Update, Upsert, Delete and Data Driven.
Yes. There is a Powercenter task available in Informatica Cloud where in user have to upload the XML file exported from Powercenter in Data Intergation and run the job as a Powercenter task. You can update an existing PowerCenter task to use a different PowerCenter XML file but cannot make changes to an imported XML. When you upload a new PowerCenter XML file to an existing PowerCenter task, the PowerCenter task deletes the old XML file and updates the PowerCenter task definition based on new XML file content.
A Linear taskflow is a simplified version of the Data Integration taskflow. A linear taskflow groups multiple Data Integration tasks and runs them serially in the specified order. If a task defined in Linear taskflow gets failed, you need to restart the entire taskflow. However, a taskflow allows you to run the tasks in parallel, provides advanced decision making capabilities and allows you to either restart from failed task or skip it when a task fails.
A Taskflow is analogous to a workflow in Informatica Powercenter. A taskflow controls the execution sequence of a mapping configuration task or a synchronization task based on the output of the previous task. To create a taskflow, you must first create the tasks and then add them to a taskflow.
The taskflow allows you to
→ Run the tasks sequentially
→ Run the tasks in parallel
→ Make decisions based on outcome from one task before triggering the next task.
A Mapping Configuration Task or Mapping Task is analogous to a session in Informatica Powercenter. When you create a Mapping Task, you must select a mapping to use in the task. Mapping task allows you to process data based on the data flow logic defined in a mapping.
Optionally, you can define the following in the Mapping Task
→ You can define parameters that associate with the mapping.
→ Define pre and post-processing commands.
→ Add advance session properties to boost the performance.
→ Configure the task to run on schedule.
Informatica Cloud Services includes the IICS repository that stores various information about tasks. As you create, schedule, and run tasks, all the metadata information is written to IICS repository.
The various information that gets stored to IICS repository include:
Source and Target Metadata: Metadata information of each source and target including the field names, datatype, precision ,scale and other properties.
Connection Information: The connection information to connect specific source and target systems in an encrypted format.
Mappings: All the Data integration tasks built, their dependences and rules are stored.
Schedules: The schedules created you run the task built in IICS are stored.
Logging and Monitoring information: The results of all the jobs are stored.
All the metadata gets stored in the Informatica Cloud repository. Unlike Powercenter, all the information in Informatica Cloud is stored on the server maintained by the Informatica and the user does not have access to the repository database. Hence, it is not possible to use any SQL query on metadata tables to retrieve the information like in Informatica Powercenter.
One of the major differences between a Synchronization task and a Replication task is that, in a synchronization task, you can transform the data before loading it to the target. However, in a Replication task, you can replicate the data from source to target without transforming the data.
A Replication task can replicate an entire schema and all the tables in it at a time which is not possible in Synchronization task.
A Replication task comes with a built-in incremental processing mechanism. In Synchronization task user needs to handle the incremental data processing.
A Replication task allows you to replicate data from a database table or an on-premise application to a desired target. You can choose to replicate all the source rows or the rows that changes since the last runtime of the task using built in Incremental processing mechanism of Replication Task.
You can choose from three different type of operations when you replicate data to a target.
→ Incremental load after initial full load
→ Incremental load after initial partial load
→ Full load each run
Synchronization task helps you synchronize data between a source and target. A Synchronization task can be built easily from the IICS UI by selecting the source and target without use of any transformations like in mappings. You can also use expressions to transform the data according to your business logic or use data filters to filter data before writing it to targets and use lookup data from other objects and fetch a value. Anyone without Powercenter mapping and transformation knowledge can easily build synchronization tasks as UI guides you step by step.
A Runtime environment is the execution platform that runs a data integration or application integration tasks. You must have at least one runtime environment setup to run tasks in your organization. Basically it is the sever upon which your data gets staged while processing. You can choose either to process via the Informatica servers or your local servers which stays behind your firewall. Informatica supports following runtime environments- Informatica Cloud Hosted Agent, Serverless runtime environment and Informatica Cloud Secure Agent.
