Business intelligence (BI) has become an increasingly popular term in recent years. Businesses use BI to analyze their sales and marketing, customer satisfaction, and more to help them make better decisions and improve their businesses overall.
While many organizations understand the importance of business intelligence, it can be difficult to know where to start when you’re new to the idea of BI or just want to learn more about it.
Thankfully, that’s where visualization comes in! With good visualization business intelligence, you can gain insights from your data much faster than you would otherwise be able to and take your business to the next level with minimal effort.
Visualization in business intelligence (BI) allows business users to see patterns and anomalies in data sets that are too big to view in traditional spreadsheet models, or that contain so much information that the average person cannot make sense of it without the help of technology and trained professionals.
Here is what you need to know about visualization business intelligence.
What is Visualization Business Intelligence?
The technique of transforming raw data (text, numbers, or symbols) into a graphic representation is known as data visualisation.
The data is represented with a specific goal in mind: to demonstrate logical unit connections and describe inclinations, trends, and patterns.
Visualization may be done in a variety of formats depending on the type of logical link and the data itself.
So, to put it plainly, any analytical report will include instances of data interpretations such as pie charts, comparison bars, demographic maps, and so on.
Visuals are often generated by hand using related software, such as PowerPoint or Photoshop. However, its primary use is in the field of analytics. As a result, data visualisation has become a typical method of presenting information to consumers via the BI interface (data representation tool).
Types of Data Visualization in Business
Data visualisation in a commercial context generally consists of a number of charts and graphs.
These are incorporated into dashboards and other process tools, displayed on monitors or bulletin boards in common areas, and included into boardroom presentations.
The following are some examples of the many sorts of visuals used in data analytics and visualisation.
Graphs and Charts
When it comes to data visualisation storytelling, charts and graphs are usually the first tools that come to mind.
A line chart may explain the overall story of data patterns over time faster than a narrative or figures, while a bar chart can swiftly compare counts or performance across categories.
However, lines and bars aren’t the only graphical tools available in data analytics and BI reporting.
Here are some more data visualisation charts and graphs to consider:
- Gantt Charts
Gantt charts are useful for quickly visualising projects or processes across time. They’re an excellent method to evaluate if a complicated timetable is feasible as anticipated, find out where one process may intersect or overlap with another, and predict (or notice when) processes are running behind.
- Pie Charts
Pie charts are a simple approach to show what components are at work in a process. If you need to know if each element of the whole is pulling its weight, or if you want to identify what factors are most essential in a process or outcome, many types of pie charts are useful.
Histograms demonstrate how your data is distributed. Histograms are statistical tools that aid in the estimation of probabilities. They can, however, immediately indicate if a process is hovering around the proper mean or whether outliers are skewing data or outcomes, when used as a visualisation narrative tool.
- Control Charts
Control charts are a form of line or dot chart that shows how a process evolves over time. These are statistical process control techniques that can rapidly tell you whether or not a process is “under control.” Control charts are frequently included in analytical dashboards because they may be used to identify whether a process is operating as intended or whether some manual intervention is necessary to enhance or resolve an issue.
Tables are often the ideal approach to show information when you want to supplement your graphics with a more detailed look at the facts behind them.
This is largely due to the fact that everyone understands how to read a table’s column and row structure.
When you know that your stakeholders would want to view more detailed data, you may add tables in your data visualisation reports.
You may also use them to point out how one piece of data is skewing the conclusions derived from a chart.
Importance of Data Visualization in Business Intelligence
Data visualization in business intelligence makes it easier to spot trends and see relationships between different types of data.
We often hear about someone making a decision with incomplete or even inaccurate information because they lacked key context for what was actually happening within their business. But data visualization can help you make informed decisions, which can ultimately save you time and money as your company grows.
To be more efficient with data, visualisation needs to play a part. The added benefit of data visualisation is that it can provide additional clarity into complex data.
With large datasets and diverse sources of information, an application or report can get confusing.
Visually representing a dataset makes comprehension much easier for users and presents overall benefits for a business intelligence program. It also helps provide users with quicker access to information; for example, if you want to compare sales from different months over time, data visualisation tools allow you to view both sets of information on one chart instead of forcing you to switch between multiple reports or applications.
When users have improved access to accurate information and real-time results, they can make faster and better-informed decisions that have an immediate impact on business performance.
Data visualization is important because it allows businesses to glean insights from data in new ways.
Data visualization involves using charts, graphs, infographics and other methods to display data visually rather than as raw numbers.
Data visualization has been around since before computers were invented but has become increasingly popular as technology has advanced.
Visualization Business Intelligence in Different Sectors
Data visualization is an effective means of understanding how things are performing for a variety of sectors and industries. Here are some ways data visualization is used in businesses.
Choropleth maps are commonly used by healthcare practitioners to illustrate crucial health data.
A choropleth map shows split geographical areas or regions that have been allocated a colour based on a numerical value.
Professionals can use choropleth maps to observe how a variable, such as the mortality rate of heart disease, evolves over time in different areas.
When deciding whether to buy or sell an asset, finance professionals must keep track of the performance of their investment selections.
Candlestick charts are used as trading tools, and they assist financial professionals in analysing price movements over time by providing vital information about securities, derivatives, currencies, stocks, bonds, and commodities.
Data analysts and finance experts can spot patterns by examining how prices have changed over time.
Visualization technologies may be used by shipping corporations to discover the optimal worldwide shipping routes.
According to research conducted by the media firm Magna, 50% of all worldwide advertising spending would be spent online by 2020.
As a result, marketing teams must pay close attention to their online traffic sources and the money generated by their web domains.
It’s simple to examine traffic trends over time as a result of marketing activities thanks to data visualisation.
Visualization Business Intelligence with Ascend Analytics
Ascend Analytics provides a full range of data analytics and predictive analytics consulting services. It allows for real-time data streaming from a number of sources and makes it easier to extract key insights from high-quality data.
Ascend Analytics was founded with the goal of providing organisations with actionable analytics to help them develop, regardless of their size, status, or industry.
To visualise and grow innovative ideas alongside your firm, Ascend Analytics brings together strategists, data analysts, data engineers, developers, data scientists, and machine learning professionals. The final architecture includes all of the necessary enabling technology.
Ascend Analytics is a user-friendly interactive dashboard that gives you access to critical data, measurements, and KPIs to help you make better business decisions.