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Showing posts with label Master Data Management. Show all posts
Showing posts with label Master Data Management. Show all posts

Wednesday, February 1, 2023

What are the features of Informatica Intelligent Data Management Cloud (IDMC)?

 Are you looking for the details Informatica Intelligent Data Management Cloud (IDMC)? Earlier it is called Informatica Intelligent Cloud Services (IICS). Are you also interested in knowing the features of Informatica Intelligent Data Management Cloud (IDMC) ? If so, you reached at right place. In this article, we will understand the features of Informatica Intelligent Data Management Cloud (IDMC).






Intelligent Data Management Cloud (IDMC) is a cloud-based solution for managing and analyzing data. Some of the features of IDMC include:

  • Data ingestion: Ability to import data from various sources, including databases, cloud storage, and file systems.
  • Data cataloging: IDMC automatically catalogs and classifies data, making it easier to discover, understand and manage.
  • Data governance: IDMC provides robust data governance features, including data privacy and security, data lineage, and data quality.
  • Data analytics: IDMC includes advanced analytics capabilities, such as machine learning, data visualization, and business intelligence.
  • Data collaboration: IDMC enables data collaboration among teams and organizations, providing a centralized location for data discovery, sharing and management.
  • Multi-cloud support: IDMC supports multi-cloud environments, allowing organizations to manage their data across multiple cloud platforms.
  • Scalability: IDMC is designed to scale with your organization's data growth, allowing for seamless data management as data volumes increase.






Multi-cloud support is one of the key features of Intelligent Data Management Cloud (IDMC). Multi-cloud support refers to the ability to manage and analyze data across multiple cloud platforms. With multi-cloud support, organizations can:

  • Centralize data management: IDMC provides a centralized platform for managing and analyzing data from different cloud platforms, making it easier to gain insights and make data-driven decisions.
  • Avoid vendor lock-in: By managing data across multiple cloud platforms, organizations can reduce the risk of vendor lock-in and have greater flexibility in their choice of cloud provider.
  • Optimize costs: IDMC allows organizations to take advantage of the best cost and performance options available from different cloud platforms, helping to optimize their overall cloud costs.
  • Improve data accessibility: IDMC enables data to be accessed and shared across different cloud platforms, improving data accessibility and collaboration among teams.
  • Ensure data security: IDMC provides robust data security features, such as encryption, access controls, and audit trails, to ensure the security of data stored in multiple cloud platforms

Multi-cloud support is becoming increasingly important as more organizations adopt cloud computing and seek to manage and analyze their data across different cloud platforms. IDMC provides a centralized solution for managing data across multiple cloud platforms, making it easier to gain insights and make data-driven decisions.






Learn more about Informatica here




Wednesday, January 4, 2023

What is Integration Template in Informatica IICS and how to use Integration Template in IICS?

 Integration templates are an important feature of Informatica Intelligent Cloud Services (IICS), a cloud-based integration platform that enables organizations to easily and quickly connect, integrate, and manage their data and applications.





 

Integration templates are pre-built integration flows for common scenarios that enable organizations to quickly and easily create and deploy integrations. Some examples of integration templates in IICS include:

  • Integrating with Salesforce
  • Integrating with a database
  • Integrating with a file system
  • Integrating with a messaging system
  • Integrating with a cloud application or service

Using integration templates can save organizations a significant amount of time and resources, as they provide a starting point for building integrations and eliminate the need to create everything from scratch. The templates can also serve as a reference for customizing and building more complex integrations.

 

The integration framework in IICS includes a range of features and capabilities that make it easy to use and customize integration templates. Some of these features include:

 

Drag-and-drop integration design: The integration framework includes a visual design interface that allows users to easily create and customize integrations using drag-and-drop functionality.

 

Wide range of connectors: The integration framework includes a range of connectors for connecting to various data sources and targets, including databases, applications, file systems, and more.

 

Data transformation and cleansing: The integration framework includes powerful data transformation and cleansing capabilities, allowing users to cleanse, enrich, and standardize data to ensure that it meets their quality and consistency standards.

 

Integration testing and debugging: The integration framework includes tools for testing and debugging integrations, helping users to identify and resolve issues more quickly.

 

Deployment and scheduling: The integration framework includes features for deploying and scheduling integrations, allowing users to automate integration processes and ensure that they run smoothly.

 

Overall, the integration framework in IICS is a comprehensive and powerful tool for building and managing integrations. By leveraging the capabilities of the integration framework, organizations can easily and efficiently connect, integrate, and manage their data and applications.

 





 

How to use Integration Template in Informatica IICS?

Using integration templates in IICS is simple and straightforward. Here's a step-by-step guide on how to use integration templates in IICS:

 

Log in to the IICS console and navigate to the Integration Templates tab.

