Imagine if you could put all of your data, visuals, and insights anywhere you wanted and make it handy for your team and your end-users. Well, this is possible with “embedded analytics,” allowing your data to leave the confines and demonstrate its worth in new contexts. It is like collecting different forms of data like charts, dashboards, and graphs from different software and apps and combining them to understand the user’s behavior. You can then make positive business decisions that are both effective and efficient. But, the question is: What is this data, and Where does it reside? It is application data, or, say, data a business wants to track in their user base. This information is stocked in the application database or as application traces in the software platform. Now, What are the traces? Traces are the track/log of each request coming and going out of the application. We may not even understand we are using embedded analytics in the business process because it is so common in our daily lives. Every dashboard and visualization is built into another application or web portal. We see it all as one. The term “embedded analytics” is now more familiar to you. If not, let’s dive into it, learn more about it, and see how to reap its benefits.
What is embedded analytics, and how did it start?
Data visualization used to be limited to Microsoft Excel or similar spreadsheets, which were small, generic, and easy to use. Big data in enterprises today has flipped this landscape. Big data is like mine. It stores customer organization data in the same way that gold is stored in treasure chests. Embedded Analytics pulls data from existing apps and platforms. Then the data can be viewed by end-users in real-time through reports and dashboards in the embedded analytics software. This study assists the end-user in detecting, reducing, and minimizing errors when making business decisions. Software companies aren’t the only ones that can benefit from embedded analytics. This technology is not limited to software development. Many enterprises rely on embedded analytics for managing teams and processes. Embedded analytics can give data to clients, partners, or website visitors. Real-time progress updates will increase your audience’s faith in your organization.
What is the purpose of using embedded analytics?
Embedded analytics is popular among users because it allows them to collect data from the apps they use every day. When data is automatically incorporated into a user’s workflow, they are more likely to utilize information instead of instinct to make business decisions. It also minimizes friction by eliminating the need to log in to a different platform. Teams become more self-sufficient and empowered when they need knowledge in their everyday apps. Conclusively, an embedded analytics platform improves user productivity. It helps people address high-level business challenges by using data and analytics. Instead of standard business intelligence, the system focuses on application issues.
How is embedded analytics different from BI software?
Embedded analytics is a method of utilizing business intelligence. Embedded analytics is the practice of bringing a dashboard out of a BI platform and placing it where you need it. A distinctive definition of business intelligence is “an infrastructure for gathering, understanding, and visualizing business data.” Embedded analytics is a unit of a BI infrastructure that helps users understand and visualize business data. Embedded analytics, on the other hand, makes this data available outside of traditional BI systems. Breaking free from the conventional BI mindset is crucial because better business decisions can (and should) be made anywhere. It does not always work because business intelligence does not always match the user’s process and circumstances. Because embedded analytics provides real-time data, companies are turning to it to solve this problem. Users of business intelligence software must switch between programs for information and decisions. Embedded analytics software blends intelligence and applications.
What Are the Benefits of Embedded Analytics Software?
Reduce Errors
Embedded analytics aid in the reduction of errors. When all data is available alongside the user’s daily routine apps, the risk of user error that can occur while viewing and interpreting data in one app and then applying what they’ve learned in another is significantly reduced.
Increase Efficiency
Embedded analytics increases efficiency because you will get all the analytics insights in one place. Besides, it brings the point of action into the workflow (no more switching between apps). It allows a business owner and their team to solve a problem or seize an opportunity without having to leave the application and disrupt their workflow.
User-Friendly Interface
The complex BI system could only be accessed by highly experienced IT people. But self-service functionality in embedded analytics makes handling the data a piece of cake. Now it is easier for both the company and the user to use these services at their ease. Furthermore, it is designed for people. A self-service solution will give your users the tools they need to use your analytics platform effectively without relying on IT.
Customize as per your needs
Embedded analytics can be configured end-to-end so that users can control the data more. It includes a dashboard and report builder that can be changed to fit the needs of new and experienced users, report templates with already chosen data sources, and more. The best-embedded analytics systems provide different levels of access. It allows the business to easily manage which users have how much access to the site.