Informatica Intelligent Cloud Services is a cloud based Integration platform(iPaaS). IICS helps you integrate, synchronize all data and applications residing on your on-premise and cloud environments. It provides similar functionality as Powercenter in a better way and can be accessed via the internet. Hence in IICS, there is no need to install any client applications on the Personal computer or server. All the supported applications can be accessed from the browser and the tasks can be developed through browser UI. In Powercenter, the client applications need to be installed on your server.
There is no possibility of including a router or multiple targets for the data synchronization tasks. Only through 2 ways, it is possible to create a task on the cloud using target and router. The first one is by uploading a previously created XML as a task and the second is by the creation of custom tasks using an integration template.
Some of the widely used resources are:
activity log: The job details of the activity log are returned in this variable.
activityMonitor: The job details of the activity monitor are returned.
connection: The details of the Data Integration connection is returned.
job: A task is started or stopped.
schedule: The details of the schedule is returned. It also helps in creating or updating the schedules.
Informatica Cloud REST API gives the capability for accessing information from Informatica Intelligent Cloud Services. Developers can also perform tasks like create, update, delete connections, start and monitor jobs, etc.
The architecture of the Informatica cloud is built to be multitenant and the web interface is given extra care of UI/UX. The nature of architecture is such that if there is the availability of in house Informatica solutions, one can exploit the heavy advantage of hybrid solution implementation. With this architecture developers can focus on more complex integration steps instead of taking the pain of running a job on the cloud, leaving Informatica Cloud to take care of the job running part.
We have all in all 5 areas and they are:
> Mapping Canvas: In this area, we would configure the map. This area is pretty much similar to the PowerCenter Designer.
> Transformation Palette: The mapping we talked about earlier, are listed down in this area. Either by click or by drag and drop, transformation can be added.
> Properties Panel: All the configuration options related to the mapping or transformation is listed here. In PowerCenter, we had different tabs which did the same tasks.
> Toolbar: All the tools related to saving, canceling, validating, arranging, Zooming in or out are available in this area.
> Status Area: Once we have taken care of all the displays or areas above this area helps in notifying us of the status of the tasks listed. There would be a notification if the mapping has >
unsaved changes, and if the changes are saved, this area will notify if there is any invalid mapping or not.
One can use many types transformation to carry out transformation in the data and they are, Expression transformation used for calculations at row level, filter transformation for filtering out data in the flow itself, Joiner transformation to create joins in data and finally the lookup transformation to look at a source, source qualifier, forgetting the relevant data.
Cloud designers can be thought about as a counterpart version of PowerCenter designer. Using Cloud designer, one can easily configure mappings which are theoretically similar to how PowerCenter mappings are configured. In Cloud designers, one can also transform data by using transformation like Expression transformation, Filter transformation, and many such others.
Informatica Cloud is the web version of Informatica PowerCenter and utilizes the capability of PowerCenter to provide a web-based application for all the functionalities. One of the applications provided by Informatica Cloud is the Cloud designer. Not only that Informatica Cloud has the capability to deliver more advanced data integration capability on the cloud. Some extra features we have on the cloud are, Dynamic Field propagation, where logical rules are used for propagating fields instead of always manually propagating them, the next is about parameterized templates, where a developer can utilize parametrized value so that the mappings can be reused in other scenarios as well.
The main intent of using Informatica Cloud is to solve the data integration problem which is very likely to happen in cases when data is moved from legacy architecture to cloud-based architecture. Using Informatica cloud one can also solve the problem of managing fragmented data lying within and outside the firewall.
Informatica Cloud is an on-demand integration and ETL platform offering through a web interface so that developers can access development, administration, and monitoring of the tasks through one place in web interface. It enables developers to build solutions which carry out ETL processes between cloud and on-premise solution.