 

Browse through the available templates to find the one that best fits your needs. You can filter the templates by category or search for specific templates using keywords.

 

Once you've found the template that you want to use, click on it to view the details. This will provide you with an overview of the template, including a description of what it does, the connectors it uses, and any prerequisites that need to be met.

 

Click the "Create Integration" button to begin building your integration using the template. This will open the integration design interface, where you can customize and configure the integration as needed.

 

Use the visual design interface to customize the integration as needed. This includes configuring the connectors, setting up data transformations and cleansing, and defining the integration flow.

 

Test and debug the integration to ensure that it is functioning as expected. The integration framework includes tools for testing and debugging integrations, helping you to identify and resolve any issues.

 

Once the integration is functioning as expected, deploy it to the IICS platform. You can choose to deploy the integration immediately or schedule it to run at a specific time in the future.

 

By following these steps, you can easily and quickly use integration templates in IICS to build and deploy integrations. The integration framework in IICS is a powerful and flexible tool that allows you to easily connect, integrate, and manage your data and applications.

                 Learn more about Informatica here 



            

                   

                

What is Informatica Intelligent Cloud Services (IICS) and what are it's capabilities?

Informatica Intelligent Cloud Services (IICS) is a cloud-based integration platform that enables organizations to easily and quickly connect, integrate, and manage their data and applications. It includes a range of features and capabilities that make it an ideal solution for a variety of integration scenarios.





 

One of the main benefits of IICS is its ability to simplify and streamline the integration process. With IICS, organizations can easily connect to a wide range of data sources and targets, including databases, applications, file systems, and more. The platform also includes powerful data transformation and cleansing capabilities, allowing organizations to ensure that their data is accurate, consistent, and of high quality.

 

In addition to these core integration capabilities, IICS also includes a number of other features and components that make it a comprehensive and powerful integration platform. These include:

 

API Management: IICS includes a comprehensive API management platform that enables organizations to design, publish, and manage APIs. This includes the ability to set policies and procedures for API access, as well as to monitor and analyze API usage.

 





Data Quality: IICS includes a range of data quality tools that help organizations ensure that their data is accurate, consistent, and of high quality. This includes the ability to perform data profiling, data cleansing, and data enrichment.

 

Data Governance: IICS includes a data governance framework that allows organizations to manage and control access to their data. This includes the ability to set policies and procedures for data management, as well as to monitor and enforce compliance with those policies.

 

Cloud Integration Hub: The Cloud Integration Hub is a central repository that enables organizations to manage and orchestrate their integration processes. It includes a range of features for managing integration flows, monitoring integration performance, and more.

 

Integration Templates: IICS includes a range of integration templates that enable organizations to quickly and easily create and deploy integrations for common scenarios, such as integrating with Salesforce or integrating with a database.

 

Overall, IICS is a comprehensive and powerful integration platform that offers a range of benefits to organizations. By simplifying and streamlining the integration process, IICS can help organizations save time and resources, improve data quality, and drive better business outcomes.

                 Learn more about Informatica here 



            

                   

                

Why to choose Informatica MDM Cloud over on-premise Informatica MDM?

 Informatica Master Data Management (MDM) is a powerful platform for managing and maintaining accurate and consistent master data across an organization. It includes a range of features and capabilities for data governance, data integration, data quality, and more. While Informatica MDM has traditionally been offered as an on-premises solution, the company now also offers a cloud-based version called Informatica MDM Cloud.





 

One of the main benefits of Informatica MDM Cloud is its cost effectiveness compared to on-premises Informatica MDM. There are a number of factors that contribute to this cost savings:

 

No upfront infrastructure costs: With Informatica MDM Cloud, there is no need to purchase and maintain hardware and infrastructure. This can significantly reduce upfront costs and ongoing maintenance expenses.

 

Pay-as-you-go pricing: Informatica MDM Cloud is offered on a pay-as-you-go basis, which means that organizations only pay for the resources they use. This can help to better align IT costs with business needs and reduce unnecessary spending.

 

Reduced IT staff costs: With Informatica MDM Cloud, there is no need to hire and train additional IT staff to manage the hardware and infrastructure. This can result in significant cost savings in terms of personnel expenses.

 

Automatic updates and maintenance: Informatica MDM Cloud includes automatic updates and maintenance, which means that organizations don't have to worry about manually installing updates or performing maintenance tasks. This can save time and resources, as well as reduce the risk of system downtime.





 

In addition to cost savings, Informatica MDM Cloud also offers a number of other benefits over on-premises Informatica MDM. These include:

 

Flexibility: Informatica MDM Cloud can be easily scaled up or down to meet changing business needs. This makes it ideal for organizations that experience fluctuating data volumes or have seasonal business patterns.

