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 stream processing platform that has rapidly gained traction in the enterprise data management market.
      • 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.
        • Augmented Intelligence

          Augmented intelligence refers to the broad application of artificial intelligence (AI) technologies to augment human intelligence with the scale and speed of machine intelligence.
          • 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

            • 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 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 Software

              Business intelligence software refers to 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 aggregates current and historical data in a single repository within a cloud platform that can efficiently deliver data and insights to users across an enterprise.
            • 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

            • Dashboards

              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.
            • 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 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 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 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 different types of storage or file formats. Cloud data migration refers to transferring or replicating data from on-premise systems to cloud-based storage.
            • 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 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 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 Systems

              A decision support system includes the technologies used for management, operations, and planning in an organization to help users make better decisions by providing data and analytics capabilities.

            E

            • 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 is shorthand for – extract, transform, load. An ETL solution facilitates the replication of data from one or more sources that is converted into format suitable for use in analytics and moved into a destination system.
            • 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.

            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

            • 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 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

            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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