Embedded analytics glossary

Did you think JSON was a developer on the team you hadn’t met? Explore the most important concepts in embedded BI below. Definitions from A to Z.

Actionable insights

Insights are actionable if they lead directly to action that drives business outcome. Actionable insights are strongly aligned to business goals or strategy. They are specific, clear and relevant in the user's context. For example, a marketer can automatically discontinue poorly performing campaigns from within a chart, based on previous campaign benchmarks.

Alerts

Alerts help SaaS product users proactively monitor their data. When a data point reaches a predefined threshold or an important KPI, an automated warning will alert a user via email, sms or another communication channel of choice.

Analytics database

An analytics database is a data management platform, optimized to store and organize data for the purpose of business intelligence and analytics. Analytics databases return complex queries at scale, which makes them a good foundational layer for an embedded analytics setup. Examples of analytics databases are Google Bigquery, Redshift, Snowflake, ClickHouse, SAP HANA and MongoDB.

Angular

Angular is a TypeScript-based, free open-source web application framework. Next to React, it is one of the popular front-end frameworks, managing the modeling, UI and control of a web application.

API

API or Application Programming Interface is a piece of software that connects different programs, and lets these applications to talk to each other. The interface defines how two programs communicate with each other using requests and responses. Typically, the workings of an API are described in the API documentation. For example, an API can be used to integrate dashboards within an application or create and update datasets.

Audit trail

An audit trail is a date and time-stamped, sequential record of the history and details around a transaction, event, or entry. Often, an audit trail is required for data regulation and compliance purposes.

Authentication

An authentication process verifies the identity of people with a set of credentials in a database or within an authentication server. Users can be authorized with a password or user name, via a token or via biometrics. Software providers use authentication mechanisms to provide secure access for eligible users only.

Authentication token

An authentication token securely transmits information about user identities between applications and websites. It allows users to access connected applications and web services with one login. In the context of embedded analytics, software companies can grant users access to embedded dashboards in their applications without having to enter their login credentials again.

AWS

Amazon Web Services (AWS) is one of the main cloud computing platforms next to Google Cloud and Azure (Microsoft).

Azure

Azure is one of the main cloud computing platforms owned by Microsoft, next to Google Cloud and AWS (Amazon).

Bi-directional communication

Bi-directional communication allows to exchange data between two applications in both directions. It is an essential element for actionable user analytics and real-time access to business-critical data. When a user completes an action in an embedded dashboard, it directly flows into the core software product for further usage, or vice versa. For example, users apply filtering in a dashboard, which is used to create a new target segment.

BI tool

A BI tool or platform is a type of software used to collect, transform, analyze and present data gathered from various data sources throughout business operations into useful, data-driven business insights. BI tools are typically used for internal reporting and business analytics.

Building blocks

Building blocks are reusable software components an engineer uses to build applications or extend an existing one. These components are designed to easily connect with other software parts, to scale and to adapt. Product add-ons like embedded analytics, onboarding flows, in-app chat functions and others are often deployed with specialized software building blocks that easily fit into an existing tech stack.

Build versus buy

Build versus buy is a decision framework to assess whether a software tool should be bought or built in-house. The framework evaluates relevant factors such as business and technical requirements, development and implementation costs, maintenance & support, resource availability, usability, and more. Calculating the ROI for both options is helpful to support the decision.

Business analytics

Business analytics is the practice of using services, tools and technologies to gain insights, solve problems, take decisions, or predict outcomes by exploring data and using analysis methods or statistics. Business analytics can be owned by data analysts or business users.

Clickhouse

ClickHouse® is an open-source, column-oriented analytical database management system. ClickHouse generates analytical data reports in real-time at scale. Alternatives to Clickhouse are Snowflake, PostgreSQL, and others.

Client-facing analytics

Client-facing analytics are analytics embedded in an application or platform to help end-users make better-informed decisions. This type of analytics add-on may better support business tactics, and can set a software product apart from the competition.

