Data Integration & Analytics Glossary

Learn about the major concepts and terms for data analytics, business intelligence, and data integration with this in-depth industry glossary.

A

  • Active Intelligence

    Active Intelligence refers to a state of continuous intelligence where technology and processes support the triggering of immediate actions from real-time, up-to-date data.
    • Apache Kafka

      Apache Kafka is an open-source distributed event streaming platform which is optimized for ingesting and transforming real-time streaming data. By combining messaging, storage, and stream processing, it allows you to store and analyze historical and real-time data.
      • Augmented Analytics

        Augmented analytics (sometimes referred to as Augmented Intelligence) describes the use of artificial intelligence (AI) and machine learning technologies within a data analytics platform to enhance human intuition and productivity across the analytics lifecycle.
        • Azure Data Warehousing

          Microsoft's cloud data warehouse, Azure Synapse (formerly SQL Data Warehouse), provides the enterprise with significant advantages for processing and analyzing data for business intelligence.

          B

          • BI Dashboard

            A BI dashboard is a business intelligence tool which allows users to track, analyze and report on key performance indicators and other metrics. BI dashboards typically visualize data in charts, graphs and maps and this helps stakeholders understand, share and collaborate on the information.
          • Big Data Analytics

            Big data analytics is the process of collecting, preparing and analyzing large, diverse data sets to generate valuable insights.
          • Big Data Management

            Big Data management includes processes and technologies to accelerate data ingestion, simplify real-time analytics, monitor data usage, control costs, and manage workloads.
          • Business Analysis

            Business analysis is the means through which operational problems and issues are systematically identified and investigated, different approaches are evaluated, and optimal solutions are determined.
          • Business Insights

            A business insight is a deep understanding of a business situation that has the power to drive an organization forward. Finding patterns and trends in your data—and acting on that knowledge—gives your business a competitive advantage.
          • Business Intelligence

            Business intelligence (BI) combines applications, processes, and infrastructure that enables access to and analysis of information to improve and optimize decisions and performance.
          • Business Intelligence Reporting

            Business Intelligence reporting is broadly defined as the process of using a BI tool to prepare and analyze data to find and share actionable insights.
          • Business Intelligence Tools

            Business intelligence tools are technology or software applications used to collect, combine, and analyze various types of business-relevant information.

          C

          • Change Data Capture

            Change data capture is a technology used for identifying and capturing changes made to data in a database and delivering those changes to another database or other type of data repository.
          • Cloud Analytics

            Cloud analytics is a service model in which data analytics and business intelligence processes occur on a public or private cloud rather than on a company’s on-premise servers to help streamline the process of taking raw data to insights.
          • Cloud Data Migration

            Cloud data migration is the process of replicating and transferring data with technologies that simplify and accelerate data migration from many databases to many cloud platforms, efficiently and securely.
          • Cloud Data Warehouse

            A cloud data warehouse is a database stored as a managed service in a public cloud and optimized for scalable BI and analytics. It removes the constraint of physical data centers and lets you rapidly grow or shrink your data warehouses to meet changing business needs.
          • Compare Power BI vs Tableau vs Qlik

            Evaluating and selecting the best solution for your company can be challenging given that there are so many vendors. This guide compares the three Gartner Leaders, Power BI, Tableau and Qlik on 12 key evaluation criteria.
          • Continuous Intelligence

            Continuous Intelligence refers to a system that leverages real-time analytics which are embedded directly into business operations, providing continuous access to the most up-to-date, accurate information, right where users need it.
          • Conversational Analytics

            Conversational analytics allow users to work with a data analytics platform using natural language interaction through text, voice and other means to ask questions, request data and discover insights.

