Embedded Analytics Software: Everything You Need to Know

Overview: Embedded Analytics Software has gained popularity over the years, as it helps businesses gain insights, make better decisions and drive growth. In this article, we will take a closer look at what embedded analytics is, who uses it, its benefits, features, and how you can use it as a competitive advantage. Additionally, we will explore five of the most relevant software products on the market today, their unique features and limitations.

Who Uses Embedded Analytics Software?

Businesses across various industries utilize embedded analytics to help them process and analyze data to make strategic business decisions. Companies of various sizes, from Small and Medium Enterprises (SMEs) to large enterprises, can utilize embedded analytics to manage and streamline their data management processes. Industries that currently use embedded analytics include healthcare, finance, e-commerce, human resources, and many others.

Benefits of Embedded Analytics Software

Better decision-making – Embedded analytics software provides real-time, accurate data that enables management to make informed decisions, fast.

Increased productivity – Embedded analytics tools can save businesses time that would have been spent on manual data entry and analysis.

Cost-effective – It saves companies money that would have been expended on the cost of manually processing, analyzing, and maintaining records.

Timely insights – Embedded analytics software provides real-time data insights that help identify trends and market insights faster than other traditional data analysis methods.

Features of Embedded Analytics Software

1. Predefined dashboard templates: Embedded analytics software comes with predefined dashboard templates that offer various features and customization options. These templates provide fast and easy access to information and data visualization tools.
2. Data Integration: Embedded analytics software enables businesses to combine data from various sources, streamlining the process and creating a single source of information.
3. Predictive analytics: Embedded analytics software uses predict analytics to forecast future trends.
4. Customizable charts and graphs: This feature allows businesses to customize charts and graphs that they want to display on their dashboards. This customizability helps add branding to reports and presentations.
5. Ad-hoc reporting: Embedded analytics software provides ad-hoc reporting capabilities to help businesses create various reports when needed, on the fly.

Five Examples of Relevant Embedded Analytics Software

1. (Sisense.com): This software boasts of offering easy to use tools that can change a company’s revenue by 10%. Its features include the ability to connect to any data source, beautiful data visualization and a drag and drop interface. Limitations include a steep learning curve that can deter some users.
2. (Tableau.com): Tableau is a popular embedded analytics software used by businesses of different sizes across various industries. Its features include dynamic dashboards, easy data blending, and superb data visualization. Its learning curve can be too steep for some new users, and it is on the expensive side.
3. (Chartio.com): Chartio provides businesses with powerful business intelligence that can increases their revenue. It comes with a powerful drag-and-drop interface, data pipeline tools, and allows for collaboration. Its limitation is that different users can’t interact with one dashboard at the same time.
4. (QlikView.com): QlikView is known for its associative analytics pioneered by their software. This feature provides for the freedom of data exploration by letting users analyze data from multiple dimensions without pre-aggregated queries. Its drawbacks include a limited amount of data that can be analysed and its high cost.
5. (GoodData.com): GoodData promises businesses a cloud-based Analytics platform that can democratize data across the organization to enable smarter decision-making. Its limitations include the lack of Machine Learning functionality and an inability to use SQL statements within its data modelling process.

How To Use Embedded Analytics Software

Using embedded analytics software can be easy or difficult, depending on the platform chosen. Typically, the following steps are taken:

1. Establish Goals: Define what you want to achieve with the data analysis and the insights you expect from the software.
2. Choose a Tool: Consider the features, pricing, and additional services of each embedded analytics software provider and choose one that suits your needs best.
3. Configuration: Connect your data sources to the software, then configure your dashboards, reports, and other display elements using the tool’s features.
4. Training: Train your team on the use of the chosen embedded analytics software, making sure that everyone is familiar with its features and how to use it for better decision making.
5. Review and Iterate: Review the results of your embedded analytics use and iterate on the goals, configuration, or data sources as needed to continually improve performance.

Conclusion

Embedded Analytics Software has become a necessary tool for businesses across various industries, with robust features that enable businesses to gain better insights and make informed decisions. By providing timely, accurate, and easily customizable data insights, businesses can save money and drive growth. With the rise of various software products, businesses can take advantage of these tools to gain a competitive advantage. Understanding how embedded analytics software works and how to use it effectively is critical for businesses, regardless of their size, to keep up with the fast-paced data-driven market.