 

Simplified deployment: Informatica MDM Cloud can be quickly and easily deployed, with no need for complex hardware installations or software configurations. This means that organizations can get up and running with the platform faster, enabling them to start realizing the benefits of master data management more quickly.

 

Improved data security: Informatica MDM Cloud is hosted in a secure and reliable cloud environment, which means that organizations don't have to worry about the security and availability of their data.

 

Overall, Informatica MDM Cloud offers a number of advantages over on-premises Informatica MDM, particularly in terms of cost effectiveness and simplicity of deployment. By leveraging the power of the cloud, organizations can easily and affordably manage and maintain their master data, leading to improved decision-making, increased efficiency, and better business outcomes.

                 Learn more about Informatica here 



            

                   

                

Business Benefits of Informatica MDM

Implementing Informatica Master Data Management (MDM) in an organization can provide numerous benefits to the business. Here are a few of the key advantages of using Informatica MDM:



 

Improved data quality: One of the main benefits of Informatica MDM is the ability to improve the quality of the organization's data. By establishing a single source of truth for key data entities, such as customer and product information, the organization can ensure that all departments are using consistent and accurate data. This can lead to better decision-making, increased efficiency, and reduced risk of errors.

 

Enhanced data governance: Informatica MDM includes a robust data governance framework that allows organizations to manage and control access to their data. This includes the ability to set policies and procedures for data management, as well as to monitor and enforce compliance with those policies. By establishing strong data governance, organizations can improve the security and integrity of their data and reduce the risk of data breaches.

 





Increased efficiency: Informatica MDM can help organizations streamline their data management processes, resulting in increased efficiency and productivity. By automating the process of cleansing, enriching, and standardizing data, Informatica MDM can help organizations save time and resources.

 

Better customer experiences: With accurate and consistent customer data, organizations can provide personalized and relevant experiences to their customers. This can lead to increased customer satisfaction and loyalty, as well as improved business outcomes.

 

Greater agility: Informatica MDM enables organizations to quickly and easily adapt to changing business needs. By centralizing data management, organizations can more easily respond to new data requirements and make changes to their data management processes as needed.

 

In conclusion, implementing Informatica MDM can provide numerous benefits to an organization. By improving data quality, enhancing data governance, increasing efficiency, and enabling greater agility, Informatica MDM can help organizations drive better business outcomes.

                 Learn more about Informatica here 



            

                   

                

Saturday, February 5, 2022

What are best Practices for Customer 360 data modeling ?

                        Are you planning to make changes in the existing customer 360 or c360 data model ? or are you thinking to extend the customer 360 data model and looking for guidelines in doing it? If so, then you reached the right place. In this article, we will understand best practices for customer 360 data modeling in Informatica Master Data Management.


A) What is Customer 360? 

                       Informatica provides a pre-designed customer domain Master Data Management (MDM) tool. Using this we can expedite the development process for MDM implementation in our organization. Customer 360 comes with a prebuilt data model which we can either update or extend as needed.

                      Customer 360 MDM also comes with a user interface called customer 360 application and it is based on business entity services.

                      There are multiple aspects we need to consider while updating or extending the customer 360 data model and we are going to discuss this in this article.






B) What are the steps for modifying the existing customer 360 data model in Informatica MDM?

                     We can extend the customer 360 data model by various actions such as 

                               1) Changing the physical schema 

                               2) Adding needed columns to an existing table 

                              3) Adding for updating values for existing columns 

                  Following are the steps we need to perform to extend the data model.

                         Step 1 : Compare existing data model with business requirement and perform gap                                                   analysis 

                         Step 2 : Prepare documentation that will provide a list of tables and columns needed to                                        add

                         Step 3 : Take a backup of an existing schema 

                         Step 4 : Review guidelines and standards for extending the data model 

                         Step 5 : Add tables and columns as needed 






C) What are the Guidelines for extending the customer 360 data model? 

                   We can change the definition of tables or add a new table to the existing customer 360 data model. To perform these kinds of changes consider following guidelines 

                    1. Check if we can use the existing table 

                   2. Do not use a root base object to store organization or person information.

                   3. Do not define table names greater than 24 characters.

                   4. Do not delete existing columns

                   5. Do not delete existing base objects

                   6. Do not modify the data types of existing columns 

                   7. Do not modify the physical name of existing base objects. 

                   8. It is ok to modify the display name of existing base object tables or columns.

                   9. Do not decrease the length of an existing column.

                  10. Prefix the names of the new base object tables to distinguish the table from the existing tables.

                   11. For newly added column in the existing table-use prefix name of the column as x_


D) What are the guidelines for adding a new base object in the customer 360 data model? 

                  We can add root or child base objects, lookup base objects or relationship base objects. For adding new base objects we need to consider the following guidelines.

