Glossary

3DES Encryption

3DES, also known as Triple DES, is the evolution of an encryption algorithm called DES (Data Encryption Standard) which was developed by IBM in the early 1970s. 3DES relies on the same mathematical and cryptographical concepts as DES, but – as the name implies – performs three separate encryption operations with three separate encryption keys.

AES Encryption

AES (Advanced Encryption Standard) is a widely adopted symmetric encryption algorithm, that ensures secure data transmission and storage by employing a standardized cryptographic process, widely recognized for its efficiency and robust security features.

Application Integration

Application integration is the process of enabling independently designed applications, systems, or software to work together. The goal is to create a seamless flow of information and functionality across different software applications, which might otherwise operate in isolation.

Data Architecture

Data architecture is the collection of models, standards, and business practices that act as a blueprint for how data is organized, stored, processed, and secured within an organization.

Data as a Service (DaaS)

Data as a Service (DaaS) is a big data management strategy that employs the cloud to provide data management services, from storage, integration, and processing—up to and including analytics. It’s an effective solution to managing massive amounts of data that is gaining popularity along with the broader adoption of other “as a Service” models.

Data Catalog

A data catalog is an organized, comprehensive inventory of all an organization’s data assets to help data professionals and business users use the data effectively. Data cataloging is the practice of storing information about data, including the type of data, where it’s located, and how it’s structured. A data catalog is like a library for data assets, providing detailed information about the data’s origin, format, quality, and usage, making it easier to determine its trustworthiness and relevance.

Data Governance Tools

Data governance tools are software solutions designed to manage, standardize, and monitor the access, quality, and security of data across an organization.

Data Intelligence

Data intelligence is the process that enables businesses to understand and use their data effectively. It involves a unique set of processes, artificial intelligence, technology, and tools that help organizations analyze, contextualize, and understand their data.

Data Marketplace

A data marketplace is a digital platform where data can be bought, sold, and accessed, much like an online marketplace for physical goods. These marketplaces serve as intermediaries that connect data providers—entities that have data to sell—with data consumers—businesses, researchers, or individuals seeking specific datasets. The marketplace operators manage the platform to ensure secure transactions, data quality, and compliance with relevant regulations.

Data Modeling

Data modeling is the process of visually mapping out the relationships between data points. It allows greater understanding of large datasets to identify trends and extract insights.

Data Product

A data product is a packaged set of data and related tools or insights designed to serve a specific business need. It treats the set as a product, focusing on usability, quality, and reliability, built to be easily accessible and actionable by end-users to streamline decision-making.

Data Retention Policy

A data retention policy is a systematic approach defined by an organization to manage the retention and disposal of its information assets. Such a policy outlines the duration for which data is to be kept, the method of storage, and the process for its eventual disposal or archiving to comply with governance policies and legal regulations.

Data Stewardship

Data stewardship is the practice of managing and overseeing data assets in an organization to ensure their quality, integrity, and security throughout their lifecycle. Fundamentally, data stewardship involves assigning ownership and accountability to data-related tasks and decisions, and implementing policies, processes, and controls to govern data usage, access, and protection. This includes activities like data quality management, metadata management, access control, and privacy compliance.

Data Strategy

A data strategy is a comprehensive plan that outlines how an organization collects, manages, and leverages data to achieve its business objectives. It serves as a guiding framework that ensures data activities are aligned with the company's goals and priorities.

Data Transformation

Data transformation is a fundamental process in data management and analysis that involves the conversion of data from one format or structure into another. This process is critical for integrating data from one or more sources, ensuring uniformity and consistency in datasets for analysis, reporting, and data-driven decision making.

Digital Marketing Analytics

Digital marketing analytics involves measuring, collecting, and analyzing data from various digital channels to understand how customers interact with your business. This data can come from websites, social media, email campaigns, and other digital platforms. By organizing and analyzing this data, businesses can build a comprehensive view of how their customers engage with digital content and make informed decisions to enhance their marketing efforts.

Digital Transformation

Digital transformation is the process of incorporating digital technology into every aspect of a business, resulting in significant changes in operations and how the business interacts with its customers. Digital transformation transcends mere technological upgrades; it requires a shift in an organization’s culture towards continuous innovation, adaptability, and embracing digital-centric strategies.

Enterprise Data Management

Enterprise data management (EDM) is the practice of managing an organization's data to ensure it is accurate, accessible, and secure. It involves the processes, policies, and tools that are used to handle data across an organization.

FHIR

Fast Healthcare Interoperability Resources (FHIR) is a standard for exchanging healthcare information electronically. It provides a framework for data exchange between healthcare systems, enabling interoperability and facilitating the exchange of patient data across different healthcare organizations and systems.

Predictive Analytics

Predictive analytics is the process of using data to predict future outcomes. It involves using data, statistical algorithms, and machine learning techniques to forecast possible results based on historical data. Organizations use it to identify patterns and trends that can guide future actions. Predictive analysis answers the question, "What is likely to happen or not happen?" It employs statistical models and other techniques to provide a forecast of likely outcomes based on historical data.

Prescriptive Analytics

Prescriptive analytics is the process of using data to determine an appropriate course of action. It involves data analytics tools, including machine-learning algorithms, to examine large data sets and recommend actions. This advanced form of data analysis answers the question, “What should we do?” It predicts future trends and makes suggestions on how to act on them by using optimization and simulation algorithms to recommend specific courses of action.

Serverless Architecture

Serverless architecture is a way of building and running applications and services without having to manage the underlying infrastructure typically associated with computing. In serverless architectures, the cloud provider automatically manages the allocation and provisioning of servers.

Advanced Data Materialization

Advanced data materialization means producing a shadow copy of a source table or virtual view in the central storage. This copy is managed and updated in a fully transparent and automated way.

Analytical Database

An analytical database is a data storage solution designed to optimize read, retrieval, and analysis of large datasets. The basic function of analytical databases mirrors more traditional transactional databases. However, while a transactional database is designed to optimize write (insert) operations, analytical databases emphasize high-performance read (select) operations that scale effectively to handle large sets of data.

