Search Results for

    Show / Hide Table of Contents

    SkyPoint Platform Glossary

    Audiences

    It is a group of profiles characterized by a defined set of attributes-based filters. You can schedule audiences to be auto-updated every day or update them manually for one-time use.

    Custom Models

    The feature allows the user to bring their own machine learning model and utilize the data from SkyPoint Studio to get the quality score.

    Dataflow

    Data import, export, connections, types (semantic labels) management, data transformations, and data quality management.

    Data Lake

    A Data Lake is a repository of data that stores a large amount of structured, semi-structured, and unstructured data.

    Data Maps

    Mapping different entities in a meaningful manner to formulate better insights with the data. It also provides an easier and powerful way to process, manage and secure the data with minimal complexity.

    Data Subject Requests

    This allows the customer to create a new Data subject request and shows the DSRs that are currently in review.

    Data Warehouse

    A data warehouse is a centralized repository for integrated data from numerous source data systems (Finance, Sales, Operations, etc.) for reporting and data analysis.

    Empower

    An all-in-one automation solution that integrates consent and preference management with data residency and privacy protection to ensure compliance with GDPR, CCPA, and other state laws.

    Entities

    Each data source ingested from the dataflows is added as an entity in the entity section. Entities are further added from Stitch Process which is the Profile entity, from Audiences , from Enrichment and from Metrics.

    Export

    It exports the entities to several destinations using export connectors provided by the platform.

    Instances

    You can consider them as subsidiaries of a single client. As soon as you create an account on the platform, a default instance is created for you namely Sandbox.

    Lakehouse

    Lakehouse brings together the benefits of a data lake and data warehouse to create a new open data management architecture based on Delta Lake.

    Map

    It defines the profile data in your entities by choosing the profile attributes, primary key, and types (datatypes defined by SkyPoint Cloud).

    Match

    It identifies the unique profiles in your entities by matching records based on certain rules.

    Merge

    It creates an entity of profile records by combining duplicate attributes and removing attributes you don’t need.

    Metrics

    Helps in tracking the performance of an organization by providing insights such as business metrics, profile metrics, and profile attributes.

    Modern Data Stack Platform

    A Modern Data Stack Platform is a data ingestion hub where you manage, clean, and analyze your data with automated pipelines and a myriad of integrations.

    Platform

    It consists of notifications, schedule, instance, product, activity stream.

    • Tenant : It displays all the basic details of the tenant with all the services assigned to it.
    • Instance : It displays the various details of the instance such as Tenant Name, Tenant website URL, Tenant identifier, Instance name, Instance identifier.
    • Notifications : It shows the notifications about dataflows and background processes. This sub-section helps to cover the area where we need to check the status of an iteration.
    • Schedule : It allows you to set a schedule to refresh all dataflows and autorun platform processes for the selected instance.
    • Activity Stream : It displays all the activity which was performed in the application.

    Predict

    Anticipate customer needs with real-time data and deliver meaningful experiences during every customer touchpoint using custom models and built-in AI.

    Profiles

    Profiles depict unified customers. Multiple entities ingested are stitched together with Identity resolution and ML model to generate a 360 view of unique customers.

    Relationships

    It is used to create associations/relationships between entities which can be further used when creating Audiences and Metrics.

    Resolve

    Establish a single source of truth with our proprietary ML-based identity resolution algorithm that produces rich and precise 360-degree customer profiles.

    Stitch

    Data Processing is performed in this section. It consists of three sub-sections: Map, Match & Merge.

    Timelines

    It depicts the entire customer's journey consisting timeline details of specific entities and attributes in the customer profiles

    Tenants

    Each customer is called a Tenant.

    Vault

    Zero trust data privacy vault with compliance to Modern Data Stack Platform.

    • Improve this Doc
    In This Article
    Back to top © SkyPoint Cloud Inc. All rights reserved.