                 1. Child base object with one-to-many relationships- Add a Party Role foreign key in the table to relate the table to the Party Role table.

                 2. Child base object with many - to -many relationships- Use the relationship base object to relate the table to the Party Role table.

                 3. Use lookup Indicator as TRUE for the lookup table.


               Learn more about Informatica MDM here -

          



Monday, December 6, 2021

What are the phases in BES External call in Informatica MDM ?

                 Are you looking for the details about various phases in BES External calls? Are you also interested in knowing what are categories under which these phases come? If so, then you reached the right place. In this article, we will learn about BES  External calls and their phases.

A) What BES External calls?

                BES External calls are the web service configured in the provisioning tool in order to achieve customization in Entity 360 or Customer 360 application. we need to develop a custom web service and deploy it on the application server. Once it is deployed, we can register the endpoint URL in the provisioning tool in Informatica MDM.





B) Categories of phases of BES External calls? 

                 The phases of BES External calls are categorized as -

                      a) Read calls

                     b) Write calls 

                     c) Merge calls  

               a)  Read calls: This category is used for read and search operations.

              b)  Write calls: This category uses write co for insert, update and delete operations.

              c)  Merge calls: This category uses preview merge co which is designed for merge-operations.

C)  Phases of External calls 

                   Let's understand detailed phases for the above categories 

              i) Read call phases : 

                        The phases for read calls are

                      * Read Co.Before Everything 

                      * Read Co.After Everything 

                      * Read view.Before Everything

                      * Read view.After Everything






             ii) Write call Phases

                      * Write Co.Before Everything

                      * Write Co.Before Validate

                      * Write Co. After Validate

                      * Write Co.After Everything  

                      * Writeview. Before Everything 

                      * Writeview. Before Vadidate

                      * Writeview. After Vadidate

                      * Writeview. After Everything


               iii) Merge call phases

                      * Perview Merge Co. Before Everything

                      * Preview Merge Co.After Everything

                      * Merge Co. Before Everything

                      * Merge Co. After Everything


                 Learn more about Informatica here 



            

                   

                

Tuesday, November 30, 2021

What is Dynamic Data Masking?

                        Are you looking for details about Dynamic Data Masking? Are you also interested in knowing what are the things we need to consider for implementing Dynamic Data Masking also known as DDM? If so, then you reached the right place. In this article, we will explore various aspects of Dynamic Data Masking.

A) What is Dynamic Data Masking (DDM)? 

                       Dynamic Data Masking is a technology using which we can mask production data in real-time. Dynamic Data Masking also called DDM does not change data physically. DDM  just changes the data stream in order to mask the sensitive data when the requestor request such information.





B) What are the Dynamic Data Masking tools?

                       Various vendors provide Dynamic Data Masking functionalities and these are

                 1. Microsoft Azure SQL Database 

                 2. Oracle Enterprise Manager 

                 3. iMask 

                 4. Informatica Dynamic Data Masking

                 5. Imperva Data Masking 

                 6. Infosphere Optim Data Privacy by IBM

                 7. K2 view Data Masking 

                 8. Mentis

C) What are data masking Rules?

                        The rules contain various conditions and actions that rule engines use in order to process the request.

              e.g. 

                     1) Connection rules : It process application connection requests.

                     2) Security rules :  It process SQL statements.

                      Here are important points about rules 

                     a) We can define and create rules in order to process SQL requests that are executed by an application against the database.

                    b) DDM rule uses two techniques i.e connection criteria and masking techniques.

                    c) In order to forward the requests the rule Engine uses connection criteria.

                    d) In order to mask the data the masking technique is used.





D) What are DDM rule components? 

                         The DDM  rule components are as below

                    a) Matcher: It defines the criteria for the rule engine to identify the match.

                   b) Action: It defines action which will be applied by the rule engine to request.

                  c) Processing Action: The rule engine applies specific action to the request after applying the rule.


              Learn more about Dynamic Data Masking here 



 

                



Friday, November 19, 2021

What are the Batch Processes in Informatica MDM?

Are you looking for an article that explains various processes in Informatica Master Data Management (MDM)? If so, then you reached the right place. In this article, we will learn about various processes through which records are loaded to the MDM system. Let's start.


Informatica MDM contains the various processes and those are -


Step 1: The land process transfers data from a source system via ETL jobs to landing tables in the MDM ORS (Operational Reference Store).

Step 2: The stage process (Stage Job) reads the data from the landing table, cleanses the data if applicable, and moves the cleansed data into a staging table via mapping in HUB Console.

Step 3: The load process (Load Job) loads data from the staging table into the corresponding base object in MDM ORS.

Step 4: The tokenize process (Tokenization Job) generates match tokens based on match columns that are used subsequently by the match process to identify candidate base object records for matching.