API Management

API management refers to the processes involved in the oversight of the interfaces through which software applications communicate. It encompasses a broad range of activities aimed at ensuring the efficient operation of APIs throughout their lifecycle. API management tools provide the necessary infrastructure for securing, scaling, and analyzing API usage.

Automated Data Processing

Automated data processing (ADP) refers to the use of technology, including computer systems and software, to automatically process, organize, and manage data with minimal human intervention. Modern applications use advanced software, cloud computing, and artificial intelligence (AI) to handle large amounts of data for a wide range of activities.

Azure Data Factory

Azure Data Factory is a cloud-based data integration service for creating data-driven workflows in the cloud for orchestrating and automating data movement and data transformation. The tool does not store any data itself but facilitates the creation of data-driven workflows to orchestrate data movement between supported data stores and then process the data using compute services in other regions or an on-premises environment.

Cloud Data Access

Cloud data access refers to the ability to retrieve and manipulate data stored in cloud-based databases, storage systems, or applications.

Customer Data Enrichment

Customer data enrichment is a process in which raw customer data is enhanced by adding information from additional sources, which increases its value and utility. This involves taking basic customer data, which might be incomplete or insufficient for certain purposes, and supplementing it with relevant and complementary details.

Data Automation

Data automation is the use of technology to perform tasks that manage, process, and analyze data with minimal human intervention. Manual data processing needs human input for operations like entering data, sorting through spreadsheets, and generating reports. Comparatively, automated data processing employs software applications and platforms to perform these tasks, dramatically reducing the likelihood of errors and freeing up valuable time for employees to focus on more critical activities.

Data Enrichment

Data enrichment is a process in which raw data is enhanced by adding information from additional sources, thereby increasing its value and utility. This involves taking basic data, which might be incomplete or insufficient for certain purposes, and supplementing it with relevant and complementary details.

Data Exploration

Data exploration is the review of raw data to observe data set characteristics and patterns to identify the relationships between different variables. It helps to expose dataset structure, detect outliers, and how data values are distributed. These characteristics reveal patterns in the data and identify points of interest that enable data analysts to gain insight into the data before it is ported into a data warehouse.

Data Fabric

Data fabric is an integrated data management architecture that facilitates the seamless access, sharing, and governance of data across multiple environments, including on-premises, cloud, and hybrid systems. It employs automation, metadata management, and analytics to provide a unified view of data, enabling organizations to connect, manage, and secure data from disparate sources, improving data quality, accessibility, and decision-making.

Data Governance

Data governance is the system of rules, processes, and guidelines concerning how an organization manages its data. Data governance encompasses assigning the people who are responsible for the data, prescribing the rules around how it's processed, transported, and stored, and complying with company and government regulations to ensure data stays protected.

Data Gravity

Data gravity describes the tendency of large datasets to attract apps and services, which attracts more data. The bigger a dataset gets, the closer the apps and services need to be to retrieve the data, increasing the weight, or “gravity.” This term is also used to describe the relative permanence of a large dataset, which becomes increasingly difficult to copy or migrate.

Data Hygiene

Data hygiene is the practice of maintaining clean, accurate, and error-free databases through routine processes that ensure organizational data remains reliable and up to date. While data quality encompasses a broader range of activities, data hygiene specifically focuses on the day-to-day tasks of cleaning and maintaining data to keep it current and free from errors.

Data Lineage

Data lineage refers to the process of recording and tracking data’s entire journey through the business pipeline. The result is a visualization of how the data moves within an environment. That visualization enables businesses to track where the data comes from, how it has been transformed, and all the locations where it has been stored.

Data Mapping

Data mapping is a process of data management where a 'map' of the data is created to link fields from one database or dataset to those in another. A data map acts as a blueprint, illustrating how each piece of data from the source is associated with data in the target system.

Data Mart

A data mart is a structured data repository designed to serve a specific line of business (LOB). A subset of a data warehouse, a data mart contains data tailored for a distinct purpose and is accessible to a specialized set of users.

Data Mesh

Data mesh is a decentralized data management approach that shifts from traditional, monolithic architectures to a business-centric model. It treats data as a product, managed by domain-specific teams, and enables scalable, self-serve data infrastructure. Coined by Zhamak Dehghani in 2018, data mesh emphasizes domain ownership, self-serve infrastructure, and federated governance to make data more accessible and manageable across an organization.

Data Orchestration

Data orchestration is an automated process for managing and coordinating data from multiple sources, combining and organizing it so it can be analyzed. It transforms fragmented data into a cohesive resource that can be used to drive actionable insights. It ensures that data from all parts of the organization is accessible and usable, supporting everything from daily operations to strategic planning.

Data Pipeline

A data pipeline is a set of processes and technologies for moving and processing data from one system to another. It typically involves extracting data from various sources, transforming it into a format suitable for analysis, and then loading it into a data storage system for business intelligence, analytics, or other applications.

Data Quality

Data quality is the degree to which data meets its users’ expectations on accuracy, completeness, consistency, timeliness, relevance, and accessibility. It encompasses a variety of aspects, including the absence of errors or inconsistencies, the accuracy of values, how appropriate the data is for its intended use, and the ease of data access and interpretation. Data quality ensures that information is trustworthy and fit for purpose, which means users can analyze it and make decisions with confidence.

Data Repository

A data repository is a centralized location where data is stored and maintained. It’s a term that describes various centralized data storage options, like data warehouses, data lakes, and data marts. These systems are designed to store information for use across departments and/or geographic regions within the same organization. They act as a hub for all data-related activities, enabling businesses to make better-informed decisions based on accurate and readily available information.

Data Residency

Data residency refers to the physical location where data is stored. This includes an organization’s on-premises servers at each location and any cloud provider’s servers if used. An organization’s headquarters and its cloud provider’s headquarters might be in one location, but the servers could be somewhere else entirely. Multinational businesses or businesses that use cloud services in different countries must comply with the local or regional data residency regulations of each country they operate in.

Data Synchronization

Data synchronization is the process of ensuring that data in two or more locations is consistent and current. This involves continuously updating each data source to reflect changes made in the others so that the data is identical across different systems, devices, or databases in real-time or near real-time. Data synchronization can be bidirectional, where changes in any location are replicated across all others, or unidirectional, where updates from one primary source are pushed to other locations.

