DAM
Digital Asset Management (DAM) offers a solution for enterprises to efficiently store, organize, access, manage and share approved digital content and rich media. Find more information here.
Dashboard
A dashboard is a user interface that provides a centralized, interactive and visual way to monitor, analyze and extract relevant information from different datasets.
Data
Data is unprocessed information; a set of values of qualitative or quantitative variables about one or more objects.
Data consolidation
Data consolidation is the process of gathering, cleaning and verifying data from multiple sources and storing it in a single location, typically a database. This process enables companies to effectively plan and execute business processes and make informed decisions. Find more information here. See also Data onboarding.
Data governance
Data governance is an approach to managing a company’s data assets. It defines who is accountable for various aspects of an organization’s data and how the data is used, structured and stored. Find more information here.
Data hub
A data hub is a database populated with data from one or more defined sources and from which data is taken to one or more applications. A product data hub is an example of a data hub.
Data lake
A data lake stores data in its raw and natural format, structured and unstructured data, until it’s needed and processed. See also Data pool.
Data model
A data model defines the base data structure for products in a system. It identifies products from the highest level of classification, down to individual attributes and properties.
Data onboarding
Data onboarding is the technical process of uploading offline customer data to the online environment for marketing needs. The data is then combined and used for analysis purposes. Find more information here.
Data pool
A data pool is a centralized repository of data where trading partners (e.g., distributors, retailers or suppliers) can access, manage and exchange information about products in a standard format. See also Data lake.
Data steward
A data steward refers to the lead role in a data governance project, with responsibility for ensuring that data policies and standards turn into practice within the steward’s domain. See also Data stewardship.
Data stewardship
Data stewardship is the management and supervision of an organization’s data assets to help provide users with easily accessible, consistent and high-quality data. See also Data Steward and Data Governance.
Data syndication
Data syndication is a method that helps optimize an organization’s product data flow and ensure that the right data is delivered to the right customer touchpoint, at the right time.
Data warehouse
A data warehouse is a central repository for information and data from operational systems and external data sources. The data is used to generate insights and to perform analytics. Whereas a data lake stores raw data, a data warehouse typically works with structured predefined data. See also Data lake.
Deduplication
Deduplication is a process that eliminates excessive copies of data, reduces the impact of redundant information and decreases storage capacity requirements.
Digital asset
A digital asset is any material that is stored digitally and comes with the right to use. Examples of digital assets include videos, logos, animations, GIFs, audio files, presentations and spreadsheets. Find more information here.
Digital transformation
Digital transformation is the strategic integration of digital technologies to create new or modify existing business processes to meet market requirements. It represents the intersection of various constantly evolving sectors, from data analytics to cloud computing.
DQ
Data quality (DQ) refers to the measure of how well-suited and reliable a data set is to serve the end user’s defined purpose. It’s a relevant criterion to ensure that data-driven decisions are made as accurately as possible. Find more information here.