- August 29, 2020
- Posted by:
- Category: Artificial Intelligence
Data has multiplied exponentially. Every day, companies, governments, and individuals work to better manage their data. Thanks to artificial intelligence and machine learning, the acquisition of valuable data has become one more element in successful strategies.
Every day 2.5quintillion bytes of data is generated worldwide, 90% of all current global data was generated in the previous two years alone. The increasing number of devices connected to the Internet is rapidly increasing data generation.
However, the value of the data that is analyzed most of the time is not high, so, cleaning, debugging, and normalizing data has become 70% of the work of a data scientist. This is mainly due to the complexity of Big Data.
Often times, massive amounts of information must be removed in order to meet a specific need. To do this, the algorithms applied to the data must make sense in their context as well as being precise, interpretable, and generalizable.
Faced with this situation, Data Analytics tools have become essential. Analytics helps companies in the proper functioning of their daily operations and in obtaining potential results and if images are attached to this analysis that simplifies that information, the success will be greater.
Moreover, advanced business intelligence and data visualization tools enable business stakeholders to collect and analyze large volumes of business data, understand complex trends and patterns. In recent years, data visualization is becoming more resourceful and competent to make data analysis useful for non-technical consumers.
What Lies in the Near Future?
Through the use of infographics and dashboards, data visualization is embracing new technologies to enrich itself and enrich consumers. How is data visualization likely to influence the way we interact with data in the near future?
-Virtual and Augmented Reality
With the unprecedented generation of data, conventional desktop monitors or television screens are likely to be insufficient to render 2D and even 3D images. The virtual and augmented reality market is estimated to be worth $170 billion by 2022, so these technologies are likely to shape the future world of data visualization and analytics.
With the use of virtual reality (VR), you can analyze and review data in a 360-degree virtual space. Business presentations are likely to be held in a simulated VR environment, with company executives sitting around watching on a projected screen.
-Easy-to-use Data Display with a Smart Phone
Since the acquisition of the smartphone data visualization company Mapsense by the technology company Apple, data visualization for mobile phones is gaining importance in the industry.
The rapid shift of Internet users from desktop to a smartphone is driving this transformation. Display charts and dashboards are for the smallest screen size of the smartphone.
This future trend is ensuring that more users can now analyze data and get useful information directly from their personal smartphones.
With the increasing availability of data and analytics tools, data-driven journalism by media companies is likely to increase globally. News stories told using an interesting infographic or statistical map is a great example of how to use data visualization as an effective way to tell a story in seconds.
-Increased Variety of Data Sources
Along with the huge volumes of data being generated, large corporations are seeking insights from the growing variety of complex data sources. Among the Big Data success metrics, 69% of the corporate executives ranked variety as the most important factor, followed by data volume (25%).
Although finding data is no longer a challenge for most data analysts, the overall quality of data visualization will depend on the quality of the data that is entered into it. This means that data viewers must evaluate and select the correct data sources for future viewing.
In an age where AI technologies are leading industries and working spheres, there is no question of its impact in the area of data visualization. With traditional dashboards unable to cope with the rise of complex data representation, AI and machine learning combined with data visualization are now redefining the customer experience.
With its natural language skills, AI and machine learning are effective in capturing critical information from business data, thus improving the effectiveness and accuracy of visualized data.
With the massive increase in the volume and variety of data, data visualization technology is evolving at an accelerating rate to meet changing business requirements.
[Prefer Reading: “AI Robots & their Impact on Human Life.”]
-Effective Data Visualization
The human brain is programmed to react better to visual signals. Consequently, visual content is processed much faster and easier compared to written content. In the digital age where people are inundated with large volumes of data on a daily basis, data visualization enables decision-makers to quickly and effectively process raw data to find the most relevant information.
Data Visualization: Significance & Roleplay
Visual analytic tools help you interact with data to obtain information, insight, design conclusion and make instant but accurate decisions. The virtue of visual representation reduces the complicated work required fo a certain task.
Companies use this tool to generate information and derive information from it, among some of the benefits it can offer:
#Helps turn an Overloaded set of Information into an Opportunity
Developers of Business Intelligence and Data Analytics applications are increasingly using advanced technology to handle large volumes of information that helps in better interpretation of analytical results.
Businesses are currently being bombarded with big data and therefore is a need to turn it into smart business decisions. While most traditional BI tools are geared towards market analysts, data visualization is seen as a way to make business analytics available to a wider audience.