Step 5: The match process (Match Job) compares two records for points of similarity. If sufficient points of similarity are found to indicate that the two records are probably duplicates of each other, then Informatica MDM Hub flags those records for consolidation.





Step 6: The consolidate process (Merge Job) merges duplicate records into a single record after duplicate records have been identified in the match process.

Step 7: Publish or distribution process is the main outbound flow for Informatica MDM Hub. Hub integrates with external systems or DB Schemas to share the consolidated (Golden) Records.


Learn more about Informatica MDM here,





Friday, October 22, 2021

What are differences between multimerge and merge API in Informatica MDM

                Are you interested in knowing what is the use of multimerge and merge APIs? Are you also would like to know the difference between merge and multimerge API? If so, then you reached the right place. In this article, we will learn about these APIs in detail.


A) What is Multimerge API? 

                 The Multimerge API is used to merge the list of records together. Multimerge is the generic form of merge API.






B) What is Merge API? 

                The merge API is used to merge two base object records that are identified as the same base object record.


C) What are the differences between Multimerge and Merge API? 

          1) Number of records to merge : 

              a) Merge API allows only two records to merge 

              b) Multimerge API allows more than two records to merge.

         2) Parameters to request : 

             a) Merge API accepts sourceRecord key and targetRecord key as parameters in the input

             b) Multimerge API accepts multiple record key lists as parameters in the request.





         3) Consolidated records : 

             a) Merge API allows records irrespective of the value of consolidation indicator 

             b) Multimerge API allows merging of unconsolidated records only i.e. consolidation indicator                   !=1

         4) Final value for consolidation indicator : 

            a) The final value for consolidation indicator after performing merge API operation is 1 i.e                           consolidated state  

            b) Multimerge API does not change consolidation indicator value for surviving records.

        5) Surviving Record : 

             a) The surviving record is specified in merge API with targetRecordkey as the parameter.

             b) For Multimerge API, the surviving record will be determined based on survivorship rules of the XREF that are participating in the merge process.


                 Learn more about Informatica MDM survivorship rules here 



   

Sunday, September 5, 2021

How to design landing table in the Informatica MDM ?

          Are you planning to implement Informatica MDM in your project and starting designing a landing table? Are you also interested in knowing the types of landing table designs? If so, then you have reached the right place. In this article, we will explore factors that need to consider while designing a landing table in Informatica MDM.


A) what is the landing table in Informatica MDM?

             Are landing tables are the tables where data from the source is loaded in order to process the data and sent through a stage process to cleanse and standardize it. For the stage process, the landing tables act as source and stage tables as targets.






B) Factors to be considered for landing table design

               We need to consider the following factors

While designing landing tables in MDM

             1. How many source systems are involved

             2. What is the volume from each source system

             3. Impact of development timelines

             4. Maintenance requirements

             5. Partition requirements


C) Type of landing table designs

             Based on the Information capture in the previous section, we can design landing tables in two ways

             1. One landing table for each source

             2. One landing table for multiple sources





1. One landing table for each source

             If each source is having different types of data ( e.g.one source is customer-centric and another source is Account centric), if the volume in each source is almost equal, or if we have good development and maintenance bandwidth then we can design one landing table for each source.









2. One landing table for multiple sources

             If multiple sources are having similar attributes and data types and volume in each source system is low and if we need to expertise the development time then we can design one landing table for multiple source systems. 



                                 



Learn more about MDM landing table here







Saturday, August 21, 2021

What are the log Files in Informatica MDM ?

        Are you trying to analyze the issue in Informatica MDM? Are you looking for the details of the log files which are generated during various Processes in the Informatica MDM? This article will explore more about the log files, their locations, and when to use those.





A) Introduction

         Informatica MDM has various components such as application server, database, business process management tool, Application user interface such as Entity 360 or customer 360. Each of these components generates logs throughout its processing.

         Here we will understand various types of log files and these are

         1. Hub server logs

         2. Process or cleanse server logs

         3. E360 logs

         4. Provisioning logs

         5. Post Installation logs

         6. Elastic search logs

         7. Application server logs

         8. Database logs

1. Hub server logs

         Informatica MDM has two core components: hub server and process server earlier it was called cleanse server. The hub server is used to initiate the jobs, managing and controlling the threads in short hub server is master component in Informatica. The logs are generated when we access the Administration section of the MDM hub. Especially when we validate the ORS . These logs are captured in Hub server logs.

          Location :- <Informatica MDM install folder>/hub|server|log

        e.g./abc|hub|server|logs|cmxserver.log

2. Process server logs

           When we execute the jobs such as Stage, load, tokenization, match and merge jobs, the logs are captured in the process server logs.