          D

          • Dashboard

            A dashboard presents critical data, visualizations, and KPIs focused on the specific needs of analytics user segments, allowing for a quicker, more organized review and analysis of business-critical information and trends.
          • Dashboard Reporting

            Dashboard reporting helps businesses make better informed decisions by allowing users to not only visualize KPIs and track performance, but also interact with data directly within the dashboard to analyze trends and gain insights.
          • Dashboard Software

            Dashboard software allows users to create visual representations of data and KPIs, helping them recognize patterns and make faster, data-driven decisions.
          • Data Analytics

            Data analytics refers to the use of processes and technology to combine and examine datasets, identify meaningful patterns, correlations, and trends in them, and most importantly, extract valuable insights.
          • Data Analytics Tools

            Data analytics tools are technology or software applications that allow users to find patterns, trends, and relationships in their data.
          • Data Discovery

            Data discovery is the process of using a range of technologies that allow users to quickly clean, combine, and analyze complex data sets and get the information they need to make smarter decisions and impactful discoveries.
          • Data Exploration

            Data exploration is the process through which a data analyst investigates the characteristics of a dataset to better understand the data contained within and to define basic metadata before building a data model.
          • Data Governance

            Data governance refers to the set of roles, processes, policies and tools which ensure proper data quality throughout the data lifecycle and proper data usage across an organization.
          • Data Ingestion

            Data ingestion is the process of moving data from a single or multiple data sources to an on-premise or cloud destination where that data can be stored for subsequent analysis by different users within an organization.
          • Data Integration

            Data integration is the process of synchronizing data across applications and data platforms and providing users with comprehensive, accurate, and up-to-date information for business intelligence and analytics.
          • Data Lake

            A data lake is a large and diverse reservoir of corporate data stored across a cluster of commodity servers running software, most often the Hadoop platform, for efficient, distributed data processing.
          • Data Lake vs Data Warehouse

            Data lakes and data warehouses are both universal data repositories. Data lakes typically store large volumes of unstructured data and data warehouses store structured data that has been processed based on predefined business needs.
          • Data Lakehouse

            A data lakehouse is a data management architecture which combines key capabilities of data lakes and data warehouses. It brings the benefits of a data lake, such as low storage cost and broad data access, plus the benefits of a data warehouse, such as data structures and management features.
          • Data Literacy

            Data literacy is the ability to read, work with, analyze and communicate with data, building the skills to ask the right questions of data and machines to make decisions and communicate meaning to others.
          • Data Management

            Data management consists of practices and tools used to ingest, store, organize, and maintain the data created and gathered by an organization in order to deliver reliable and timely data to users.
          • Data Mart

            A data mart is a structured data repository purpose-built to support the analytical needs of a particular line of business, department, or geographic region within an enterprise.
          • Data Migration

            Data migration is the process of moving data between storage systems, applications, or formats. Typically a one-time process, it can include prepping, extracting, transforming and loading the data.
          • Data Pipeline

            A data pipeline is a set of tools and processes used to automate the movement and transformation of data between a source system and a target repository. Building data pipelines can break down data silos and create a single, complete picture of your business.
          • Data Replication

            Data replication refers to the processes by which data is copied and moved from one system to another – from a database in the data center to a data warehouse in the cloud, for example.
          • Data Science vs Data Analytics

            Data science and data analytics are closely related but there are differences between the two fields. One key difference is that data science involves creating custom data models.
          • Data Streaming

            The process of moving data in a continual flow using modern replication technologies to inject database transactions into streaming systems like Kafka for real-time event processing, machine learning, and more.
          • Data Visualization

            Data visualization enables people to easily uncover actionable insights by presenting information and data in graphical, and often interactive graphs, charts, and maps.
          • Data Visualization Examples

            This guide showcases the ten most compelling and interesting data visualization examples from recent years. As you’ll see, a well-done chart can turn huge datasets into clear stories on any topic, from food to music to politics.
          • Data Visualization Tools

            Data visualization tools let users create graphics and imagery that help them make sense out of large amounts of data and make more informed decisions.
          • Data Warehouse

            A data warehouse is a data management solution to store large quantities of historical business data, performing queries to support various business intelligence and analytics use cases.
          • Data Warehouse Automation

            The process of automating the entire data warehouse lifecycle from data modeling and real-time ingestion to data marts and governance to accelerate the availability of analytics-ready data.
          • DataOps

            DataOps is a data management methodology that aims to improve the communication, integration, and automation of data flows between data management and consumers throughout an organization.
          • Decision Support System

            A decision support system (DSS) is an analytics software program used to gather and analyze data to inform decision making, either by suggesting insights and analyses for humans to perform or by automating calculations and delivering best-case decisions.
          • Digital Dashboard

            A digital dashboard is an electronic interface which allows users to track, analyze and report on KPIs and metrics. Modern, interactive dashboards make it easy to combine data from multiple sources and deeply explore and analyze the data directly within the dashboard itself.