Interactive data visualization tools allow a better understanding of relationships and trends in information sets. A recent study reveals that decision-makers using data visualization tools are 28% more likely to discover relevant information than those who rely almost exclusively on traditionally managed reports and simple dashboards.
Additionally, 48% of employees using business intelligence in conjunction with visual data discovery tools are able to access the data they need with the help of IT staff.
#Allows Professionals to Expand their Cognitive Abilities in the Analytical Process
The volume of data that companies can collect on costumers and market conditions that companies can provide business leaders with insights into new revenue and business opportunities.
The use of data visualization will allow decision-makers to understand changes in customer behavior and market conditions, across multiple datasets, much more efficiently.
Business leaders can use data visualization to see that not only are customers spending more in their stores as macroeconomic conditions improve, but they are also increasingly interested in buying prepared foods, for example.
Taking a look at a customer’s sentiments and other data reveals an emerging opportunity for the company to act on new business opportunities before their rivals.
Enterprises with the most advanced and fully and fully capable analytics are twice as likely to be among the best financial performers in their industry. Plus, these companies are five times more likely to make those crucial decisions faster and more effective than their competition.
#Tools are Used for Applications that Include Large and complex Datasets throughout Analytical Processes that require Excessive Monitoring and Interaction
Most business reports are formal documents packed with static charts and graphs. As exhaustive as these reports may be, they become so complex that most of the information is lost or fails to attract the attention of the people whose opinions matter the most.
On the other hand, reports generated from Big Data visualization tools make it possible for relevant information to become more vibrant and memorable for executives. Thus, such tools allow users to encapsulate otherwise complex data and make it more enjoyable for executives and business managers.
Through graphics, decision-makers will be able to easily interpret large amounts of data from various sources through interactive elements and constructive visual tools, such as fever charts and heat maps, to name a few.
#Decision-makers will be able to adopt new skills that allow them to use advanced Computational Tools to improve the discovery process
Another scope of data visualization that has emerged in the business world of late is geospatial visualization. The popularity of geospatial visualization has occurred due to the large number of companies offering web services, which attracts the interest of visitors.
This type of business needs to take advantage of location-specific information, which is already present in the system in the form of the customer’s zip code, for example, providing a better daily analytics experience. This type of visualization adds a new dimension to the figures and helps to better understand the subject.
It is not without its challenges.
Like many modern tools, data visualization is not without its challenges:
- The tools display graphics but do not explain, sometimes assuming users understand more than they actually do.
- Different users can draw different conclusions.
- Implicit bias of who manages the data, no matter how small.
- A false sense of security: sometimes the graphics are not enough to tell the whole story and this option is not always taken into account.
However, having these small challenges during any data visualization project can help minimize their impact.
A Booming Market
Despite its specific purposes and the multitude of areas in which it can be used, the visual analytics tool has one great goal to achieve: Deliver information in a way that is understandable to people and that they can easily analyze and act upon.
Taking into account that emerging technologies influence between 70% and 80% of the income of large companies, it is noteworthy that, for example, large financial services companies have already adopted these tools to closely monitor the destination of money.
This change in mindset is because companies can apply Big Data analytics visualization to almost any area of their business, from marketing to supply chain to customer service, to improve results and optimize their business.
However, the power of analytics can only be realized effectively by hiring people who can understand and use analytics tools to their full potential.
The global Visual Analytics market is expected to grow at an annual rate of 20.4% by 2022, reaching $ 6.51 billion. Being a relatively new tool, the latest studies affirm that SAS Analytics skills are the most demanded skills in today’s job market.
As a result, there is a high demand for SAS analytics professionals in today’s marketplace. More and more companies are moving towards it, due to its transparent interface and visual representation. As a result, earning a SAS visual analytics certification is a great way to find a challenging and well-paying job.
In today’s world, where everything from web browsing patterns to medical records is recorded digitally, petabytes of data are being generated and processed every day.
Big data will be decisive in all spheres of life. However, just to process and analyze that data is not enough, the human brain tends to find patterns more efficiently when data is represented visually. Data visualization and analysis play an important role in decision-making in various sectors.
It also leads to new opportunities in the visualization domain that represent the innovative idea to solve the Big Data problem through visual means. It is quite a challenge to visualize such a huge amount of data in real-time or in static form.
Against this backdrop, it is important for companies to seek tools that allow them to immediately begin working with data to create visual analytics and more easily get value from data.