            Location :- <Informatica MDM install folder>/hub|Cleanse/logs

             e.g . /abc/hub|cleanse/logs|cmxcleanse.log

3. E360 logs

              We can configure the user Interface using the provisioning tool. The User Interface is called Entity 360 application. When we access the application the logs are generated.

              Location:- <Informatica MDM install folder>/hub|server|logs 

              e.g. /abc/hub|server|logs|entity360view.log

4. Provisioning logs

             We use provisioning to configure business entities, transformations, views, tasks, and E360 applications. When we use the provisioning tool the logs are generated and stored below location.

             Location :- < Informatica MDM install folder>/hub|server/logs 

             e.g. /abc/hub|server|logs|provisioning.logs





5. Post Install logs

               The post-install logs are generated when we install Informatica MDM as well as when we apply EBF or upgrade.

               Location :- <Informatica MDM install folder>/hub|server|logs

              e.g. /abc/hub|server|logs|postInstallSetup.log

6. Elastic search logs

                If you are using Elastic search in your Informatica MDM then you may need to use Elastic search logs.

                Location:- <Elastic search folder>/logs 

                e.g. /aqr|logs|elastic search.log

7. Application server logs

                Application server logs are located as below

                a) Jboss

                 <Jboss home>/standalone/log/server.log

                  b) Weblogic

                   < Weblogic home >/domains/domain name/servers/server name/log/abc.out

                  c) websphere

                   <websphere home>/Appserver/profiles/profile name/logs/server name/systemout.log

8. Database logs

                  Database logs are not directly accessible. You need to reach out to your DBA to get database logs.


           Learn more about Informatica MDM here







        



Friday, August 20, 2021

What is difference between 'Remove from match list ' and 'Not a match' in IDD ?

             Are you looking for an article on Informatica Data Director which explains what is the difference between 'Remove from match list' and 'Not a match' options which are available in IDD application in Informatica Master Data Management? If so, then you reached the right place. Let's understand these two options here.


A) What is the match process?

                Informatica MDM comes with a process named match process. With help of this process, we can determine potential matching records. In other words, we can remove duplicate records from the system. Informatica Data Director application uses a match engine that comes with MDM in order to achieve it.

                   IDD application uses a match engine at the time of processing manual match records as well as at the time of creating a new record. This requires some specific to be mode using IDD configuration manager.






B) Where in the IDD application we can find the match feature?

                IDD application is used by data stewards or business users to manage the data. In order to manage the data, records need to be first searched and then opened. Once the record is opened we can see data, Xref, timeline, history, and match sections. The match section shows potential matching consolidate to the given record.


C)  Difference between ' Remove from match list ' and ' Not a match' in IDD

                  As discussed in the earlier section, potential matching records are available in the match section. If uses are working on a manual merge queue using this match section the users either can merge the record or can perform one of the below actions on the merge task.

                  1. Remove from match list

                  2. Not a match





                 The remove from match list removes the record from the match view in the IDD application. If the user logins again the record will be shown again on the screen.

              On the other hand, if the user selects the ' Not a match ' action then the matching entry will be deleted from match table. The record will not be shown in the IDD view anymore. This will also delete the merge task.

              Learn more about the merge process here -

 


Thursday, August 5, 2021

What is lifecycle of consolidation_ind ?

    Are you looking for details about consolidation indicator in Informatica MDM? Are you also interested in knowing what are valid values for the consolidation indicator column? If so then you are right place. In this article, we will also explore the lifecycle of consolidation indicator for a record.


A) What is a consolidation indicator?

          The consolidation indicator is a column in the base object table. The consolidation process is also known as the merge process updates the consolidation indicator value for a record based on the record's process.






B) What are valid values for consolidation_ind?

          When we execute load jobs, Match job and merge jobs record goes through various processes because which value of consolidation indicator column goes through the values below

        4 : New record

        3 : Record queued for the match process

        2 : Record has gone through the match process

        1 : Consolidation record  

a) Consolidation_ind = 4

           The actions below cause record to have consolidation_ind = 4

          1. Inserting a new record in the Informatica hub 

          2. Queue a record as the new using data manager 

          3. When we unmerge the record either through API or E360 application

b) Consolidation_ind = 3

          The actions below cause record to have the consolidation_ind=3

           1. When we queue a record for a match using data manager

           2. If match job fails, the records that were picked up for matching but the match did not complete for that record will have value for consolidation indicator as 3

C) Consolidation_ind = 2

         The actions below cause record to have the consolidation_ind =2

         1. When the match process completes for the record

         2. When the record is queued for merge using data manager or any API or application.





d) Consolidation_ind = 1 

          The actions below cause record to have consolidation_ind =1 

         1. For the Golden source system the records will be loaded with consolidation_ind=1

         2. When the record is accepted as unique 

         3. If Accept Record as unique is set to yes and match process does not find matching record.

         4. If Accept Record as unique is set to yes and after merging records, it does not have any more matches.

e) Consolidation_ind =9

         If a business user puts the record on hold.

