by Hema | Sep 22, 2020 | Device manager, IoT Platform | 0 comments
Reports have a huge impact on any business, or industry. Reports communicate information & explore a series of trends that any part of the business / industry has caused or accelerated. The goal of reporting is to convey / dispatch a specific data with an intelligible intend to a target audience. Despite of size or industry, reports are beneficial & crucial tool for any enterprise. By facilitating the tracking & analysis of the functioning and entire robustness/well-being of the business, reports help in pin pointing fields for refinement and opportunities for growth. In case of business, reports can be used to keep an eye on betterment and growth, point out trends or any deformities that may need additional inquiry that is important business KPIs. In case of industries, reports can be used to track production KPIs such as OEE. But, the reports need to be conveyed as a complete bundle which is engaging & easy to understand. The numbers in rows & columns will not provide actionable insights since it is likely to be much boring. Here comes the data visualization. Data visualization makes such reports intelligible & easy to understand for everyone, regardless of its comfortableness with data analysis.
Among the most basic ways, the effective method to lend a hand to people who deals with data overload is to visualize it. In a very simple term, this is all about presenting data out as a chart, laying it on a graph and also using data to turn out a responsive picture. By mapping out data visually, it does not limit its function only to be trouble-free to understand necessary information, it is also quite simple to identify notable trends, key patterns and captivating relationships between data which looks challenging to discover. Though, the numbers are still important, the data without visualization or visual effects will not create an impact & also it’s truly a disservice to a decision maker. Hence, to bring those numbers to life in a compelling way, it is vital to implement data visualization into reports.
When we think of adding some visual effects into our data, as likely as not our mind right away tends to use line graph or pie chart. Though these two graphs are commonly used to visualize data, the right visualization should be coupled with the right set of information. There are numerous types of visualization methods to display data in effectual and compelling ways. This includes Line Chart, Bar chart, Pie chart, Area chart, Histogram chart etc.
As mentioned earlier in the above paragraph, the right set of data must be paired with right visualization to expect a compelling insight. This is not like throwing numbers into any table or any chart & meaning it as the effective data visualization. It’s not about creating a chart or graph; it’s all about representing the data with the right chart to maximize the grasping power. That is, all the visualization types cannot be used to visualize all types of data reports. Let’s say we want to generate a server room monitoring report that compares room temperatures across standard temperatures over time. How can we speedily and effortlessly identify when there is a high rise of temperature that may cause damage to the systems?
Line chart suits for this. Basically, it’s an effortless way to link discrete data, providing a simple, easy visualization of trends, and how they correlate over a period of time. While such trends could be easily overlooked in line chart or bar chart and will help to visualize the data easily. Comparing information will become easier as it presents data as rise & fall speedily. An application team can track the temperature trend to gain immediate understanding of issues & make quicker decisions. The same way, each data visualization can be applied specific to each business, industry or enterprises.
The major difficulty in reporting that declines the analysis part is picking what kind of graphs to implement. That’s because selecting the incorrect graphical form or directly sticking to the most usual form of data visualization could cause uncertainty with the decision maker & could result in faulty data evaluation. For instance, as mentioned above, in generating server monitoring report, Line chart will be a suitable one. In case of incorporating pie chart, the visuals will not convey the right information to the decision maker creating confusion. This is because, pie chart will be suitable for displaying percentages & not to view trends.
Here’s a precis of some basic type of charts, to know well about how they can be used or implemented.
Line Graph : A line graph discloses trends over time which can often be used to display distinct varieties of data. Line graphs best suits to have rapid data analysis. It is suitable to tell the range quickly, minimum/maximum, & any gaps or clusters, by presenting a good impression of trends & changes. For example, line graphs are mostly used in temperature trend analysis in industries.
Bar Graph : Bar graphs are intelligible, widely used, and can display changes over time which lacks in other graphs showing only a single data set. It has a potential to present data that shows changes over time, helping people to visualize trends. For example, bar graphs can be used in mapping performance of the air conditioner.
Gauge Chart : Gauge charts are predominantly used for differentiating values between the less number of variables. Varied pointers can be used on one gauge or multiple gauges in order to compare data. Gauges are most often used for displaying key performance indicators (KPI). For example, gauges are mainly used as a speedometer to measure the speed of the vehicle over time.
Doughnut Chart : A doughnut chart can be used for easy analysis and reading of the pictorial format. These charts are known to reveal the ratio of ‘part-whole’ where every part represents 100% when gathered together. It displays survey questions or data with a small number of comparing categories. For example, Doughnuts can be suitable for analyzing market trends.
Pie Chart : Pie charts are most commonly used to display percentage or proportional data and each slice of pie represents each category. Hence it much suits when having a categorical data. The use of a pie chart would be to compare areas of growth within a business such as turnover, profit and exposure.
Hence, each type of visualization carries a specific role in Business / Industrial reporting and analysis. To make the reporting more simple, we have added a support of incorporating data visualization types into reports in Bevywise IoT Platform. Bevywise IoT Platform already supports creating three forms of graphs
From now on, graphs or charts which can be more specific to the industry / business use cases can be created with the new support.
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