Visualization and data connectivity are the two most important aspects driving the digital environment today. Building dashboards and reports are now an integral part of almost everybody working in the corporate sector. This includes everything from creating operation reports for different shopping floors to creating financial reports for the top-level executives of an organization. This depicts the importance of data visualization in any organization, no matter the scale or size.
However, data visualization is not very complex today with the rise in cutting-edge solutions such as the SAP Analytics Cloud. There is a lot that can be done with SAP Analytics Cloud in terms of enhancing the data visualization processes of an organization. Therefore, let us take a look at what SAP Analytics Cloud has to offer in terms of data visualization.
But First, What Is SAP Analytics Cloud?
SAP Analytics Cloud is one of the latest cutting-edge Software-as-a-Service (SaaS) developed by SAP that leverages business intelligence (BI) to provide enhanced and accurate analytics functionalities to businesses.
There is a lot that one can do with SAP Analytics Cloud, such as leveraging predictive analytics and machine learning to generate valuable insights helping businesses to make better and calculated decisions in favor of the business. Furthermore, organizations can ensure data-driven forecasts, budgets, and analysis through the modification and creation tools offered by SAP Analytics Cloud.
What Is Data Visualization In SAP Analytics Cloud?
Data visualization in SAP Analytics Cloud is something that we use to understand things in a better way. This feature can empower a business in many different ways as businesses can create visualizations and maps featuring the outcomes of different business strategies.
Furthermore, organizations can combine the data visualization functionalities with SAP Analytics Cloud planning to generate highly accurate insights depicting the overall performance of businesses. This can give a business a competitive edge by making informed business decisions to drive business results.
Things To Keep In Mind For Effective Data Visualization With SAP Analytics Cloud
Data visualization with the enhanced competencies of SAP Analytics Cloud makes it very easier to present data interactively so that the audience understands the story behind the data. Therefore, keep the following pointers in mind when presenting data using SAP Analytics Cloud.
- Understanding The Audience: Whenever we try to convey some message or information to someone else, it becomes very important to understand the target audience. Every graph and chart we present must be designed as per the requirements and expertise of the target audience. This way, one will be able to better their message or information to the audience.
- Defining An Unambiguous Objective: Defining an unambiguous purpose is important because this allows us to focus on the specific elements of the data visualization design in SAP Analytics Cloud. This way, one can deliver solutions to real issues, be it monitoring customer behavior, tracking the performance of the business, or the level of satisfaction derived by the customers. One must prevent using visual elements that do not feature a clear purpose.
- Gathering All Business Requirements Effectively: It is very important to gather all the business requirements and understand them effectively. This will help us find different solutions to fulfill those requirements. Whichever approach one opts for gathering these requirements, it is imperative to ensure that the users remain at the center of the data design and requirements. This way, one can ensure that the user gets what they require from data visualization with SAP Analytics Cloud.
Different Types Of Data Visualizations In SAP Analytics Cloud
SAP Analytics Cloud is the ideal solution that we need to manage our data in an effective manner. Therefore, let us take a look at different types of data visualization offered by SAP Analytics Cloud.
- Stacked Bar Chart: Organizations can use this visualization strategy to display data with a column-shaped rectangle where the length of the column depicts the data value. Generally, these columns are built vertically, but one can even create the horizontally based on their preferences. However, it is important to note that stacked bar charts are not useful when depicting negative values.
- Correlation: Correlation charts are used to depict if the value of a particular indicator and any effect on the other indicator. The cluster bubble and scatterplot diagram are used to represent the relationship between different values. One can even use these bubble charts to show the correlation between three or more indicators.
- Pie Chart: Pie charts are the ideal way to ratio or the part of the absolute value as these charts are great for representing the percentage of different values. However, it is advisable to represent limited data with these charts as too much data can make the chart look cluttered, making it difficult to comprehend.
- Trends: Trends are generally used to demonstrate different changes in data within a certain period of time. One line is used to connect different data points on a graph, making it ideal for showing different trends. Furthermore, one can even use these trend charts to determine how different variables correlate with each other.
- Histogram: Histogram is very similar to bar charts. Many even call it frequency distribution as one can use it to depict the frequency of different value occurrences in a given interval. Just like stacked bar charts, the height of each column in a histogram depicts the value frequency of occurrence in specific ranges.
- Input Controls: This innovative way of representing data enables one to filter data, facilitate comparisons between numbers, and even analyze relationships. One can use input controls for representing information about different features, indicators, and temporal analytics.
- Heat Maps: This is a way to represent data in a dimensional manner where different data and represented and distinguished using different colors. In general, the lines in heat maps are used to define a specified dimension, while the columns are used to define the other dimension. The color on the map can change depending on the value of the indicators.
- Waterfall: This type of data visualization represents alterations in the preliminary values that are combined to represent the total value. The columns in waterfall data visualization are equipped with different colors where one can define both negative and positive values without any hassle.
Conclusion
As we already know, conventional enhancements in data visualization were always made possible through widgets. Appropriate data is then assigned to the widgets, making it a very technical approach to representing data. However, the latest enhancements in SAP Analytics Cloud will enable end-users to visit any web-based platforms, raise relevant business queries, and generate valuable insights whenever required.
Therefore, businesses can now confidently generate quick and accurate results by leveraging the optimized database and ideally developed data model offered by the SAP Analytics Cloud Platform. Therefore, our recommendation to different enterprises would be to consult a good SAP consulting company and leverage the perks of augmented analytics offered by the SAP Analytics Cloud platform.