Data Virtualization Architecture

Data virtualization architecture is a technology framework that enables seamless access and integration of dispersed data sources. It allows organizations to retrieve, manipulate, and analyze data in a unified and efficient manner without the need for physical consolidation. This architecture hides the technical information about the data, such as how it is formatted or where it is located, making it easier for users to access and understand the data.

Data Warehouse

A data warehouse is a central repository of integrated data collected from multiple sources. It stores current and historical data in one single place that is typically used for analysis and reporting. The data stored in the warehouse is uploaded from systems such as marketing or sales. The data may pass through an operational data store and may require data cleansing for additional operations to ensure data quality before it is used in the data warehouse for reporting.

Data Wrangling

Data wrangling describes the use of various processes such as data collection, data cleansing, data enrichment, and data integration to transform data to a format that can be used in analysis. It’s used for cleaning, transforming, integrating, and enriching raw data to prepare it for analysis and decision-making purposes.

Database Management

Database management refers to the process of efficiently and effectively managing data within a database environment. It includes tasks like data storage, retrieval, updating, and security.

Database Management System

A database management system (DBMS) enables users to perform tasks such as creating, securing, retrieving, updating, and deleting data within a database. The system connects databases with users or with application programs, guaranteeing consistent organization, accessibility, and usability of the data. A DBMS also oversees the control of data, the database engine, and the database schema to ensure data security, integrity, concurrency, and consistent data-administration procedures.

Database Schema

A database schema is a structure that defines the associated database, including the definition of the tables, data types, and fields (or columns). The schema also defines the relationship between different tables, the primary and foreign keys, and indexes.

Database Virtualization

Database virtualization is the process of emulating the interaction between database software and the hardware it runs on, allowing servers with different hardware from the server housing the physical database to access resources from it. This permits the creation and distribution of virtual databases, which contain copies of curated subsets of the original database. These virtual databases are not bound to a single server, and don’t have to process all queries from all users on a single machine.

DBT

DBT (Data Build Tool) is a command-line tool that enables data analysts and engineers to transform data in their warehouse more effectively.

Delta Lake

Delta Lake is an open-source format framework that creates a storage layer built on top of an existing data lake. It enhances data storage and management by enabling ACID transactions, scalable metadata handling, and unified streaming and batch data processing.

Document Processing

Document processing is the method of handling and organizing documents in both digital and physical formats. It involves various steps such as capturing, sorting, extracting information, and storing documents efficiently.

Enterprise Automation

Enterprise automation is the use of technology and software to automate repetitive and manual business processes across an organization. This approach uses a variety of technologies, including artificial intelligence (AI), and machine learning (ML), and business process management (BPM), to create a cohesive, integrated system that automates tasks ranging from simple data entry to complex decision-making processes.

File Transfer Management

File transfer management involves the organized and efficient movement of digital files between systems or locations, ensuring secure and seamless data exchange. It is a critical aspect of modern computing, particularly for organizations that handle large volumes of data.

Hybrid Cloud

A hybrid cloud is a computing environment comprising a mix of on-premises, private cloud, and public cloud services that coordinate between the platforms. It's designed to give organizations greater control over their data and applications by creating a balance between the need for the scalability of public cloud services and the security of private cloud or on-premises infrastructure.

In-Database Analytics

In-database analytics is a technology that integrates analytic capabilities directly within the database, eliminating the need to transfer data between the database and separate analytics applications. This technology is built within an enterprise data warehouse (EDW), which supports parallel processing, partitioning, and scalability optimized for analytics. In-database analytics is used for comprehensive processing, usually for fraud detection, risk management, and trend and pattern analysis.

Logical Data Warehouse

A logical data warehouse provides a virtual data layer that makes the data look like it resides inside a common database, with a common interface and standardized data model.

Metadata Management

Metadata management is the process of organizing, controlling, and leveraging metadata throughout its lifecycle within an organization. This process includes defining metadata standards, capturing metadata from various sources, storing it in a central repository, and ensuring its accuracy, consistency, and accessibility.

SQLAlchemy

SQLAlchemy is an open-source SQL toolkit and Object-Relational Mapping (ORM) system for Python. It provides developers with the flexibility of using SQL databases in a Pythonic way. This means developers can work with Python objects and do not need to write separate SQL queries.

Workflow Management

Workflow management is the process of setting up, executing, and monitoring the series of steps required to complete a specific task.

Zero ETL

Zero ETL is a methodology for storing and analyzing data within its source system in its original format, without any need for transformation or data movement. Modern data warehouses and data lakes, which are already located in the cloud, can use integrated services of cloud providers to analyze the data directly from their original sources.

ADO

ADO (ActiveX Data Objects) is a Microsoft technology that provides a set of COM (Component Object Model) objects for accessing, editing, and updating data from a variety of sources through a single interface.

Apache Hive

Apache Hive is a fault-tolerant, distributed data warehouse system that enables data analytics at a massive scale. It enables data scientists and system administrators to read, write, and manage petabytes of data residing in distributed storage using its own version of SQL, Hive Query Language SQL.

Apache Spark ETL

Apache Spark is a distributed data processing framework that provides a high-level API for easy data transformation and has strong ecosystem support with many pre-built tools, connectors, and libraries. Apache Spark ETL efficiently handles large volumes of data, supports parallel processing, and allows for effective and accurate data aggregation from multiple sources.

Automate SFTP File Transfer

SFTP (secure file transfer protocol) is a specific protocol used to securely send data files from one software system to another. Files can be transferred manually over SFTP using tools like FileZilla or WinSCP, or file transfers can be automated to ensure reliability and speed.

CDC Data Replication

CDC data replication, or Change Data Capture, is a technique in database management that identifies and captures changes made to data, enabling real-time synchronization and replication of those changes across systems for accurate and up-to-date information.

Change Data Capture

Change Data Capture (CDC) is a technique used to automatically identify and capture changes made to the data in a database. Instead of processing or transferring the entire database, CDC focuses only on the data that has been altered, such as new entries, updates, or deletions.

Cloud Migration

Cloud migration refers to the process of moving digital assets (data, applications, IT processes, or entire databases) from on-premises computers to the cloud or moving them from one cloud environment to another.

