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
Capabilities of Informatica Customer 360i
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
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 360i1. 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.
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
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