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 - Latttice’s architectural approach that decentralizes data ownership. Teams manage their own data products while adhering to shared governance and standards.
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.
Data Source - Any system, file, or platform that provides raw data to Latttice (e.g., Redshift, Postgres, Snowflake). Data sources are connected via Latttice connectors.
Structured Data - Data that is highly organized and stored in defined formats such as rows and columns (e.g., databases, spreadsheets). Easily processed by analytics tools.
Unstructured Data - Data that does not have a predefined format or structure (e.g., Websites, Documents). Often requires additional processing to analyze effectively.
Platform Specific Terms
Where you can investigate the Elements (Data Source) you have selected.
Latttice - An AI-powered, zero-code data product platform that enables teams to create, secure, and share data products.
Zero-Code - Latttice’s philosophy of enabling users to build powerful data products without writing code or SQL. All actions, from data prep to insight generation, are done via a no-code interface.
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 curated collaborative dashboard where users can find, share & pin data products, creating a personal or team-wide view of what matters most.
Latttice Dashboard -
Latttice Connect - An API layer that enables external tools to securely access data products created within Latttice. Eg. PowerBI, Tableau, ServiceNow, Dataiku etc. Any tool that can access a REST API, can access via Latttice Connect.
Connector - A prebuilt integration that enables Latttice to connect with source systems e.g. Snowflake, Databricks, BigQuery, PDF Document etc. Latttice has a stable of 35+ connectors and growing.
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 GPT - A feature that allows users to securely browse, query, and interact with datasets directly through Chat GPT.
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.
Recommendations Engine - An AI agent that automatically analyzes the structure and content of your data product and provides suggestions for improving data quality and ensuring compliance with data privacy standards.
Latttice Governance
ABAC (Attribute-Based Access Control) - A granular access control model that grants or restricts access based on user and resource attributes (e.g., region, department). Enables dynamic, context-aware permissions across workspaces. There are four categories for ABAC Controls: Data Governance, Data Quality, Data Enrichment, and Data Transformation.
FGA (Fine-Grained Access Control) - A security model in Latttice that enforces row and column-level access control for users and groups. Users only see the data they’re permitted to view based on their role or attributes.
Latttice Convo Terms
Convo - Latttice’s natural language interface. Users ask questions in plain language and receive instant answers in a tabular format.
Data Fusion - The process of combining data products from the same or different data products to create a fused data product. Enables users to combine, transform, and enrich data products, by either combining data products together (either within or across data sources), or creating analytical versions of data products.
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.
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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