Data Duplication

Data duplication (also called data redundancy) is the process of creating identical copies of data within a database or across multiple data storage systems. Unlike data replication, which synchronizes data across different locations, data duplication often refers to a single procedure to move data to another location. It can also refer to unintentional or unnecessary copying of data within a system.

Data Extraction

Data extraction involves retrieving relevant information from various sources, which can range from databases and websites to documents and multimedia files.

Data Hub

A data hub is an architecture that provides a central point for the flow of data between multiple sources and applications, enabling organizations to collect, integrate, and manage data efficiently. Unlike traditional data storage solutions, a data hub’s purpose focuses on data integration and accessibility.

Data Ingestion

Data ingestion is the process of gathering various types of data from multiple sources into a single storage medium—in the cloud, on-premises, or in an application—where it can be accessed and analyzed. This can be done manually for smaller and fewer data sets, but automation is a must for organizations that process large amounts of data harvested from numerous sources.

Data Loader

A data loader is a software component or application designed to load data efficiently into a system or another application. The primary purpose of data-loading applications is to facilitate the process of importing large volumes of data. Data loaders contribute to the efficiency and reliability of data-import processes across various applications, including database management systems, business intelligence (BI) systems, and data warehouses.

Data Migration

Data migration is the process of transferring data from one location—a storage system, file format, database, or environment—to another. It's a strategic process that can be part of a broader initiative like digital transformation to better align with modern business practices. It's also a major element of data consolidation in M&A (mergers and acquisitions), ensuring that all critical data is harmonized and accessible in a unified system.

Data Replication

Data replication is a process where data from various sources within an organization is copied to a central location like a database or data warehouse. It improves the availability and accessibility of data, ensuring that all users, regardless of their location, have access to consistent and updated information.

Data Transfer

Data transfer (also called data transmission) is the process of moving or copying data from one location, system, or device to another.

Data Warehouse Automation

Data warehouse automation refers to the use of dedicated software and tools to automate the processes involved in managing a data warehouse. It streamlines data retrieval from various sources, automatically applies business rules and transformations, and efficiently loads data into the warehouse for easier access and increased accuracy.

Enterprise File Transfer

Enterprise file transfer refers to the secure and efficient exchange of digital files within an organization, typically involving large volumes of data. This process ensures the seamless and reliable transmission of files between different systems, users, or departments. It uses specialized software or services that can handle the transfer of large files or high volumes of data, often across different geographical locations.

ETL Database

An ETL (extract, transform, load) database is a specialized system designed to efficiently manage the extraction, transformation, and loading of data from various sources into a unified destination for analytical or operational purposes.

ETL Testing

ETL (extract-transform-load) testing involves verifying the correctness of data transfer from various sources into a target system, typically a data warehouse, ensuring accuracy, consistency, and reliability of data after transformation.

FTP

FTP (File Transfer Protocol) is the earliest and most commonly used protocol for transferring files over the internet. It operates on a client-server model, where the client makes a data request, and the server responds by supplying the requested data.

MFT FTP Server

MFT FTP Server refers to a Managed File Transfer (MFT) solution that employs the File Transfer Protocol (FTP) for secure and efficient transfer of files between systems, ensuring reliable and streamlined data exchange.

Middleware

Middleware is a collection of software that acts as an interface between the functional APIs provided by an operating system, and the services provided throughout a company’s network, to distribute services throughout the company’s infrastructure. It does this by literally passing information between both sides of each requested software interaction in the system.

Reverse ETL

Reverse ETL is a process that reorders the process of traditional data integration. Unlike the conventional ETL (extract, transform, load) sequence, which aggregates and combines data from different sources into a centralized data warehouse for analysis, reverse ETL focuses on taking the processed and analyzed data from the warehouse and distributing it back to operational systems and business applications.

SCP File Transfer

SCP (Secure Copy Protocol) is a secure method for transferring files between local and remote systems over a network. It provides encrypted data transfer and authentication, ensuring the confidentiality and integrity of the transferred files.

SCP Port

SCP (Secure Copy Protocol) uses the TCP (Transmission Support Protocol) port 22 by default, which is the standard port for SSH (Secure Shell) connections. This port is used to establish secure communication between the client and the server, ensuring that data transferred via SCP is encrypted and secure from potential eavesdropping.

Secure Managed File Transfer

Secure managed file transfer involves the protected and controlled exchange of digital files between systems, ensuring confidentiality, integrity, and compliance with security standards throughout the transmission process.

SFTP

SFTP (SSH File Transfer Protocol) is a secure protocol used to access, transfer, and manage files over a network.

SQL Server Replication

SQL Server replication is a set of technologies for copying and distributing data and database objects from one database to another and synchronizing between databases to maintain consistency.

SSIS

SSIS (SQL Server Integration Services) is a component of Microsoft SQL Server used for data integration, transformation, and migration tasks.

SSIS ETL

SSIS, or SQL Server Integration Services, is a Microsoft platform used for building enterprise-level data integration and transformation solutions. SSIS ETL (Extract, Transform, Load) refers to the process of extracting data from various sources, transforming it according to business requirements, and loading it into a destination, all within the SSIS framework.

.NET Architecture

A .NET (pronounced 'dot-net') architecture refers to the structured design and framework configurations within the .NET ecosystem, encompassing various application architectures and patterns tailored for developing robust, scalable, and efficient software solutions.

API

An application programming interface (API) is a set of protocols, tools, and definitions that enable different software applications to communicate and interact with each other.

API Connector

An API connector is a software library, tool, or platform that facilitates the programmatic access to systems provided by APIs. API connectors make it easier for IT teams, developers, and other data consumers to access the data behind APIs.

API Integration

API integration is a process that connects multiple software applications using APIs (application programming interfaces) to communicate and share data. They enable systems to use each other’s functionalities to create a more efficient digital environment. API integration is used to automate tasks, enhance software capabilities, and improve the flow of data across disparate platforms. They play an important role in developing applications that interact with other internal or external systems.

Azure Synapse

Azure Synapse is a service designed by Microsoft to combine enterprise-level data warehousing and big data analytics into one streamlined platform. An evolution of Azure SQL Data Warehouse, Azure Synapse gives organizations the flexibility to analyze data with either serverless or dedicated resources.

