Glossary of Industry Terms#

This glossary explains industry terminology that is used in Squirro’s documentation.

Also see the Squirro Glossary for Squirro-specific terms.

AI#: Artificial Intelligence. It is the simulation of human intelligence processes by computer systems.
Accuracy#: In ML, and specifically the Squirro AI Studio, how often a model is correct. It is calculated by dividing the number of correct predictions by the total number of predictions.
AJAX#: Asynchronous JavaScript and XML. A JavaScript development technique, that refers to JavaScript code loading additional data through API requests.
API#: Application Programming Interface. A computer interface that was created for consumption by computer programs. Squirro provides a number of APIs to programmatically ingest, and access data, and to work with Squirro projects.
Big Data#: Big Data refers to extremely large data sets that can be analyzed to reveal patterns, trends, and associations.
CLI#: Command Line Interface. Many Squirro capabilities are available on the command line. Those are mostly targeted at developers.
CORS#: Cross-Origin Resource Sharing. A mechanism that allows a web server to specify that certain JavaScript scripts are allowed to call the API. This enables cross-domain fetching of data from JavaScript. See the Mozilla web docs reference for Cross-Origin Resource Sharing (CORS).
CRM#: Customer Relationship Management. Squirro has existing integrations with Salesforce.com and Microsoft Dynamics.
DevOps#: DevOps is a set of practices that combines software development and IT operations to shorten the systems development life cycle and provide continuous delivery with high software quality.
Elasticsearch#: Elasticsearch is a distributed, open-source search and analytics engine that is used to store, search, and analyze large volumes of data quickly and in near real-time. It is built on top of the Apache Lucene search engine library and provides a RESTful API for querying data. Squirro uses Elasticsearch as its primary data store for ingesting and indexing data. Elasticsearch is used to store and index data from a variety of sources, including databases, file systems, and APIs. Squirro also uses Elasticsearch to power its search and analytics capabilities, allowing users to search and analyze large volumes of data quickly and easily. Additionally, Squirro provides Elasticsearch-based APIs that allow developers to programmatically access and manipulate data stored in Elasticsearch.
Embeddings#: A technique used in Generative AI that represents words or tokens as vectors in a high-dimensional space. The idea behind embeddings is to convert categorical, symbolic data (such as words) into numerical data that the model can process and learn from. Embeddings help models capture and understand the nuances of language, including things like word meaning, context, and even grammatical roles. Squirro uses paragraph embeddings in its Semantic and Hybrid Search feature.
Generative AI#: A type of AI that is used to generate new data, such as images, music, or text. Generative AI models are trained on large datasets and learn to generate new data that is similar to the training data. Examples of generative AI models include GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders).
Hallucinations#: Refers to a situation where a large language model (LLM) generates information or outputs that are not based on the data it was trained on or provided. These are typically facts or assertions that seem plausible but are not accurate or reliable.
LLM#: Large Language Model. A Generative AI program based on transformer architecture specifically designed to process and generate natural language. It utilizes machine learning principles, specifically deep learning, and is trained on large amounts of text data.
ML#: Machine Learning. Machine learning is a type of AI that allows software to learn automatically from existing data sets. This often replaces manual rule-based approaches.
NLP#: Natural Language Processing. A sub-set of ML used to understand natural language.
On-premises#: An on-premises deployment puts the infrastructure (such as the phsyicals servers and databases) fully under the client’s control. Squirro fully supports this deployment model in addition to its SaaS offerings. See System Administrator/DevOps Engineer for information.
Precision#: In ML, and specifically the Squirro AI Studio, how often a model is correct when it predicts a positive result. It is calculated by dividing the number of correct positive predictions by the total number of correct positive predictions plus false positive predictions.
RAG#: Retrieval-augmented generation. It is a type of natural language generation that combines the use of a retrieval model and a generative model. The retrieval model is used to retrieve relevant information from a database or a set of documents, and the generative model is used to generate a response based on the retrieved information.
Recall#: In ML, and specifically the Squirro AI Studio, how often a model predicts a positive result when the result is actually positive. It is calculated by dividing the number of correct positive predictions by the total number of correct positive predictions plus false positive predictions.
Regression#: Regression is a type of ML that is used to predict a continuous value. For example, it can be used to predict the price of a house based on its size and location.
Reinforcement Learning#: Reinforcement learning is a type of ML that is used to train an agent to make decisions in an environment. The agent receives rewards or punishments based on its actions, and learns to make better decisions over time.
SaaS#: Software as a Service. If Squirro is consumed as a SaaS offering, this means that the Squirro cloud is used to host the infrastructure. Squirro offers on-premises support as well.
SAML#: Security Assertion Markup Language. A standard for exchanging authentication and authorization data between an identity provider and a service provider. Squirro supports SAML for SSO. See SAML SSO for Squirro.
SDK#: Software Development Kit. Squirro provides SDKs for Python and JavaScript.
SSO#: Single Sign-On. A mechanism that allows users to authenticate once and gain access to multiple applications or services without having to re-enter their credentials. Squirro supports SSO through SAML. See SAML SSO for Squirro.
Tokenization#: Refers to the process of breaking down text data into smaller pieces, referred to as “tokens.” These tokens usually represent words or characters, depending on the type of tokenization used. For example, if the previous tokens correspond to the sentence “The quick brown fox jumps over the”, the model might predict that the next token should be “lazy”, because “The quick brown fox jumps over the lazy dog” is a common sentence.
Widget#: A user interface component that allows users to interact with the data displayed in the dashboard. Widgets can be used to display data in different formats, such as tables, charts, or maps, and can be configured to allow users to filter, sort, or drill down into the data. Widgets can also be used to display controls, such as buttons or sliders, that allow users to manipulate the data or change the behavior of the dashboard. See Widgets.