Given the times, many companies around the world are realizing that traditional methods of enabling analytics no longer work or are no longer relevant. Waiting for professionals to run analytics to give us results and gather data together before turning it into actionable insights is a long and arduous process, yesterday’s story. Nowadays, we need real time Self-service insights and analytics to keep up with trends and market fluctuations that tend to happen in the blink of an eye.
But how do we achieve it? There are many analysis solutions to choose from in the market, and it can be difficult to make the right decision. Our focus today will be on two popular elements, namely: embedded and standalone analytics solutions. The main difference between the two is that the built-in analytics are built into an app or some other piece of software. In contrast, standalone analytics are offered separately and often require third party tools/processes to access them.
At To-Increase, we provide Business Analytics Solutions It can be embedded in Microsoft Dynamics 365 F & SCM, Power Apps, MS Teams, and Microsoft CE. These solutions cater to various industries, covering different business functions to achieve improved business results.
In this blog, we will compare the two analytical models by understanding in detail what are both embedded and standalone, along with the pros and cons that drive them, so that you are better equipped with the knowledge to decide which is right for you.
What are embedded analytics?
As the name suggests, the included analytics software allows data to be analyzed within a single application and becomes a part of the normal business workflow, eliminating the need to switch to a separate application. It is used extensively for section-specific insights. As an example, let’s consider the context of the analytics built into the sales function. Sales teams need to understand win rate, total revenue, segmentation of pipelines, etc., to keep track of numbers on their chances – with built in analytics; They can have all of these ideas in one place.
Embedded Analytics was developed with the lack of accessibility and integration between users and data in mind in the first place. Allows easy access and implementation of data management, visualization, and task reporting within the solution, providing better usability for business users. If we rely on numbers, It’s better to stay with one app, than switch to a standalone app.
The future of embedded analytics, according to You’ll focus on data-centric awareness and training to help users better understand what’s happening in their business, interact with data directly, and create an effective data strategy. You can expect a rise in the data applications market, which will serve as a repository for knowledge sharing and easy access. A token-less or low-code citizen developer approach with easy-to-use self-service packaging is where it stands. For example, existing SaaS products, such as Salesforce, And And others, come with easy reporting of structures.
What are independent analytics?
Independent analytics tools collect data from multiple sources to solve complex problems. Let’s take ROI on decisions as an example. In this case, there is a need to carefully consider the various aspects at multiple levels, such as internal costs, external costs and the division of revenue by different categories, among others. Data points are in different systems, thus standard analytics and a business intelligence tool is essential to get the insights. Moreover, it also allows you to view data from other relevant sources.
traditional style business intelligence Model, independent analytics can be accessed on a separate platform or application. The point of integration occurs between the main data generation application and the analytics application. A typical example of this And Which requires a special login to access data and insights, while the data generation product itself does not have a business user interface.
Using independent analytics, different systems, diverse data models, and complex logic make standard business analysis and analysis tools for organizations essential to link business value across domains together. Further, the growth in buildable data and analytics is valued with the goal of providing a flexible, easy-to-use, and easy-to-use experience, which can help connect data insights to actions/business goals using elements from different solutions. This enhances cooperation and performance in the organisation.
Compare the two analytic models
Now that we understand what each analytics model is, let’s look at the advantages and disadvantages that differentiate embedded analytics versus standalone analytics.
Benefits of an embedded analytics solution
One of the main strengths of the built-in analytics tools is seamless integration with applications, processes, and software for your daily workflow. It provides quick access to data analysis and visualization, providing up-to-date insights in a simple way, accelerating the entire flow of analytics across the enterprise.
Some of the additional benefits of built-in analytics are:
- Provides dashboards based on the features of your application
- Allows easy customization of actions based on users’ needs
- It easily integrates with other business features, such as web pages, commercial software, portals, etc.
- Provides more control over data security, especially when dealing with sensitive data
Embedded Analytics Solution Limits
Embedded analytics are not without their share of concerns. The analytics model is not very user friendly, may require technical knowledge or resources to some extent, and usually involves more budgetary commitment when it comes to implementation. Some other limitations of the built-in analytics:
- It is limited to one application, with no possibility to manage any supporting functions outside of it
- Limited customization is allowed due to pre-set configurations, which may not work for everyone
- SaaS or PaaS Accredited programs from an ability perspective
Benefits of an independent analytics solution
Independent analytics can be effective for organizations that have the time and resources to turn their big, broad data into actionable insights. This can allow companies to improve their performance by enabling better decisions. Some aspects that tend to favor independent analyzes are:
- Combines data from different sources in a compatible format
- Comprehensive features to help with comprehensive data management
- Helps simplify complex data analysis
- Allows mass customization in light of flexible core frameworks
Limitations of an independent analytics solution
From a user’s point of view, independent analytics provide a fragmented experience with users having to work with separate apps, each with a different look, feel, and way of operating. Here are some of the limitations that standalone analytics solutions have:
- It takes effort to turn data into relevant insights
- Application and analytics in different environments
- It takes longer when it comes to analytics
- Difficult to maintain and has additional overhead costs
- Requires technical knowledge to navigate
What is the best option for you?
Now that you know the strengths and limitations that each analytical model offers, you can get a better idea of what works for you. When choosing a data analysis solution, there is no right or wrong, and it is entirely a business decision, given your current situation. A good place to start can be identifying factors such as business goals, scalability, budget, and integration with existing systems, available resources, and data sources.
However, understanding the need for the hour can help you stay ahead of your game and prepare. Regardless of the industry, users are looking for easy access to high-quality, real-time insights to help them make confident and informed decisions. For this reason, there is an increase in built-in apps and self-service analytics, which puts the power in the hands of users. At the same time, organizations are increasingly embracing the best apps, which means plenty of apps to deal with. Extracting insights from these applications needs intelligent analytics solutions to integrate and create data models, craft repeatable logic, and create powerful visualizations.
To keep pace with the times, the first step will be to plan your data-driven journey from the start, and with the right analytics and business intelligence foundations to succeed. We’ve put together an eBook that helps you understand the need to be data-driven and how new age analytics and business intelligence tools can help you.
Want to dive into the world of data-driven decision making? Get a copy of And Which gives you insights into the right steps to successfully implement analytics in your organization.