Data Visualization Trends In 2022

Data Visualization is the most enthusiastic subject among businesses nowadays. Today, companies are sitting on mountains of data that have a goldmine of knowledge and information. The information, once properly comprehended, can be exceptionally useful for them to make better, data-driven decisions.

There are a number of data visualization trends and as their value increases, the number of companies that are turning to the art of data visualization will keep growing.

The healthcare industry is equally influenced by the processes of data visualization. Data visualization can be understood as a process of representing data and information in visual forms such as graphs, charts and diagrams.

In the healthcare setting, professionals turn to data visualization to communicate patient information and other vital resources. This enables healthcare professionals to display critical information in the form of graphs, charts, pictorials and other visuals. Through this system, all the data is passed and processed quickly and efficiently.

In this article, we will cover data visualization trends in the healthcare industry.

Tools For Visualizing Health Data

Data visualization also takes the form of a “dashboard,” which can also be understood as a series of interactive reports that enable decision-makers to easily analyze metrics or scan patterns. Several types of dashboards can be used in health care organizations. Some of these are briefly explained below.

  • Operational Dashboards

Just as the name suggests, an operational dashboard is designed to display the everyday, routine operations of the hospital. It is a monitoring tool used to track the constantly evolving processes of the hospital and to monitor the current performance of key metrics.

The data is updated quite regularly, sometimes even on a minute-by-minute basis, making the working very quick and efficient.

It gives out real-time information about whatever is happening in the hospital at the current moment. All this information and data regarding the routine operations can be seen and reviewed. From base-level information to hospital administration, all the data and information can be checked and reviewed throughout the day. 

  • Strategic Dashboards

A strategic dashboard is a monitoring tool that is commonly used by executives to track the status of main performance indicators. The data of the strategic dashboard is also updated on a recurring basis but at less regular intervals than an organizational dashboard.

Just as operational dashboards are used for routine activities, strategic dashboards are especially created to see and review trends and changes in the key indicators.

It also provides collective information for quick and easy viewing and reviewing. For instance, a strategic dashboard enables healthcare professionals to review various changes in different items over the months. This can be viewed with regard to different strategies and events. 

  • Analytical Dashboard

An analytical dashboard is a reporting tool used to analyze large volumes of information to enable users to examine trends, predict results, and discover insights. Within business intelligence tools, the use of analytical dashboards is more common because they are typically developed and designed by data analysts. The analytical dashboards work for analysis and bringing similar information together.

It includes various data visualization tools for extrapolating or concluding the findings from a large dataset. The analytical dashboard is a mix of various tools and helps in further reviewing and gathering information. This dashboard is efficient enough to comprehend and understand relevant patterns from a wide set of patient medical records which in turn not just makes things quick and easy but also reduces efforts. 

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10 Top Data Visualization Tools To Help You Handle Data

1. Tableau

Tableau Homepage Screenshot | Mindbowser

Tableau is a data visualization software that is among the best interactive data visualization tool. Tableau helps in making big data small, and small data meaningful, understandable and actionable.

Tableau makes it easy to acquire insights from dashboards and worksheets as it enables to development and design of interactive maps, graphs, charts and so on, which are then updated in the dashboard for the users to see and make sense of the data.

It offers easy drag and drop features and helps users to see the data in real-time. Data sharing is also easy with the help of tableau servers and can be shared on the web.

2. Qlik Sense

Quilk Sense Screenshot | Mindbowser

Qlik sense is a complete data analytics solution that helps in tackling even the most complex data analytics problems. It is a well-known data visualization software that is widely used offers a lot of features and flexibility to its users and also allows them to link data from various sources for better analytics.

It also has an easy-to-use interface and comes close to tableau when compared with each other.

3. Microsoft Power BI

Microsoft BI Screenshot | Mindbowser

Power BI primary focus is business intelligence. The tool gives users the ability to access on-premises and in-cloud data. The free tier offers upto 1GB of data usage and the users can make reports and share them on the dashboards.

The paid version has some added features that let users fully interact with the data and share queries via the data catalog. 

4. Domo

Domo Homepage Screenshot | Mindbowser

Domo is considered one of the best options for companies who are looking for independent and self-service visualization and analytics solutions. It is easy to use and can also be viewed on mobile devices which makes it a go-to choice for companies who collaborate and communicate with their shareholders and want to provide all the necessary information and updates.