Cloud agnostic

Cloud agnostic refers to tools, platforms or applications that are compatible with any cloud infrastructure. Cloud agnostic tools can be moved to and from different cloud environments without any operational issues.

Cloud native

Cloud native is a way to build and run responsive and scalable apps anywhere - be it in public, private, or hybrid clouds. An app is "cloud native" if it provides a consistent development and automated management experience across any cloud throughout its lifecycle from development to production.

Collaborative analytics

Collaborative analytics enable collaboration on data analysis in one platform. It lets a broad group of people actively participate and use analytics, regardless of their role, skill set or specific needs. Components of collaborative analytics include user-tailored insights, commenting options, sharing & export features, or other options to work together on dashboards.

Compliance

Compliance is a business's conformation to laws, regulations, guidelines and specifications relevant to its business processes. It helps to protect a business's reputation and resources.

Composable architecture

Composable architecture is a framework for the digital industry to maximize the ability to build, assemble, unplug and reuse every business or IT element. Like with lego blocks, the same pieces can be used to build new "solutions", allowing software companies to rapidly seize market opportunities or roll out new capabilities.

CSS

CSS stands for Cascading Styling Sheet. It is a simple programming language mechanism for adding style to a web document or page (font, colors, spacing,...). Designers and developers use CSS to adapt the look and feel of websites, web applications or software products to the company's brand.

Customer Analytics Experience

Customer Analytics Experience (or in short, CAX) is a new perspective on the client-facing analytics feature set. It originates in the belief that people need insights to make smart decisions and that a premium experience will lead to more engaged and empowered users. CAX are premium client-facing analytics for SaaS where UX, personalized insights and end-user success intersect.

Custom events

A custom event increases interaction between two applications, for instance a dashboard and another application. Custom events trigger actions based on specific data clicked on in a chart. For example, in a marketing campaign tool, a user can create new target lists by visually segmenting users in a dashboard by slicing and dicing across various dimensions. The new target list can then be used for new campaigns in the core business flow across the company.

Data connection

A data connection is a dynamic interface between different applications - or an app and web services - through which data are transmitted, or other information can be sent and received. Most embedded analytics vendors offer a variety of out-of-the-box data connectors to common data sources like Google Analytics, Snowflake, Clickhouse, MySQL, PostgreSQL, and others.

Data governance

Data governance is a core process of a data management strategy. It is based on defined standards and policies to manage availability, security, consistency and usability of data. Often, a data governance team executes and monitors the data governance process.

Data lake

A data lake is a centralized repository designed to store, process, and secure large amounts of structured, semistructured, and unstructured data. It can store data in its native format and process any variety of it when needed, regardless of size limits.

Data mart

A data mart is a simple subset of a data warehouse that stores and maintains data that is ready for analysis, for one business line or subject line. It lets you get fast access to data and insights in contrast to exploring a more complex data warehouse structure. A data mart contains, for instance, subject-oriented data for the marketing department only.

Data mining

Data mining, or insights mining, is a process to extract and discover patterns in large batches of data. During this process, you'll turn raw data into useful information involving statistics, advanced analytics,or machine learning. Enriching embedded analytics with data mining supports business users to control smart and timely actions.

Data model

A data model is a logically structured, abstract diagram of a software system, a database or ecosystem and the data elements it contains. Text and symbols are used to represent the elements and how they relate to one another.

Data security

Data security is the process of protecting digital information from unauthorized access. It concerns both physical security of data, as well as policies and processes to ensure data is only accessible by authorized users. Data should be protected at all times against data breaches like cybercriminal activities, theft, insider threats and human error.

Data source

A data source is the physical or digital location where data is held in the form of a data table, data object, or other storage format.

Data stack

A data stack is a set of technologies and tools that perform the following basic functions for organizations: loading data, storing data in one place, transforming it into usable data, and opening it up to teams via analysis, business intelligence or embedded analytics.

Data visualization

A data visualization is a graphical presentation of data or information, and often a more accessible and efficient way of communicating insights. Intuitive, well-designed visualizations are important in embedded client-facing analytics as an aid to translate complex data into easy data stories, without the need for expert skills.