          E

          • ELT

            ELT stands for “Extract, Load, and Transform” and describes the set of data integration processes to extract data from one system, load it into a target repository, and then transform it for downstream uses such as business intelligence (BI) and big data analytics.
          • Embedded Analytics

            Embedded analytics seamlessly integrate analytic capabilities and content from a data analytics platform into business applications, products, websites or portals to enable data-driven business processes.
          • ETL

            ETL stands for “Extract, Transform, and Load” and describes the set of processes to extract data from one system, transform it, and load it into a target repository.
          • ETL Pipeline

            An ETL pipeline is a set of processes to extract data from one system, transform it, and load it into a target repository. By converting raw data to match the target system before loading, ETL pipelines allow for systematic and accurate data analysis in the target repository.
          • ETL Tool

            An ETL tool is used to consolidate and transform multi-sourced data into a common format and load the transformed data into an easy-to-access storage environment such as a data warehouse or data mart.
          • ETL vs ELT

            The ETL and ELT acronyms both describe processes of extracting, transforming and loading data from a source into a target repository. In the ETL process, data transformation is performed in a staging area outside of the target repository and in ELT, transformation is performed on an as-needed basis in the target system itself.

          G

          • GeoAnalytics

            Geoanalytics leverage spatial data and visualizations to reveal crucial geospatial information and expose hidden geographic relationships to help users make better location-related decisions.

          I

          • Interactive Data Visualization

            Interactive data visualization is the use of tools and processes to produce a visual representation of data which can be explored and analyzed directly within the visualization itself. This interaction can help uncover insights which lead to better, data-driven decisions.
          • IOT Analytics

            IoT analytics is the application of data analytics to the streams of information coming from networks of consumer, enterprise, and industrial, internet-connected devices.

          K

          • Kafka Streams

            Kafka streams integrate real-time data from diverse source systems and make that data consumable as a message sequence by applications and analytics platforms such as data lake Hadoop systems.
          • KPI

            KPI stands for key performance indicator, a quantifiable measure of performance over time for a specific objective.
          • KPI Dashboard

            A KPI dashboard displays key performance indicators in interactive charts and graphs, allowing for quick, organized review and analysis.
          • KPI Examples

            KPI examples provide stakeholders guidance in selecting the most impactful key performance indicators for their organization and teams.
          • KPI Reports

            KPI reports provide a graphical, at-a-glance view of key metrics in real-time, helping decision-makers track the performance of their company, department, or initiatives, and identify areas in need of improvement

          M

          • Marketing Analytics

            Marketing analytics is the practice of combining and analyzing datasets, identifying patterns, and then coming away with actionable insights that improve the ROI of marketing efforts.
          • Marketing KPIs

            Marketing KPIs are quantifiable measures of performance for specific strategic objectives. Marketing leaders and teams use KPIs to gauge the effectiveness of their efforts, guide their strategy, and optimize their programs and campaigns.

          R

          • Reporting Analytics

            Reporting analytics refers to the process of collecting and analyzing data from various sources and presenting the results graphically and in an easy-to-consume format for efficient distribution.

          S

          • SAP Analytics

            SAP analytics refers to the processes and technologies that enable use of SAP business application data for analysis using modern data integration and data analytics systems or SAP’s native analytics tools.
          • Spatial Analysis

            Spatial analysis is the collection, display and manipulation of location data—or geodata—such as addresses, satellite images and GPS coordinates to uncover location-based insights.

          V

          • Visual Analytics

            Visual analytics integrates computational analysis techniques with interactive visualizations, offering users a new and innovative way to interact with, explore, and manipulate data.

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