BigQuery

Google BigQuery is a managed, serverless, and highly scalable data warehouse solution provided by Google as part of its Google Cloud Platform (GCP). It’s designed to store and analyze large datasets and supports various data types, including structured, semi-structured, and unstructured data. It uses columnar storage, which allows it to quickly read and aggregate data, enhancing the speed of SQL queries.

Cloud Connectivity

Cloud connectivity involves the use of the internet to link tools, applications, machines, and other technologies to cloud service providers (CSPs). These providers offer resources like computing power, storage, platforms, and application hosting.

Cloud Data Integration

Cloud data integration is the process of centralizing data access between disparate cloud-based sources and applications to create a single source for analysis and reporting. Cloud data integration allows businesses to move and transform raw, fragmented data from different cloud-based sources and applications using ETL (extract, transform, load) processes to make the data accessible and usable. This helps to gain business insights for informed decision-making.

Cloud Data Warehouse

A cloud data warehouse is a centralized data repository hosted on a cloud computing platform. Unlike traditional on-premises data warehouses, there is no upfront investment in hardware and infrastructure; instead, it leverages the cloud provider's resources. The key advantages of a cloud data warehouse include enhanced accessibility, reliability, and security. See: data warehouse

Cloud Integration

Cloud integration is the process of configuring multiple cloud services and local systems to connect and interact seamlessly. It involves integrating cloud-based applications, data sources, and IT services to enable unified and efficient data and workflow management across different platforms.

Cloud Managed File Transfer

Cloud managed file transfer (Cloud MFT) is a technology service that allows organizations to share files and data securely over the internet using cloud infrastructure. Unlike traditional managed file transfer (MFT), cloud MFT operates in a cloud environment, enabling organizations to manage file transfers without the need to invest in and maintain physical servers. See: Managed file transfer

Data Connectivity

Data connectivity refers to the process of creating a connection between data sources and systems or tools to read and analyze the data. This can be as simple as connecting a single source to a visualization tool, or it can involve multiple sources that need to be accessed by different users with varying permission levels.

Data Connectivity Platform

A data connectivity platform is a technology solution that promotes the integration and exchange of data across various systems, applications, and data sources. It provides the tools to connect these varying sources and applications, enabling the smooth flow of data, regardless of the native formats or protocols.

Data Connector

A data connector is a software tool that links various applications, data sources, systems, and web services, enabling the seamless exchange of data between them. Once connected, the connector automatically transfers data from its source to a specified destination. Data connectors work through Application Programming Interfaces (APIs) that grant the connector access to the system's data. Different business systems can communicate through the connector for data queries, analysis, and other functions.

Data Democratization

Data democratization refers to the process of making data accessible to non-technical users within an organization without the intervention of IT specialists or data scientists. The intention is to empower all employees-regardless of their technical expertise-to be able to use data in their decision-making processes.

Data Integration

Data integration is the process of centralizing data access between disparate sources and applications to create a single source for analysis and reporting. Data integration takes two shapes: live access through a semantic or virtualization layer or replication using ETL (extract, transform, load) processes. Both forms allow businesses to easily work with fragmented data from different sources and applications to gain business insights for informed decision-making.

Data Lake

A data lake is a centralized repository developed to store large amounts of raw, unstructured, or structured data. This approach is different from traditional databases and data warehouses that need pre-processed, structured data in files or folders for querying, analysis, and storage. Data lakes enable IT teams to store data in its native format, enhancing scalability and flexibility and making it easier for organizations to integrate, analyze, and process a variety of data types.

Data Virtualization

Data virtualization is a technology that coordinates real-time or near real-time data from different sources into coherent, self-service data services. This process supports a range of business applications and workloads, enabling data to be accessed and connected in real time without the need for replication or movement.

Data Warehouse Integration

Data warehouse integration connects individual data silos into a single cohesive system, allowing unified access to all the stored data. It works by standardizing data formats to ensure compatibility and then merging similar data points to reduce redundancies.

Database API

Database APIs provide a connection between an application and a database through a set of standardized instructions or commands. When an application makes a request to access or modify data, the API translates this request into a format that the database can understand. The database then processes the request and returns the appropriate response back to the API, which in turn delivers it to the application.

Driver Types

Drivers are the software components that facilitate communication between an application and a database management system. Common examples include JDBC (Java Database Connectivity) for Java applications, ODBC (Open Database Connectivity) for Windows-based applications, and ADO .NET (ActiveX Data Objects .NET) for .NET Framework applications, each tailored to their respective programming environments.

Enterprise Data Integration

Enterprise data integration is the process of combining data from disparate sources and applications to create a cohesive view for analysis and reporting. Data integration allows enterprises to move and transform raw, fragmented data from different sources and applications using ETL (extract, transform, load) processes to make the data accessible and usable. This helps to gain business insights for informed decision-making.

Integration Architecture

An integration architecture is a group of technologies and applications connecting disparate data sources and applications. It simplifies the integration of multiple data elements and tracks the flow of data between applications. Integration architecture allows different software applications to communicate, removing data silos and streamlining operations.

JDBC

JDBC (Java Database Connectivity) is a Java API that enables Java programs to execute SQL statements and interact with databases.

JDBC Driver

A JDBC (Java Database Connectivity) driver is a software component that enables Java applications to interact with databases by providing a means to connect to a database and execute SQL queries.

Managed File Transfer

Managed file transfer (MFT) is a technology platform that enables organizations to share electronic information in a secure way across different systems or organizations. It goes beyond simple file transfer protocol (FTP), hypertext transfer protocol (HTTP), and secure file transfer protocol (SFTP) methods by incorporating encryption, standardized delivery mechanisms, and tracking to ensure the safety and integrity of the data.

ODBC

ODBC (Open Database Connectivity) is a standard API that allows applications to access data from various database management systems (DBMSs).

ODBC Driver

An ODBC driver translates an application's queries into commands that the database understands, acting as a bridge between the application and the data. They enable efficient database connectivity across diverse systems. ODBC drivers enhance data accessibility and sharing across platforms, crucial for businesses operating in multi-database environments.