Data warehouse

A data warehouse is a large collection of business data used to help an organization make informed decisions. It stores transactional data, transforms data for analytical purposes, and is optimized for aggregation and retrieval of large data sets. Unlike a data lake, a data warehouse stores data in a structured way, readily available for reporting & data analysis.

Drag and drop

Drag-and-drop is a common feature in user interfaces, apps or software platforms. It is literally grabbing an object and dragging it to a different, desired location. This intuitive and easy technique helps embedded dashboard users to create charts and crunch data themselves without the need for expert support.

Drill down

Drill-down is an analytical capability that lets a user switch from a general insight view into more detailed, granular data at lower hierarchy levels in one click. It is a powerful, interactive UI feature for embedded analytics consumers.

Drill through

Drill-through is a powerful navigation technique in a data visualization or dashboard. A product user can explore data further by clicking on one chart and sending them to another dashboard or chart item to show related data.

Embedded analytics

Embedded analytics is an analytics solution seamlessly integrated in a software application or website. In many cases, users may be unaware that the report element, data visualization or analytical insight is delivered by an embedded, white-label analytics platform. Analytics feel native to the host application.

Embedded dashboard editor

An embedded dashboard editor is a self-service BI environment for end-users, seamlessly integrated and white-labeled in another software application. It lets end-users edit, customize, create dashboards and mine their own insights directly from within their core business application or workflow.

ETL

ETL stands for Extract, Transform, Load. It is a data integration process that collects and refines different types of data from multiple data sources, and delivers data to a data lake or analytical data warehouse such as Redshift, Snowflake, or BigQuery. It enforces data quality to present consistent data for end users to make decisions. The process plays a critical role in producing business intelligence and executing broader data management strategies.

Front-end

Front-end is the layer of a program or application visible to the user. It consists of graphics, typography, and a user-friendly interface that transforms information from the back-end to a graphical interface, by using CSS, HTML, and JavaScript.

Front-end framework

A front-end framework is a package to build the front-end of a website or application. It consists of packages of prewritten code, prebuilt site components like buttons, side panels, navigation bars, and defined font styles. It lets engineers quickly develop responsive, user-driven features at scale. Well-known examples of front-end frameworks are Angular, React, React Native and Vue. Visualization libraries are often available for the most common front-end frameworks and can be installed with a few lines of code.

Generic dashboards

Generic dashboards - or generic insights - are general, basic metrics that an entire customer base can easily access and understand. Generic insights are often shared via email, on a blog or website, or whichever channels customers use. They are relevant to a large group of people, which means they aren't very specific to a user's specific context.

Hierarchical data

Hierarchical data are linked to each other in a parent-child relationship, often represented in a tree diagram. It allows users to group, process and analyze data in a simple way and quickly drill down to the information they need.

Iframe

An inline frame - better known as an iframe - is an HTML element that loads another HTML page within a document or webpage. It essentially puts another webpage within the parent page. Iframes are commonly used for advertisements, embedded videos, web analytics or interactive content.

Interactive analytics

Interactive analytics make tons of data more usable for non-technical users with user-friendly tools. Features such as filtering, drill-down and alerts enable users to easily explore complex data, quickly run queries and interpret data to gain valuable insights on the spot.

Intuitive dashboards

Intuitive dashboards include practices and tools that let non-technical people use analytical features. That way, they can make sense of data directly while starting to use a dashboard, without needing help from a data scientist or data analyst.

IoT

IoT, or Internet of Things, is a system of connected physical objects (IoT devices) that exchange sensor data over a network. An IoT ecosystem consists of web-enabled smart devices that use systems to collect, send and act on acquired data. Data is either sent to the cloud to be analyzed or analyzed locally.

KPI

KPIs, or Key Performance Indicators, are measurable values that reveal how a team or company is performing against those business goals. Visualizing KPIs in dashboards help to monitor the progress and take the right action on any business goal, whether it’s in sales, marketing, or any other part of business.