It also includes some popular data sources like Amazon Web Services (AWS), Google Analytics and more.

5. Sisense

Sisense Homepage Screenshot | Mindbowser

Sisense is a powerful visual report generator and offers an easy-to-use interface to its users. It also allows users to collect and analyze high-volume data and generate smart analytics reports. It also enables the collection of data from multiple sources and stores them in a single source which makes it easy to analyze and make sense of the available data. 

Sisense is used by some prominent organizations like NASA, Merck, eBay, ESPN and SONY.

6. SAP Lumira

SAP Lumira Homepage Screenshot | Mindbowser

Formerly known as Visual Intelligence, SAP Lumira is a self-service visualization tool that enables business users to create and visualize stories on datasets.

One of the main features of SAP Lumira is that it enables users to connect to multiple data sources both online and offline and is available for individuals, small businesses, and big enterprises.

7. TIBCO Spotfire

Tibco Homepage Screenshot | Mindbowser

TIBCO Spotfire is a smart enterprise-class data visualization platform that offers an AI-based engine that helps in reducing friction in the discovery of data.

It allows the user to quickly understand and make sense of the data and can be used on desktop, cloud and platform editions. It is used by some of the top organizations like Procter and Gamble, Cisco, NetApp, and Shell.

8. MicroStrategy

Microstrategy Homepage Screenshot | Mindbowser

One of the great features of MicroStrategy is that it not only supports data visualization but also supports data mining. It also offers a ton of other features like interactive dashboards, highly formatted reports, scorecards, and automated report distribution.

It is great for individual users and offers a user-friendly interface and quick downloads and installations. It can also be connected with cloud-based data sources and personal spreadsheets and support both mobile and web apps.

9. ThoughtSpot

Thoughtspot Homepage Screenshot | Mindbowser

ThoughtSpot is an AI-driven analytics tool that can be used by anyone to make data-oriented searches and helps in getting quick and reliable insights.

It is more like a search engine than a data visualization tool and allows users to do guided searches throughout the company data. ThoughSpot is often used by financial service professionals who need quick insights to make data-oriented decisions.

10. Looker

Looker Homepage Screenshot | Mindbowser

Looker is a browser-based data visualization solution that offers a user-friendly environment and offers dashboard collaboration. It also allows users to create custom visualizations and the ability to share reports and analytics easily. It is also used by some of the leading companies like Amazon, The Economist, IBM, Spotify, etc.

Data Visualization Trends

Keep on reading if you want to understand some of the data visualization trends to look out for in the coming years. 

  • Cloud Computing

Cloud computing provides two-fold benefits to the healthcare industry. It has proved to be helpful for both healthcare providers and patients alike. Looking at the corporate sector, cloud computing has proven to be effective for reducing operating costs while enabling providers to deliver high-quality, personalized treatment.

Patients who are increasingly used to the instant delivery of services are now able to take advantage of the same promptness from the health sector. By allowing them to manage their own health records, Cloud also amplifies patient interaction with their own health plans, resulting in better patient results. 

It further breaks down location barriers and provides remote accessibility for improved performance and experience. During the prevention, treatment and recovery process, cloud-based telehealth systems and applications facilitate easy sharing of health data, enhance accessibility and provide patients with healthcare coverage.

Having the data of the patient in the cloud also facilitates interoperability between the pharmaceuticals, insurance, and payments of the different segments of the healthcare industry.

This facilitates the smooth transfer of data between the various stakeholders, thus speeding up the delivery of healthcare and introducing quality in the process.

Combined with rapidly emerging technology such as Big Data analytics, artificial intelligence, and the medical internet, cloud computing enhances efficiencies and opens up multiple opportunities to streamline the delivery of healthcare. It improves the availability of services, enhances interoperability and lowers costs.

  • Predictive Analysis

In order to make predictions about the future or the unknown, predictive analytics is the method of learning from historical data. Predictive analytics would allow the right choices to be made for health care, enabling care to be customized to each person.

Predictive analytics approximate the likelihood of a prediction based on observations in the historical data rather than only providing information from past events to an end-user, a significant step forward for many personalized health organizations.