 

      Learn more about consolidation indicator in Informatica MDM here -



Tuesday, July 20, 2021

Top 10 things you need to know before implementing Informatica MDM?

           Are you planning to implement Informatica Master Data Management aka MDM? Are you not sure what are the things you need to consider before considering MDM solution? If so, then you reached the right place. In this article, we will see the top 10 things which you need to know before implementing Informatica Master Data management in your organization. 

 1.Data Quality Measurement 
            You need to know how you are currently measuring data quality not only in a single project but also across the enterprise. This will give you two benefits one, you will know better options for quality of data measurement, and second, a baseline to measure the quality of data after MDM implementation.





 2.MDM and Data Quality
              Is there a relationship between master Data management and Data Quality? Can MDM help in improving data quality? The answer is Yes. However MDM and Data Quality are two distinct processes in any organization. You need to know what is the relationship between Master Data Management and Data Quality.

 3.Returns of Improved data quality?
               We initiative various projects for improvement in the processes and to achieve better results on Investment. You need to know what is the return you will be getting after improving data quality.

 4.Data Governance 
              Data governance is a crucial part of the business. Are you aware of how is data governance is implemented in your enterprise? You need to have proper data governance to get optimum benefits from MDM implementation.

 5.Data for business strategy 
               It is not new that this Era of data. We are in data 4.0 where the majority of the businesses are data-driven. You need to plan your business strategies based on data that is of great quality and well maintained.





 6.Data enrichment
               Why do you need data enrichment? One may ask this question. The answer is to make better decisions and recommendations we need to take important steps towards data enrichment.

 7.Privacy regulations 
               These rules and regulations we need to follow a business. We need to be fully aware of those rules and regulations and consider those implementing any MDM solutions.

 8.Customer satisfaction 
                Is your customer satisfied with your services? What are your customer's preferences and how are you managing these? How are addressing your customer's concerns and feedback? These are important questions you need to answer so that you improve those with MDM.

 9.Risk measurement and assessment 
                Informatica MDM defiantly plays a vital role in risk assessment and measurement. However, you need to know your current solutions and look for better opportunities to improve those.

 10.Future Perspective
             While implementing Informatica MDM, you need to look for long-term benefits instead of short-term MDM with great benefits for the long run.

Learn more about information MDM here

       

Wednesday, July 7, 2021

How to achieve better stage job performance in Informatica MDM

      Are you working on MDM and want to understand its different fields, then this is the right place in this article we are going to know about what are the product recommendation, thread setting properties, and database recommendations of MDM stage job performance


 A. Thread setting for MDM Stage Job Performance

       In this article, we will see what are the different reasons for issues and their solutions regarding stage job performance.

     1) Post/ Pre Stage UE

          The reason for this issue is it we are going to write the query regarding inserting or updating and record, it will create locks and because of this it slows down the performance to avoid this there is a need to put logger statement in UE  code. If doable rerun the jobs by removing the UE code.





     2) Cleanse Function 

            Each in every record will have to go through a cleansing process so here need to check that if any cleanse function is taking more time to process.

           Depends on which type of cleanse function you are using there is a need to check network latency also we need to check of IDQ  end.

     3) Directory 

            The main reason for the directory issue is having a shared directory within 2 different instances of the process server.

           To avoid file locks each process should have its own directory.

     4) Tables  

            The system will reduce the performance if the tables like RAW, REJ, C_REPOS_JOB_CONTROL table contain a huge amount of data.

           We can keep the important data and archive old data. 

   5) Log level

           We will have to keep the logging level to INFO.


B. Thread setting for MDM Stage Job Performance

          The configuration that can be updated :

       1) Threads for cleanse operation (HUB Console)

          Max value = ( Number of CPU cores -1 )

        2) In cmxcleanse properties

            (cmx.server.cleanse.min_size_for_distribution)

            Default size is 1000





        3) com.informatica.mdm.batchcontroller.Batchjob.min_rec_for_multithreading

            The default size is 1000. We can decrease the size if multithreading is enabled and no. of records are lesser than 1000.


C. DB Recommendations for MDM Stage Job Performance.

        1) collect AWR reports.

        2) For the DB performance, collect TESTIO results


D. Appserver Recommendation for MDM Stage Job Performance

        1) when we run the processing server and DB server jobs, check that the CPU is going high.

        2) Have to check basic java arguments such as - xmx value.

           


 

Monday, July 5, 2021

What is Business Entity Services in Informatica MDM?