Device-Friendly
The decentralization of business is becoming more common. Many companies have employees from all over the world. These employees need embedded analytics software. The analytics software built into a company should give users access to business-critical data, analyses, and dashboards, and users worldwide need business software on various devices. Embedded analytics software can be used on mobile devices and is accessible to anyone on the network who has access to the internet. It also comes with the necessary tools, capabilities, and security.
What features should good Embedded Analytics Software have?
Technical and customer support
Any embedded analytics software must offer practical solutions to the customer’s issues. Your software provider should be dependable and genuinely interested in your company’s success. The provider should analyze all the issues and discrepancies in the platform regularly according to the feedback shared by the end users. They should also provide frequent upgrades that solve recurring problems and enhance performance. These upgrades will benefit the end user’s performance. Your embedded analytics software vendor should offer outstanding customer service and technical support. Customers still favor companies with dependable customer service, no matter how simple the software is. The vendor should conduct engaging training sessions and demonstrations. It not only increases user confidence but also helps customers determine whether the system will meet their specific needs or not.
Data Security
Organizations rely on their data to gain insights, so they must keep it safe. Businesses must prioritize data security because it can give them a competitive advantage. It safeguards sensitive information. Users can be granted permission in various ways in embedded analytics, ensuring report security in almost any situation. For large businesses with a wide range of user needs and wants, embedded analytics offer fine-grained control down to the level of each report element. It lets you decide which parts of reports can be accessed by whom.
White label analytics
The term “white labeling” in an analytics platform describes the process of integrating a third-party data analytics solution into your workflow. Hence, It seamlessly matches the look and feels of the application used daily by the users. When users are required to switch between multiple portals to access analytics without white-labeling, the user experience is somewhat fragmented. Analytics are seamlessly integrated with the user-friendly interface in a white-labeled product. Ultimately, higher white-label software adoption rates result from improved customer satisfaction.
Interactive Dashboards and Reports
Graphical representations and data visualizations aid people in comprehending and remembering large amounts of data clearly and understandably. It lets them make good decisions. Decisions can be made quickly and confidently because it is simple to read and evaluate. Most people learn better when they can see what they are learning, so integrated analytics software with a robust visualization library helps users thoroughly explain complex information. Let’s now look at the best-embedded analytics tools.
Zoho
Zoho Analytics is a powerful tool for obtaining business intelligence. It collects and organizes data in such a way that you can get elaborated and actionable insights. Reports in Zoho Analytics can be shared with other users or published for stakeholders to see directly. In addition to it, Zoho provides endless features like automatically identifying data types and giving suggestions for joining datasets. It lets you create custom data types to define invalid data.
Looker
Looker embedded analytics is redefining business intelligence for the 21st century. It is a part of Google Cloud that helps companies drive growth with embedded analytics by creating apps quickly and connecting workflows. It leverages the latest and quickest analytic databases to deliver real-time findings. Whether you are into fitness or products, it is customizable to your business.
Sisense
Sisense excels at data modeling and dashboard design. This program allows advanced segmentation, forecasting, and regression. It is a 360-degree solution for businesses with an intuitive and appealing user interface. Even someone inexperienced with graphics, charts, and dashboards can easily learn the system. The product’s features are useful for specialists as well as beginners. It allows white-label applications to maintain the brand experience and uses AI and ML to deliver a seamless data experience to customers.
Conclusion
An organization’s most valuable assets are data and analytics, which are the basis for data-driven decision-making. With embedded analytics, users can easily access all data and reports in the same workflow, using data to overcome obstacles in the dynamic environment and make effective data-driven decisions. Implementing embedded analytics can help websites, portals, applications, and even finished products get more use out of the data they gather. Because embedded analytics is so simple to use, more and more people are using them and getting involved in developing them. Businesses that have adopted this strategy can produce more precise insights because embedding analytics acts as a catalyst for group problem-solving. You may now look at some of the best BI tools.
