Friday, 24th May 2019

Building a case for embedded BI

By Dean Yao, Director of Marketing, Jinfonet Software.

Business intelligence (BI) drives business growth. In the not too distant past, “big data” was the domain of big corporations with the resources to analyze and apply insights gleaned from an accumulation of data related to all aspects of a company’s functioning. Now, though, data, and the tools to crunch it, are no longer the exclusive province of large enterprises, but are a core component of the decision-making process for businesses of all sizes and in all sectors.

Today’s sophisticated analytics tools perform a variety of data mining and reporting tasks under the label of business intelligence. They are making insights about company data available to anyone, for uses ranging from corporate decision-making to day-to-day operations performed by employees in all capacities. And now, embedded analytics, the next generation of business intelligence, is making data analytics more accessible, usable, in-context, and cost-effective than ever with clear benefits for productivity, engagement, and decision-making on all levels of a company’s operation.

What is Embedded BI?

Business intelligence is often called descriptive analytics or business analytics, though these things aren’t all exactly equivalent. Business intelligence includes reporting, dashboards, and analytics, but this far broader concept also refers to a range of strategies that involve leveraging tools, such as software and services from a variety of sources, to transform raw company data into actionable information. This information can then be used by relevant personnel, from the CEO on down, to drive decisions about all aspects of the company’s performance and future goals.

Standard business intelligence applications are designed to collect data, mine it for relevant insights, and present it in a meaningful and accessible way. But these applications and platforms typically exist separately from the data, which is held in a variety of programs and applications used by the company in day-to-day operations.

That means that raw data from files across a company’s systems must be exported to BI applications for analysis and processing. Not only does this process take time, but it also requires additional expenditure; the company must acquire the necessary stand-alone platforms to “crunch” the data alongside existing computing software. It also means that relevant personnel will have to learn a new interface just to gain access to cleaned and processed data. Thus, traditional business intelligence frameworks may not be efficient in terms of either time or money.

Embedded BI, also referred to as embedded analytics, aims to eliminate many of the limitations of existing BI solutions by incorporating BI tools directly into applications used for a company’s day-to-day functioning as well as software applications that vendors deliver to their customers. In this way, each of these applications has the ability to access, analyze, and present data within the context of its host application. BI tools can be built into new applications with a broader function or be integrated as an addition to existing applications the company is already using.

Adding the power of business intelligence tools to existing applications can have far-reaching implications in terms of accessing and using company data in more efficient ways. Incorporating embedded BI tools into a company’s current applications brings clear benefits for businesses of all sizes in terms of productivity, efficiency, and customer engagement.

Embedded BI Provides Real-Time Insights

Standard BI models that depend on standalone applications for analyzing data and preparing it for presentation typically operate on a time lag. Data must be collected from another source and then processed through the independent BI application before it can be used. But with the tools of embedded BI, data can be extracted and analyzed directly within the application where it originated, using analytical tools right in the report or dashboard. That provides users with immediate, real-time access to meaningful information that can be used to make decisions more quickly and efficiently – or to share with other users.

A Simpler Model Streamlines Usage

When BI tools are embedded within existing applications, there’s no need to switch between an open, work-specific application and a separate one for analytics. With the relevant tools easily accessible through their own report or dashboard, users can get the information they need on the spot. This provides immediate, applicable insights and also saves time since there’s no need to leave the application.

Adding analytical tools to familiar applications already in use means users don’t need to spend additional time learning a new interface in a standalone analytics application. It can also increase user engagement and reduce reluctance to access analytical tools in a different application, which can also enhance productivity and encourage wider use of the data being collected. Also, because the tools of BI are readily available and easy to use, even those without much technical experience can adopt them and remain engaged with them over time.

BI Becomes Efficient – and Economical

Embedded BI can be a more efficient model for collecting and analyzing data on every level of a company’s operation. When employees in all areas can access the data they need to make immediate decisions relevant to their workflow, they become more productive, minor problems can be solved quickly, and the data can also be used to drive higher-level strategic decisions about the company’s larger goals. Also, because data can be gathered and processed within existing applications, it becomes readily accessible to all members of a company’s workforce at the same time, whether they’re working on site or remotely.

