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Monday, May 20, 2019

Overview of Informatica Customer 360i




Would you like to know more about what is Informatica Customer 360i? Are you also interested in knowing what are capabilities of the Informatica Customer 360i application? If so, then refer this article. This article also provides highlights on the underlying architecture of Informatica Customer 360i .


What is Informatica Customer 360i 



Informatica acquired AllSight company which is Artificial Intelligence enabled customer insight company on Feb 28, 2019. AllSight Inc a startup had a product named AllSight Intelligent 360. After-acquired by Informatica it called now as Informatica Customer 360 Insight (Customer 360i). It is powered by CLAIRE engine (Cloud-scale AI-powered Real-time Engine). CLAIRE uses artificial intelligence (AI) and machine-learning techniques powered by enterprise-wide data and metadata. It helps to significantly boost the productivity of all managers and users of data across the organization.

Capabilities of Informatica Customer 360i




1. It connects data of any type
2. It has capabilities to manage billions of records across all data sources
3. The customer data linkages can be easily resolved
4. With the help of Customer 360i, we can create relationships using advanced machine learning algorithms
5. Using Natural Language Processing we can provide additional customer attributes from unstructured data.
6. The relationships, households and complex B2B hierarchies using a graph data store can be easily visualized with product
7. It has capabilities to present multiple perspectives of the customer based on unique users and use case context




The architecture of Informatica Customer 360i

1. Customer 360 Insights is built on a big data technology stack.
2. The technologies used are Spark, Apache Hadoop, In-memory data stores, Graph, Columnar.
3. Data scientists can use R and Python languages with Informatica Customer 360i for flexibility.
4. It uses the microservices architecture to achieve scalability for deployment and redeployment of functionality
5. It also uses the SaaS deployment model which helps to simplify as well as accelerates implementation.

Use of Informatica Customer 360i

1. Informatica Customer 360i can be used for customer engagement
2. It works on structured and unstructured data sources
3. It will help enterprises to create the relationship between master, transaction, interaction, and reference data
4. These relationships will help to discover rich, personalized behavioral insights.


5. These insights can be used across the enterprise to connect customer interactions in real time and ensure the delivery of the next best action.
6. This new solution automates and simplifies profile and relationship unification
7. It also scales AI across transactions and interactions in the business data.




Customer Intelegence evolution

Application Centric
 1. Fix data quality
 2. De-duplication in the business data

Master Data Driven
 1. Resolve duplicate records from multiple store
 2. Manages master data
 3. Fix data quality in the enterprise system data


Customer Intelligence Empowered
 1. Match customer entities
 2. Enrich data with derived intelligence
 3. Provide multiple unique customer views

Sunday, May 19, 2019

Details about Informatica MDM metadata or infrastructure tables




You might have come across the term metadata tables in infrastructure tables during your Informatica MDM project implementation. What are these infrastructure tables? What is the significance of these tables? How can we access it and use it? Are you facing these questions and would like to know more about these? If so, then you reached the right place. In this article, we will explore the infrastructure tables get generated during the Base Object, Stage and Landing tables configuration. So let's start.

Introduction:

The MDM infrastructure tables are the core part of Informatica MDM. These tables are created, whenever we configure the basic tables such as Base Object (BO), Stage and Landing tables along with their properties such as Raw Retention, Delta detection on the Stage table or match and merge setting on the Base Object table.




What are the MDM infrastructure tables?

Assume that we create Landing table, Stage table, and Base Object table as C_L_PARTY, C_S_SALES_PARTY, and C_B_PARTY respectively. Also assume that we configure raw retention, delta detection, tokenization, match and merge rule as well. After doing all these configurations at table level the supporting tables are created.

  1. Tables at Landing table level: There is no infrastructure table created at the landing table level
  2. Tables at Staging table level: The tables created at the Staging table level are 
  • C_S_SALES_PARTY_RAW
  • C_S_SALES_PARTY_PRL
  • C_S_SALES_PARTY_OPL
  • C_S_SALES_PARTY_REJ
    Each of these tables has its own importance and are used during MDM batch job execution.
           3. Tables at Base Object table level: There are 14 supporting infrastructure tables are created.
  • C_B_PARTY_MTCH
  • C_B_PARTY_HIST
  • C_B_PARTY_XREF
  • C_B_PARTY_HXRF
  • C_B_PARTY_DRTY
  • C_B_PARTY_CTL
  • C_B_PARTY_HMRG
  • C_B_PARTY_HCTL
  • C_B_PARTY_EMI
  • C_B_PARTY_EMO
  • C_B_PARTY_VXR
  • C_B_PARTY_HVXR
  • C_B_PARTY_VCT
  • C_B_PARTY_STRP  

What is the need of the MDM infrastructure tables?

The Informatica MDM implementation involves various process such as Stage, Load, Tokenization, Match, Merge, etc. During each process, the data is transferred from the source table to the target table. During this transfer data is manipulated with the help of supporting table. e.g. During the stage job, the data is transferred from the landing tables to Staging tables. During this transfer, the landing data is maintained in _PRL, _RAW tables. The _PRL table data is used to determine delta of the source record which is subprocess during stage job. 

Similar cases are involved during load job as well tokenization job. These infrastructure tables play a vital role in Informatica MDM implementation.




Relationship between Landing table and the Base Object table

  • The load job loads data from the Stage table to a Base Object
  • There is still the dependency on landing table data to handle the rejection. 
  • The batch job will try to pull the source table record for inserting into the reject table.
  • If the landing table is missing the corresponding records, then the reject table will have an entry to state that the source table entry not found. 
  • If the landing table is huge and performance issues occur in the load job during the rejection handling, then assess the environment to add a custom index on the landing table.

Is it ok to modify the existing structure of the MDM infrastructure tables?

Informatica strongly recommends that do not modify the structure of these tables as these designed for internal processing purpose only. If you modify these tables, metadata validation may complain error.

The video below provides detailed information about the MDM infrastructure tables -


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