OLTP

OLTP, or Online Transaction Processing, refers to a type of computing that facilitates and manages transaction-oriented applications in real time, ensuring the efficient and immediate processing of business transactions such as order placements or financial transactions.

Procurement Data Management

Procurement data management refers to the process of collecting, organizing, storing, analyzing, and using data that is related to procurement activities within an organization. This process encompasses all the data that is associated with sourcing, purchasing, and acquiring goods and services from suppliers.

Redshift ETL

Redshift is a cloud-based data warehousing service provided by Amazon Web Services (AWS), designed to handle large-scale data analytics workloads. Redshift ETL (extract, transform, load) refers to the process of extracting data from various sources, transforming it into a usable format, and loading it into Amazon Redshift for analysis and reporting purposes.

Spark Connector

A Spark connector is a software component that enables seamless integration between Apache Spark and various data sources or storage systems. It allows Spark applications to read from and write to these systems using optimized connectors tailored for specific databases, file systems, or messaging platforms. Spark connectors facilitate efficient data ingestion, processing, and storage, improving data accessibility and enabling big data analytics.

Spark Data Pipeline

A Spark data pipeline is a robust and scalable framework that uses Apache Spark's distributed computing capabilities to efficiently process and transform data, enabling ETL (extract, transform, toad) workflows for large-scale data processing.

Spark JDBC

Spark JDBC refers to the Java Database Connectivity (JDBC) interface provided by Apache Spark, an open-source distributed computing framework. It enables Spark applications to interact with external databases using standard JDBC application programming interfaces (APIs), easing data retrieval, manipulation, and storage operations within Spark applications.

Spark Python

PySpark is a Python library that enables users to leverage Apache Spark, a powerful distributed computing framework, through Python programming language. It allows for seamless integration of Python's simplicity and flexibility with Spark's scalability and performance, facilitating efficient data processing and analytics tasks.

3PL EDI Integration

3PL (third-party logistics) EDI integration is the incorporation of Electronic Data Interchange (EDI) technology into business systems, to coordinate with third party logistics partners. 3PL EDI integration software platforms provide an interface for defining what data is exchanged with what trading partners, and how that data should be generated, received, processed, stored, transformed, and validated.

ACID Transaction

ACID (atomicity, consistency, isolation, durability) transactions ensure reliable and consistent database operations to maintain data integrity.

AS2 EDI

AS2 and EDI are two technologies used together to transfer business documents and messages between the computer systems of separate companies. It is a universal document standard that's been around for many years and offers maximum interoperability between trading partners.

B2B Data Integration

B2B (Business-to-Business) data integration is a specific type of data integration that permits the secure exchange of data between two or more businesses or trading partners. This type of integration employs automated systems to allow companies to share data like orders, invoices, inventory levels, and shipping information directly while also adhering to security and compliance protocols. This improves efficiency, reduces errors, accelerates decision-making, and strengthens partnerships between companies.

B2B File Transfer

B2B (Business-to-Business) file transfer refers to the automated, secure exchange of files between two or more businesses using specific protocols designed for B2B data integration. B2B file transfer systems manage the secure transfer of large volumes of data using encryption and authentication tools and protocols. This provides smooth communication and collaboration between businesses, improving overall operational efficiency, ensuring data safety, and streamlining workflows.

Business Process Automation

Business process automation (BPA) is the practice of using technology to automate repeatable, rule-based tasks within a business process. It involves automating complex business transactions that are typically multistep and repetitive. Unlike other types of automation, BPA solutions are often complex, connected to multiple enterprise IT systems, and tailored specifically to the needs of an organization.

Business Rules Engine

A business rules engine (BRE) is software that centralizes the management and execution of established business rules and processes. Business rules are defined and stored in the engine so they can be used consistently across systems and applications. BREs eliminate the guesswork and inconsistent interpretation of business processes, reducing errors, and improving decision-making. BREs separate business rules from application code, easing maintenance, and facilitating quick modification to adapt to changes.

Business System Integration

Business systems integration (BSI) is the process of connecting different business systems to share data and communicate with each other. This can help break down data silos and improve the flow of information throughout an organization. The top B2B integration platforms provide businesses an opportunity to automate and optimize various workflows and integrations.

Cloud Based EDI Solutions

Cloud-based EDI (electronic data interchange) solutions streamline electronic data interchange processes by providing secure, scalable, and accessible platforms for businesses to exchange critical documents and information over the internet.

Cloud EDI Software

Cloud EDI (electronic data interchange) software streamlines electronic data interchange processes by providing secure, scalable, and accessible platforms for businesses to exchange critical documents and information over the internet.

Data Transfer Protocols

Data transfer protocols refer to the standardized methods used to securely move data between various data sources and applications. These protocols ensure the integrity and reliability of data as it moves across different networks and systems. They define the rules for formatting, transmitting, and receiving data and ensure that the destination will correctly receive the data sent by the source.

DICOM (Digital Imaging and Communications in Medicine)

DICOM (Digital Imaging and Communications in Medicine) is the global standard for medical imaging and associated data. It specifies the formats of medical images that can be exchanged with the necessary data and quality for clinical applications.

Different Types of EDI

EDI (electronic data interchange) is a collection of standards that specify how business documents can be understood by different software systems, even if they are not compatible with each other. The two most prominent types of EDI are X12 and EDIFACT.

EDI 210

An EDI 210 is a type of X12 EDI document called a Motor Carrier Freight Details and Invoice. The document is sent by shipment carriers (e.g., FedEx, USPS) to companies that have requested the use of their trucks, planes, and ships to carry goods.

EDI 214

An EDI 214 is a type of X12 EDI document called a Transportation Carrier Shipment Status Message. The document is sent by shipment carriers (e.g., FedEx, USPS) to companies that have requested the use of their trucks, planes, and ships to carry goods.

EDI 240

An EDI 240 is a type of X12 EDI document called a Motor Carrier Package Status. It is exchanged between logistics providers and shipment carriers (e.g., FedEx, USPS) to provide updates on the status of shipped goods.

EDI 810

An EDI 810 is a type of X12 EDI document called an Invoice. It provides the same function as a paper or electronic invoice, including purchase details, item details, and the amount owed.