Embedding BI tools and systems not only saves time and boosts productivity, but it can also be a more economical solution for creating a broad spectrum BI methodology in the company. This approach eliminates the need for purchasing, installing, and maintaining stand-alone analytics applications. It also reduces the need for a larger IT staff to manage a more diversified and widespread analytics operation involving multiple applications and systems.

Embedded BI applications can be used to collect data and run analytics on data sets from any level of the company and those tools can be used to shape operations across the organization, from front-line employees who need information to plan a daily workflow to executive staff making tactical decisions about the company’s future growth. Embedded BI within existing applications can provide information needed by staff at all levels of responsibility for a variety of tasks and functions. It also does so more quickly and smoothly than standard BI solutions would do.

Multiple Uses of Data for a Competitive Advantage

Data gathered in BI operations of all kinds can have multiple uses. Data that provides insights about one aspect of a company’s operations can reveal information relevant to other business areas within the company, as well as its overall mission and long-term goals. Embedded BI tools provide various kinds of data more quickly and comprehensively than standard BI methodologies. Users can analyze that data to respond rapidly to changes in the sector’s marketplace and new moves by competitors.

For e-commerce or retail users, embedded BI can be especially useful for gaining access to insights about consumer behavior and buying habits. Everyone, from sales and marketing staff to a company’s CEO, can use that insight to create a better user experience for consumers, craft long-term strategies for growing a customer base, or increase engagement with existing ones.

By keeping its functions simple, an embedded BI application can provide users, like sales managers, product developers, and advertising specialists, with a variety of insights into consumer buying behavior. Embedded BI applications are flexible and scalable so that they can be used over time by a variety of users as the company grows.

Just as it does in standard BI frameworks, data processed by embedded BI tools can be used to create and present analyses in useful, accessible formats – reports, charts, graphs, spreadsheets, and more. These materials can, in turn, be used to craft comprehensive reports, provide quick visual updates, and offer insights during meetings and consultations at all levels of the company.

No longer an exclusive tool for big companies, “big data” plays an essential role in businesses and enterprises of all kinds. That means companies, ranging from small startups to global enterprises, need an efficient, economical way to access, analyze, and present data relevant to every aspect of their operations.

Embedded BI is a fast-growing segment of business intelligence today. It's a solution for companies, small and large, that require fast access to data insights for strategic planning, decision making, and managing day to day operations.


Dresner Advisory Services, LLC. "Embedded Business Intelligence Market Study,"Microstrategy. 30 Nov 2017.

Harris, Daniel. “ A Guide to Embedded Analytics: Use Cases and Benefits.” Software Advantage. Accessed 26 Mar 2018.

Gardner, Michelle. “New Findings on the Adoption of Analytics: Why Embedded BI Is Taking Over.” Logi Analytics. 12 Dec 2016.

“New Study Views Embedded BI as Major Catalyst for Strategic Growth.” TechTarget. 3 Dec 2014.

“The Future of Business Intelligence is Embedded and Controversial.” Inside Big Data.20 May 2017.

“Top Benefits of Embedded BI” Panorama. Accessed 26 Mar 2018.

With TimeXtender Discovery Hub , Columbus delivers rapid reporting from multiple data sources.
According to an Accenture study, 79% of enterprise executives agree that companies not embracing big...
Did you know that autonomous vehicles are now the largest producer of data in the world? asks Chris...
The Big data and analytics question is at the forefront of many business leaders thinking but it’s w...
Business decisions are increasingly being made based on data insight, but getting access to this dat...
“We should be playing with two up front”, “We shouldn’t have subbed him off”, “I can’t believe they’...
By Adam Wilson, CEO, Trifacta.
With multiple different issues driving purchase and shoppers using different technologies to buy...