Localization

Localization of software refers to the process of adapting software and related documentation to meet the requirements of a specific language and culture so it feels natural for an end-user. Adaptations can range from translations to language, spelling, date and number formatting, currencies, or even graphic and UX design.

Low-code

Low-code is a software development approach that requires little to no coding to build applications. Instead of using complex programming languages, applications are developed using visual interfaces with basic logic and drag-and-drop capabilities. If analytics is not a company's core activity, low-code technology is useful to rapidly deploy embedded analytics applications in a host software application. It removes complexity, minimizes the volume of coding and allows engineers to focus on improving the core application.

Measure and dimension picker

A measure and dimension picker is a function on an analytics dashboard that adds interactivity for its end-users. It gives users more control over the measures and dimensions being displayed in a dashboard, and allows deeper analysis within the same graph. Without support from experts, business users are able to choose a measure or dimension through the UI to automatically update and show their preferred data in a chart.

Metadata

Metadata is a set of underlying data, which summarizes basic information about data. Metadata can make it easier to find, use and reuse particular instances of data.

Microservices

Microservices are an architectural approach to software development. With microservices, software is composed of small, independent services that communicate over well-defined APIs. It makes applications faster to develop and easier to scale, enabling innovation and accelerating time-to-market for new features.

Modern data stack

Unlike a traditional data stack, a modern data stack is a flexible set of cloud-centric, managed service technologies designed around the business model and operations. Flexible, scalable plug & play blocks as part of a custom-built end-to-end solution - instead of an all-in-one solution - allow to act at the right time. With a modern data stack, companies can more easily adapt to changes. It also lowers the technical barrier for businesses to store, manage and learn from data. This is an important factor to consider in the deployment of a performant embedded analytics solution.

Monetization

In a SaaS context, monetization typically refers to different ways to generate revenue streams from product add-ons like embedded analytics. You can monetize product features either via tiered pricing, a flat fee, seat-based pricing, custom pricing, or positioning it as a necessary add-on for retention.

Multi-device

People use different devices at different times, but want software to work smoothly with the same user experience wherever they are, on whatever device they have at hand. Multi-device applications can easily run across different operating systems, platforms and devices.

Multi-language software

Although English is the standard language on the internet and in most apps, multi-language software allows for localization to different languages and helps to increase the attractiveness of software in international markets. A native multi-language UI for a core set of languages, or the possibility to easily translate terms in a UI will boost user experience and customer satisfaction.

Multi-stage aggregation

Multi-stage aggregation refers to the possibility of running formulas or calculations after aggregating or grouping of data. With multi-stage aggregation, you can answer more complex analytical questions like "What is the average maximum traffic jam length per weekday per country?" in addition to more basic queries like calculating the average traffic length per country. Multi-stage aggregation capabilities in an analytics dashboard add significant analytical power for end-users, especially when you don't have to do data manipulation.

Multi-tenancy

Multi-tenancy refers to a mode of operation of software where multiple independent instances of one or multiple applications operate in a shared environment. The instances (tenants) are logically isolated, but physically integrated. Multi-tenancy speeds up upgrades, saves time and lowers infrastructure costs.

Multi-tenant dashboards

In a multitenant analytics platform or dashboard, a user only sees data relevant to him. In addition, multi-tenant dashboards allow for other customizations that are personalized for each user. For example, you can greet a user with a theme that is meant for them only. Multi-tenant dashboards lower infrastructure costs, speed up software development and save time.

Multi-tenant databases

Multitenant databases store all data in one location and require row-level filtering to ensure each user only has access to his or her relevant data. Multi-tenant datasets lower infrastructure costs and save time.

NLG

Natural language generation (NLG) is the use of machine learning algorithms to discover patterns in datasets and automatically produce written or spoken insight narratives, as if written by humans.

NLQ

Natural language query (NLQ) is a self-service business intelligence reporting capability. It allows users to ask questions on their data using everyday business language, either typed into a search box or via voice command. It parses for keywords and generates relevant answers delivered as a report, chart or textual explanation to support business decisions.