EDI 820

EDI 820, also known as the Payment Order/Remittance Advice, is an electronic data interchange (EDI) transaction set used in business to transmit detailed payment information from a payer to a payee. It includes data such as payment instructions, remittance details, and financial transaction information.

EDI 830

The EDI 830 transaction, also known as the Planning Schedule with Release Capability, is an Electronic Data Interchange (EDI) document that enables the transmission of detailed production schedules and planning information between trading partners in the supply chain, facilitating effective coordination and planning.

EDI 835

An EDI 835 document is a specific type of X12 EDI message called an electronic remittance advice (ERA). Healthcare insurance providers send EDI 835 documents to healthcare service providers, like hospitals, when the insurance provider has approved payment for specific claims submitted by the service provider.

EDI 837

EDI 837 refers to a standard electronic data interchange (EDI) format used in the healthcare industry for the transmission of healthcare claims. It facilitates the exchange of information between healthcare providers and payers, streamlining the billing process and ensuring uniformity in data communication.

EDI 846

An EDI 846 is a type of digital business document called the Inventory Inquiry/Advice. It standardizes the format of an electronic message that businesses use to communicate inventory levels, whether to inquire about the inventory status of a supplier or to advise a customer or partner about product availability.

EDI 850

An EDI 850 is a type of X12 EDI document called a Purchase Order. It provides the same function as a paper or electronic purchase order and contains the same information.

EDI 852

EDI 852, also known as Product Activity Data, is an electronic data interchange (EDI) document that provides detailed information on product sales and inventory levels, aiding in efficient supply chain management and demand forecasting.

EDI 856

An EDI 856 is a type of X12 EDI document called an Advance Shipment Notice (ASN). An ASN indicates that ordered items are being prepared for shipment and includes details on expected delivery.

EDI 861

EDI 861, also known as the Receiving Advice/Acceptance Certificate, is an electronic document used in Electronic Data Interchange (EDI) to confirm the receipt of goods or services. It provides acknowledgment and acceptance details, enhancing communication and efficiency in supply chain transactions.

EDI 862

The EDI 862, also known as the Shipping Schedule/Production Sequence, is an electronic data interchange (EDI) document used in supply chain management to communicate shipping schedules and production sequences between trading partners in a standardized format.

EDI 997

EDI 997, also known as an Acknowledgment (ACK) in electronic data interchange (EDI), is a functional acknowledgment sent by the recipient to confirm the receipt and successful processing of an incoming EDI transaction.

EDI Client

An EDI client is a software application or system that enables users to interact with Electronic Data Interchange (EDI) services, facilitating the exchange of standardized business documents between trading partners for seamless and efficient communication.

EDI File Transfer Protocol

An EDI file transfer protocol refers to the standardized methods used to securely exchange Electronic Data Interchange (EDI) documents between businesses. These protocols ensure data integrity, confidentiality, and reliability during the transfer of business-critical documents. Common EDI file transfer protocols include AS2, SFTP, FTPS, OFTP, and VAN, each offering features like encryption, authentication, and non-repudiation for efficient and secure business communication.

EDI Format

EDI (Electronic Data Interchange) format is a standardized electronic format for the exchange of business documents. It allows seamless communication and data exchange between different systems and trading partners in a structured manner.

EDI Healthcare

EDI healthcare, or Electronic Data Interchange in healthcare, refers to the electronic exchange of standardized healthcare information between different parties, streamlining administrative processes, improving accuracy, and enhancing efficiency in the healthcare industry.

EDI Integration

EDI integration refers to the seamless incorporation of Electronic Data Interchange (EDI) technology into business systems, enabling efficient and automated exchange of structured data between trading partners for streamlined communication and transaction processing.

EDI Logistics

EDI logistics, or Electronic Data Interchange in logistics, refers to the automated exchange of business documents and information between trading partners in the supply chain, streamlining communication and enhancing efficiency in the logistics and transportation processes.

EDI Mapping

EDI mapping involves the process of translating electronic data interchange (EDI) messages between trading partners by mapping data elements from one format to another, ensuring seamless communication and data exchange in business transactions.

EDI Payment

EDI payment is an umbrella term that encompasses the exchange of several types of EDI documents that relate specifically to purchasing and fulfillment. Importantly, EDI payments are not the direct transfer of money between bank accounts. Rather, EDI documents are used to catalogue and communicate the necessary transfer of money to external parties.

EDI Services

EDI services, or Electronic Data Interchange services, facilitate the electronic exchange of business documents between trading partners, streamlining communication, reducing manual intervention, and enhancing efficiency in supply chain and business operations.

EDI Shipping

EDI shipping describes the communication processes between trading partners in the supply chain. This involves exchanging documents such as bills of lading, purchase orders, invoices, and shipment statuses. The aim is to minimize or eliminate manual errors and delays, thereby enhancing the efficiency of shipping operations.

EDI Standards

EDI standards, or Electronic Data Interchange standards, define a set of rules and guidelines for the electronic exchange of business documents between trading partners. These standards ensure uniformity and compatibility in data formats, facilitating seamless communication and transactions in the business-to-business (B2B) environment.

EDI Supply Chain

EDI (Electronic Data Interchange) in the supply chain streamlines and automates the exchange of business documents between trading partners, enhancing efficiency, accuracy, and communication in the procurement and distribution processes.

EDI System

An EDI (Electronic Data Interchange) system is a digital framework that enables the exchange of business documents and transactions in a standardized electronic format, facilitating seamless communication and collaboration between trading partners.

EDI to CSV

EDI 861, also known as the Receiving Advice/Acceptance Certificate, is an electronic document used in Electronic Data Interchange (EDI) to confirm the receipt of goods or services. It provides acknowledgment and acceptance details, enhancing communication and efficiency in supply chain transactions.

EDI Transactions

EDI transactions refer to standardized electronic business documents trading partners use to send and receive business information. These transactions allow businesses to exchange documents such as purchase orders or invoices quickly and efficiently, promoting seamless transfer of information.

EDI Translator

An EDI (Electronic Data Interchange) translator is a specialized software tool that facilitates the seamless exchange and translation of electronic documents between different systems, ensuring compatibility and efficient communication in business transactions.

