The Glossary
This glossary provides an overview of Latttice-specific terms you’re likely to encounter in the How-To Guides and while using the platform. It highlights key concepts, features, and terminology that have unique meanings within the Latttice ecosystem, ensuring you have a clear understanding of the language and tools that power your experience with Latttice.
Data Mesh Terms
Data Mesh - A decentralized approach to managing data at scale, focusing on domain ownership, data as a product, and self-serve data access.
Data Product - A curated, reusable representation of data designed for a specific purpose, treated as a product with clear ownership and quality standards.
Domain Ownership - Assigning responsibility for data to the teams closest to its generation and usage, aligning accountability with expertise.
Self-Serve Data Access - The utilization of zero code, AI powered tools that enable users to create, manage, and access, data products independently without heavy reliance on centralized teams.
General Data Terms
ETL (Extract, Transform, Load) - The process of extracting data from a source, transforming it for analysis, and loading it into a destination system.
Metadata - Descriptive information about a dataset, such as its source, structure, or usage context.
Data Governance - Policies and processes to ensure data is accurate, consistent, and secure throughout its lifecycle.
Schema - The structure or organization of data in a dataset, including its fields, types, and relationships.
Data Catalog - A centralized inventory of datasets that provides metadata, discovery tools, and context for users.
Platform Specific Terms
Where you can investigate the Elements (Data Source) you have selected.
Latttice CoPilot - An AI-powered assistant in Latttice that uses natural language and automation to simplify data product creation.
Latttice Convo - A feature in Latttice that allows users to combine multiple data products into a single, enriched view, enabling seamless data integration and analysis.
Pin Board - A collaborative workspace in Latttice where users can "pin" and organize their favorite data products, insights, and visualizations for easy access and sharing.
Connector - A pre-built integration in Latttice that allows seamless connection to popular data sources and analytical systems.
Data Source - Any system or file containing raw data that can be connected or uploaded to Latttice for further processing.
Sandbox Environment - A safe, isolated space in Latttice where users can experiment and test workflows without affecting live data.
Data Pipeline - A sequence of processes for collecting, transforming, and delivering data to support Data Products.
Latttice CoPilot Terms
Natural Language Queries - Questions or instructions you can type into Latttice CoPilot to create data product, such as “Create me a data product joining dataset A with dataset B for all customers in Region C.”
AI Agent - AI technology embedded in Latttice that creates data product constructs.
Data Suggestions - Automated recommendations by Latttice CoPilot to enhance or enrich your data exploration process.
Data Transformation - The process of cleaning, shaping, or aggregating data to make it usable, assisted by CoPilot’s AI capabilities.
Latttice Convo Terms
Data Fusion - The process of combining data products from the same or different data products to create a fused data product.
Fused Data Product - A single, consolidated output created from multiple datasets using Fusion to provide a holistic perspective.
Join Logic - Rules used in Convo to define how datasets are merged, such as inner joins or outer joins.
User Role Terms
Data Producer - The person or team responsible for creating and maintaining a data product.
Data Consumer - The person or team using data products to generate insights or support decision-making.
Latttice Connectors
The following connectors are available in Latttice:
Cloud Data Warehouses: Snowflake, BigQuery, Amazon Redshift, Azure Synapse
Relational Databases: MySQL, PostgreSQL, SQL Server, Oracle, ClickHouse, Exasol, Vertica
Data Lakes: Amazon S3, Google Cloud Storage, Azure Data Lake, Delta Lake, Hive
NoSQL Databases: Cassandra, MongoDB, Elasticsearch, Druid, MariaDB
File Formats: Apache Parquet, Avro, CSV, JSON, Hive, Iceberg
Streaming Platforms: Apache Kafka, Kinesis.
Other. Black Hole, ElasticSearch, Faker, Google Sheets, Ignite, JMX, Kudu, OpenSearch, Phoenix, Pinot, Prometheus, Redis, SingleStore, Thrift
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