This helps physicians, financial analysts, and administrative staff to get a “head up” on future situations before they happen, and make decisions on how to proceed with forward-thinking.

In emergency treatment, surgery and intensive care, the importance of predictive modeling in healthcare can easily be observed, where a patient’s outcome is directly linked to the rapid response and acute decision-making of the care provider when or if the condition takes an unexpected turn for the worse.

Leveraging predictive analytics will alter the dynamics of power between patients and doctors. For fear of losing decision-making power or liability issues, if doctors do not readily implement predictive analytics, then patients will go straight to the algorithms to find their own answers. But the accuracy and reliability of these recommendations need to be trusted by consumers.

  • Strategy And Integration

Strategy and integration compare various types of data and create and deliver comprehensive, patient-specific care plans simpler for the care providers. A provider may, for example, display the medical history of a patient, and then compare it with other patients with similar conditions against the projected patterns and trajectories.

The reviews of the data visualization effectively check and verify various data points and apply information gained to make improved patient care decisions. 

  • Data Viz Is More Social

With the growing trend of social media in the past decade, data researchers have shifted to making data visualization more social, presentable, visually appealing, and easily understandable.

This trend is becoming more and more popular and researchers are adopting it pretty quickly, using instances like 3D animations, GIFs, and Youtube Stories.

  • Data Democratization

With the introduction of new data analysis platforms, the data that was once considered difficult to understand and required input from scientists and technical teams has now completely changed with the introduction of no-code analysis platforms.

These platforms not only process the data but also show data in an easy-to-understand manner. This trend will not only help teams to make data-driven decisions without any technical inputs but also increase the usage of data in decision-making. 

  • Data Storytelling

Storytelling is among the most important and integral parts of the business process. It not only makes the customer feel connected but also helps in building a relationship with them.

The idea of visualizers becoming storytellers was out there a few years ago, but in the past year, it has gained a lot of traction. Visualization of data is more of storytelling nowadays and is being widely adopted by many organizations. 

  • Data Journalism Is Going Mainstream

It can’t be argued that data in charts, diagrams, and dashboards are easy to showcase and explain, as compared to long paragraphs and reports.

Over the years this trend has taken over the top media organizations and more and more of them are using this summarized data to show it to their viewers as it not only takes less space but is easy to explain and understand. It is already very popular in the mainstream media and will gain more popularity in the coming years.

  • Artificial Intelligence

Since the introduction of AI in the data visualization industry, not only has there been a transformation in the way we look at data but also there has been the ease with which data can be consumed.

Big companies have massive data that can be overwhelming for them, and AI solves this problem by helping them discover what data they should be looking at. Over the coming years, more and more data will be available and the use of AI will make it easy to get a sense of the data.

  • Mobile-Friendly Data

Mobile devices need no introduction, as we have all been using them for almost all of our tasks. Since mobile experiences matter most for businesses and for their customers, engaging in providing mobile-friendly data will be among the key trends in the coming years.

Many data visualization enterprises have already incorporated features in their tools that can be used on mobile devices, and more and more organizations are adopting this trend rapidly.

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In this sophisticated digital age, data visualizations have become a critical part of the business world and an ever-increasing part of managing our everyday lives!

In addition, data visualization trends and data analysis will also assist in preventing any fraud, excessive expenses, or waste and misuse of funds. Seeing that the healthcare sector is a big aspect of life, those who commit some fraud in terms of their benefits, bills, etc. are likely to be, and there is always the risk of wasting too much on a single field or event. What helps with data analysis is to prevent certain circumstances so that the industry can work properly and have sufficient facilities.

Also, it’s important to have in mind that it’s a tedious job to record and interpret all medical data, even with the aid of advanced technologies, and due to the various types of data available, there will still be a mistake or inadequacy.

Sandeep Natoo

Head Of Emerging Trend

Sandeep is a highly vigorous Machine learning expert with over 12+ work of experience with developing heterogeneous systems in the IT sector. He is an expert in building Java integrated web applications and Python data analysis stack. He has been known for translating complex datasets into meaningful insights, and his passion lies in interpreting the data and providing valuable prediction with a good eye for detail. He is highly optimistic and avid nature, for various challenges is his major strength.

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