EDIFACT

EDIFACT (Electronic Data Interchange for Administration, Commerce, and Transport) is a widely used global standard for electronic data interchange (EDI) between business entities.

EDIFACT XML

EDIFACT XML refers to the electronic data interchange standard, EDIFACT, expressed in XML (eXtensible Markup Language) format. It enables the structured and standardized exchange of business documents between different computer systems.

EHR (Electronic Health Record)

An electronic health record (EHR) is a digital representation of a patient’s paper chart, designed for real-time, patient-centered care. It provides instant and secure access to authorized users and encompasses a wide range of patient information.

Enterprise Application Integration

Enterprise application integration (EAI) refers to the process of linking different enterprise applications within an organization to simplify and automate business processes to the greatest extent possible, while also ensuring seamless data sharing across various systems. EAI allows for the integration of disparate applications, which may have been developed and deployed in different environments, enabling them to communicate effectively and function as a cohesive unit.

Enterprise Data Warehouse

An enterprise data warehouse (EDW) is a centralized repository that consolidates a company's historical business data from multiple sources and applications. It is typically a collection of databases that store structured data, enabling businesses to perform complex queries and generate insights across the organization.

ETL Pipeline

An ETL pipeline is a type of data pipeline, which is a set of processes for managing and using data. The ETL pipeline extracts data from one or more sources and, if needed, is transformed into a form or format suitable for its intended use. After the transformation process, the data is loaded into a storage system, like a data warehouse or a data lake, for analysis, reporting, and machine learning projects.

File Transfer Protocols

File transfer protocols are standardized methods used to transfer files between computers over a network. They govern how data is formatted, transmitted, and authenticated, ensuring secure and efficient data exchange. Common protocols include FTP, SFTP, FTPS, HTTP/S, and AS2, each offering various features such as encryption, authentication, and data integrity verification to facilitate reliable file transfer in different environments.

Financial EDI

FEDI is electronic data interchange of financial data, in a standardized format. FEDI is mainly used by medium- to large-size companies and their trading partners, federal governments, and state governments, but is generally everywhere goods or services are sold. FEDI provides a standardized format for financial data understood by software systems within financial institutions, eliminating the need for paper-based transactions.

FTP Port

One of two ports (Port 21 and Port 20) that serves a specific role in the FTP communication process.

FTP Server

An FTP server is a server that uses a specialized software application that uses the File Transfer Protocol (FTP) to store and manage files. It acts as a digital storage hub, allowing users to upload or download files to and from the server over a network or the internet.

Health Information Exchange (HIE)

Health information exchange (HIE) is a technology that allows digital access and sharing of patient information within a hospital system, a community, or a region.

HIPAA EDI

HIPAA EDI, or Health Insurance Portability and Accountability Act Electronic Data Interchange, refers to the standardized electronic exchange of healthcare-related data between entities, ensuring secure and efficient communication in compliance with HIPAA regulations.

HL7 Software

HL7 software facilitates effective communication and interoperability within the healthcare industry by adhering to the Health Level Seven (HL7) standards, streamlining the exchange of clinical and administrative data between healthcare systems and applications.

IDoc in SAP

IDocs (intermediate documents) are standardized documents, or data containers, used for data exchange with SAP applications and non-SAP systems. SAP IDoc transactions resemble EDI documents and are commonly used to electronically transfer information, such as purchase orders, invoices, shipping notices and more. IDocs are based on two EDI standards, X12 and EDIFACT, each defining types of transactions and the data segment formats required to communicate the information.

Integration Platform as a Service (iPaaS)

Integration Platform as a Service (iPaaS) is a self-service cloud-based solution that standardizes how applications are integrated, simplifying integration across on-premises and cloud environments. It is essentially a cloud-based, API-driven middleware that can be used to integrate any two or more SaaS (Software as a Service) solutions, cloud applications, data sources, or even legacy systems, from one central hub.

Inventory Integration

Inventory integration is the process of connecting and synchronizing an inventory management system with other systems, particularly accounting systems, and other back-office systems, such as order fulfillment. This helps product suppliers maintain the correct inventory types and amounts to meet customer demand. This also helps provide supply chain partners with transparent and up-to-date information, as well as provide accurate information for financial reporting and to government compliance.

Managed File Transfer Service

A managed file transfer (MFT) service is a secure and automated solution that facilitates smooth and efficient exchange of files between users, systems, or organizations, ensuring data integrity and compliance with security protocols throughout the transfer process.

Map Connector

A map connector is a software component that facilitates the seamless integration of data between different systems by translating or mapping data formats from one system to another. It allows organizations to connect disparate applications, databases, and data sources, ensuring accurate and efficient data transformation, compatibility, and communication across platforms.

NetSuite EDI Integration

Netsuite EDI integration streamlines the exchange of electronic data interchange (EDI) transactions within the NetSuite platform, enhancing efficiency and accuracy in business-to-business communication and transaction processing.

OFTP2

OFTP2 (Odette File Transfer Protocol version 2) is a secure and standardized protocol for electronic data interchange (EDI). It uses encryption and digital signatures to secure data during transmission, ensuring that it cannot be intercepted or tampered with during transit.

Secure Enterprise File Transfer

Secure enterprise file transfer refers to the protected and encrypted exchange of digital files within an organization, ensuring data integrity and confidentiality during the transmission process.

Web EDI

Web-based EDI is a modern adaptation of traditional EDI that leverages the internet to facilitate the exchange of business documents between trading partners. By using a standard web browser interface, Web EDI significantly simplifies the EDI process, reducing the need for specialized software and extensive IT support. This approach democratizes EDI technology, making it accessible to businesses of all sizes, including those that might lack the resources for more complex setups.

What is EDI

Electronic Data Interchange (EDI) is a computer-to-computer exchange of business documents in a standard electronic format between two or more trading partners. It enables companies to exchange information electronically in a structured format, eliminating the need for manual data entry and reducing the cost and time associated with paper-based transactions.

Business Rules

Business rules refer to the guidelines or principles that dictate how various aspects of a business should operate. They encompass the procedures, policies, and conditions that guide decision-making and actions within an organization.