No-code

No-code refers to software that can be used by non-professional developers. No-code does not necessarily mean no technical skills are needed. These tools provide small, flexible building blocks for developers to quickly assemble a bigger, custom application without writing code. They often have a simple user interface, and easy visualization of the development process and business logic. Simple and easy... At least for technical experts who understand programming concepts ;-).

Notification

A notification is a message for app or platform users outside the app's UI, or within the app itself. In-app notifications are common to notify users about new features, direct users to points of interest or share other useful information to support app users. Notifications can also be set up to alert users when a KPI is met or a data threshold is passed. It increases user engagement and boosts product usage.

OEM analytics

OEM analytics are analytics developed and distributed by expert technology providers, and then sold by other companies under their own brand. OEM applications help to reduce internal development costs and speed up deployment. End-users are typically not aware of the third party delivering the analytics solution. Rather, the OEM application is fully integrated and white-labeled into the main application.

Off-the-shelf

Off-the-shelf is a term used to describe an application, product, or database connectors that are ready-made, instantly available, and not specially designed or custom-made. These tools are made according to a standardized format. Off-the-shelf tools are typically part of the build-vs-buy assessment, especially for non-core add-on tools, which is often the case when adding embedded analytics to a SaaS product.

OKR

The acronym OKR stands for Objective and Key Results. OKRs help businesses focus better on results by defining measurable targets and tracking progress. Similar to KPIs, visualizing OKRs in an analytics dashboard helps to easily monitor and inform a broad audience of progress towards business goals.

OLAP

Online Analytical Processing (OLAP) is a computing method that lets users easily and selectively extract and query data, and analyze it from different points of view. OLAP is used for analytical database. Those queries often help with trend analysis, financial reporting, sales forecasting, budgeting and other planning activities.

OLTP

Online Transactional Processing (OLTP) is a data processing mechanism that handles large volumes of consecutive transactions at speed. OLTP is used for transactional databases, at the core of businesses operations. They typically consist of constant updates, many users accessing data, the need for fast response times and high availability. On the contrary, OLAP processing is a read-only data process optimized for analytical queries. Data can be moved from OTLP databases to OLAP databases via ETL.

On-premise

On-premise refers to IT infrastructure, hardware and software applications that are installed on a company's own servers, rented servers, or hosted in a company's own cloud environment. This contrasts with IT applications hosted on a public cloud, or external data center. On-premise solutions can become very cost-intensive, often require the right expertise, and are difficult to scale as demand grows.

Operational database

An operational database, or transactional database, is a database management system designed to run the day-to-day operations or business transactions of a business. Typically, operational databases store, update, retrieve, modify and process large amounts of data in real-time. Running analytical queries directly on an operational database is not recommended due to risk for suboptimal performance on both ends.

Plug and play

Plug and play refers to software, IT building blocks or devices that are intended to work perfectly when first used or connected, without reconfiguration or adjustment by the user. Plug-and-play components support a hassle-free installation process, reduce costs and make better use of resources.

Plugin

A plugin, also called add-on or extension, is an element of a software program that adds new functionality or specific features to an app. Or it enhances an existing application without altering the host program itself. Plugins are a convenient and fast way to connect an embedded analytics solution with data sources, web services, or any other API.

Portal

A portal is a web-based platform that shows relevant information from different sources in a single user interface to eligible users.

Predictive analytics

Predictive analytics use a variety of statistical techniques from data mining to predictive modeling and machine learning to make predictions of future outcomes based on current and historical data. When used in an embedded analytics solution, it gives more analytical power directly to end-users.

Product analytics

Product analytics are product engagement metrics that companies track and use internally to get a view on how their users are engaging and interacting with their products. Product stats can serve as input for product improvements or new developments.

Query engine

A query engine is a software component that allows companies to connect data from different sources in different formats and technologies. It then executes queries against that data to provide answers for users in an embedded analytics application.

React

React is a free, open-source front-end Javascript library for building user interfaces. Next to Angular, it is one of the most popular front-end frameworks. React focuses mainly on the appearance (UI) of a web application.

