Data Processing in Martini

The Data Processing section focuses on the methodologies and techniques for managing and transforming data within the Martini platform. This section provides comprehensive guidance on various data processing strategies, enabling you to efficiently handle large datasets, ensure data quality, and integrate data from diverse sources.

Topics Covered

1. Overview: Get introduced to data processing concepts in the Martini platform, including the importance of data quality and integration in your applications.

2. Data Models: Learn about the structure and design of data models in Martini, including how to create, manage, and utilize data models effectively.

   • Creating/Deleting: Understand the steps to create and delete data models within the Martini platform.
   • Import/Export: Discover how to import and export data models, facilitating data sharing and collaboration.
   • Data Model Editor: Explore the Data Model Editor tool, which allows you to visually design and modify data models.
   • Object Types: Understand the various object types that can be defined within a data model.
   • Object Converters: Learn how to use object converters for transforming data between different formats.
   • Model References: Discover how to establish references between different data models for better organization and relationships.
   • Cursors: Explore the concept of cursors for navigating through datasets efficiently.
   • Normalizing Data Models: Understand the principles of normalization and how to apply them to your data models.

3. Master Data Management: Explore best practices for managing critical data assets, ensuring consistency, and maintaining data quality across your organization.

   • Overview: Get an introduction to Master Data Management and its significance.
   • CDM Mappings: Learn about mapping common data models for effective data integration.
   • Synchronization: Discover strategies for synchronizing master data across systems.
   • Advanced Sync: Explore advanced techniques for ensuring up-to-date data in real-time.
   • Testing: Understand the importance of testing in Master Data Management to ensure data accuracy and reliability.

4. Search Indexes: Learn how to create and manage search indexes to facilitate efficient data retrieval and searching capabilities.

   • Solr: Get introduced to using Solr for building powerful search functionalities.
     • Creating a Core: Learn how to create a core in Solr for organizing indexed data.
     • Indexing Documents: Discover the process of indexing documents for searchability.
     • Updating Documents: Understand how to update indexed documents effectively.
     • Deleting Documents: Explore methods for deleting documents from your search index.
     • Searching Documents: Learn how to perform searches on indexed documents using Solr.
     • Search API: Discover how to utilize the Search API for programmatic access to search functionality.
   • Elasticsearch: Understand how to leverage Elasticsearch for scalable and flexible search solutions.