    Are you looking for details about the Business Entity Services aka BES in the Informatica MDM? Are you also interested in knowing how to use Business Entity Services in your project? If so, then you reached the right place. In this article, we will explore more about Business Entity Services. Let's start.


A) What are Business Entity Services in MDM?

         Informatica MDM is used to master the data from various source systems. We onboard the data from sources to the MDM landing table. The data is moved to the staging table from the MDM landing table and then to the base object tables by executing stage and load jobs. Once we consolidate the data in the MDM, it will be ready to consume by consuming systems. Consuming can consume a golden copy of the records by consuming ETL or JMS Queue or Business Entity Services. Business Entity Services are web services that can be used for real-time integration of external systems with Informatica MDM.

B) What are operations can be performed using Business Entity Services?

      The various operations such as Read, Write, the search can be performed using Informatica BES.

      1) Read BE Business Entity Service-

          It is used to read the data from the base object. the result does not include soft-deleted records.

      2) Write BE Business Entity Service- 

            It is used to create, update and delete parent and child business entity elements. we cannot perform trust override with this service.

      3) Search BE Business Entity Service-

            It is used to root record in the business entity. We can use match operation while searching records to achieve fuzzy searches.

C) Understanding Business Entity Services Architecture 

        Business Entity Services is an integral part of Informatica MDM and it is available as wed service. The consuming system can write web service consumer and consume BES, for reading and write operation. Once the operation is invoked when the data is searched against the base object or updated against the base object.



D) What are the REST Methods Supported 

      Here is the list of HTTP methods supported in Business Entity Services

           GET - used to retrieve details about record, task, or a file 

           POST - used to create task or record 

           PUT -  used to update root, child records, or a file.

          PATCH - used to update task partially 

          DELETE - used to delete records or file


Learn more about Business Entity Services here -  



Tuesday, June 22, 2021

When Tokenization job gets executed in Informatica MDM?

Are you looking for the details about when the tokenization job executed in Information? Would you be interested in knowing the relationship between a match job and a tokenization job? If so, then you reached the right place. In this article we will explore the instances during which tokenization job gets triggered:

A. Why we need a tokenization process in MDM?
          Tokenization is a process that generates the token-based fuzzy match key and other match column configuration. The tokens generated are stored in the table <BO> STRP. This STRP table is used as input to match the process. The match process matches the records based on these tokens.





B. When the tokenization process executed
           The tokenization process gets triggered at various points and These are:
          1)  Manual tokenization execution
          2)  During the match process
          3)  During the load process

1) Manual tokenization job execution
       We can execute the tokenization job in Informatica MDM manually whenever it is needed. It is recommended that tokenization need to executed separately instead of in conjunction with load or match job.





2)  Tokenization process as part of match job
       If it is required to update the match token, the match process in Informatica automatically starts the match job's tokenization process. This scenario may happen if new records have been added or updated existing records.


3) Tokenization process during load job.
         If we enable the `Generate Match Tokens on Load' property on the base object then, when records loaded in the base object at that time the tokenization job will be triggered. It is not recommended to enable this property as it will adversely impact load job.






Learn more about the tokenization process here-


Wednesday, May 19, 2021

Informatica MDM match job and Tokenization job

       Are you interested in knowing what is the relationship between the Informatica MDM match and tokenization job? Would you also like to know what all conditions needed in order to tokenization job as part of match job? If so, then you reached the right place. In this article on Informatica MDM, we will learn match and tokenization job relationship.

A] What is the tokenization job in Informatica MDM?

           Tokenization is a process in Informatica during which match columns are used to generate tokens. These are based on the type of fuzzy match key column, another match column, and type of data present in the system 

          An example of the token is X01Z530K. It is an alphanumeric value for a given record.





B] What is a match job in Informatica MDM?

      By using the match process the record is matched in order to consolidate the record from various source systems. The match process uses tokens that are generated as part of the tokenization job.

       Once records are matched then those are stored in <BO Table>_MTCH table. The merge or consolidation process uses the MTCH table to consolidate the records.

C] Dose the match job always generate Match tokens?

        The answer is No. The match job will not always generate match tokens automatically. There various factors as part of a match job.





D]  What are factors are needed in order to generate tokens as part of the match job automatically?

         The following conditions are required to be there in order to generate a match token when we execute the match job.

     1. The base object should be fuzzy match enabled.

     2. The important ' Fuzzy Match Key ' column must be defined in match columns.

     3. Match ruleset should have at least on Fuzzy match rule.

     4. If generate Match Tokens job already executed then match job will not generate tokens.

     5. If the value of Dirty Indicator column value is 0 ( zero) for all the records then match job will not generate tokens

More details about the tokenization job are explained in the video -







What are the features of Informatica Intelligent Data Management Cloud (IDMC)?

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