Real-time data

Real-time data (RTD) is information that is processed, delivered and consumed immediately after creation. It supports instant action and live decision-making inside an embedded dashboard with no delay after data is generated.

Recommendation engine

Recommendation engines are advanced algorithms or data filter systems that predict and suggest which content, products, or services are most relevant for a particular customer. It is based on the principle of collecting user behavior data, and can substantially enhance the level of customer analytics experience.

Responsive design

A responsive design is a graphical user interface for applications that adapts smoothly to different devices and screen sizes (desktop, mobile, smartphone,...) to optimize the user experience.

ROI of embedded analytics

The return on Investment (ROI) of embedded analytics in SaaS is the balance between (1) the total cost of ownership, including setup, implementation & maintenance, and (2) the value it delivers. Value could be defined as lifetime value of customers, growth in users, churn prevention, additional revenue stream options, or competitive advantage. More unconventional, and less quantifiable measures worth taking into account are the reduced burden on the engineering team, overall brand and product perception, increased product stickiness and usage, and more.

Scenario analysis

A scenario analysis evaluates possible events that could take place in the future. Changing one or multiple input variables allows to predict and evaluate various possible outcomes. This allows stakeholders to test decisions and assess risks.

SDK

A software development kit (SDK) is a collection of software tools and programs in one package used by developers to create an application for specific platforms. An SDK provides a set of tools (compiler, debugger, ...), libraries, relevant documentation, code samples, processes, and development guides.

Self-service analytics

Self-service analytics empowers users to find information, analyze data or support decisions on their own without interaction with a service team or data analytics expert. Essentially, self-service analytics put control and experience in the hand of users. When embedding analytics in other business applications, self-service is crucial to facilitate onboarding and adoption without the need for heavy training or expert skill sets.

Serverless

Serverless is a cloud-native development model that lets developers build and run applications without needing to design or think about the underlying infrastructure where their code runs. This delivery model automatically intercepts user requests and events to dynamically allocate and scale compute resources.

Server-side

Server-side means that action takes place on a web server. This is in contrast to client-side.

Single sign-on (SSO)

Single sign-on (SSO) is an identification method that lets users log in to multiple applications and websites with one set of credentials. As a result, it streamlines the authentication process. SSO enhances the user experience when embedding analytics in another product or platform.

Single source of truth

Single source of truth refers to a single, unified source for all the data within an organization. The concept ensures that everyone in the organization bases business decisions on the same data.

Snowflake

Snowflake is an advanced data platform provided as a software-as-a-service for data warehousing, data lakes, data engineering, data science, data application development, and secure sharing and consumption of data.

Static reporting

Static reports give insight in data at a specific point in time, but are not frequently updated. This contrasts with dynamic reports which provide up-to-date and real-time information.

Stickiness

Stickiness is a conceptual term used in product management. It refers to the tendency to gain repeat business, and continuing product usage via smart product design. The stickiness of a product is influenced by multiple factors such as user interface design, product quality, ease of use, pricing, and customer experience.

Streaming API

If an API allows two applications to talk to each other, a streaming API allows data exchange between digital assets in real-time for precise, up-to-date results.

Structured data

Structured data follow a defined data scheme, and can be categorized and stored in a structured data model like relational databases. Structured data enable easy manipulation and querying.

Technology agnostic

A piece of technology - hardware, software, databases,... - is called agnostic if it works and adapts easily to various operating systems or environments. Technology-agnostic tools are faster and more flexible to integrate in any existing architecture.

Temporary token

A temporary token is a protocol which verifies a product user's identity. In return, each user receives a unique access token. As the name suggests, a temporary token is short-term and security credentials are not stored with the user. Instead, they are dynamically generated and provided to the user when requested. Amn SSO token is often preferred for security reasons.

Embedded analytics

Self-service analytics

Custom data experiences

Composable analytics

AI analyst agent

Explore Luzmo AI

Embedded analytics glossary

Good decisions start with actionable insights.