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The Role of Data Visualization in Data Democratization

    Data visualization has changed the way brands and businesses used to present information. While data democratization has further evolved the techniques of approaching data. Data democratization is referred to as giving barrier-free access to large-scale data. It makes digital information easily accessible to all users without requiring any prior technical knowledge of data analytics. Democratization of data has reduced the dependence on technical data analytic experts. It has enabled ordinary users of information systems to analyze and gather information at their fingertips without any outside assistance. Getting inferences from data visualizations has become easier for an average non-technical user through the democratization of data. Which helps in effective decision formulations.

    Implementation of data democratization requires a self-aware, well-structured, and easily adoptable solution of data visualization for easy-to-understand user exposure. Protocols are required to be in place. It makes sure that information users understand the data in its true essence without any perceptual misunderstanding. Data security is also required to be maintained. Because increased accessibility to data often comes out to be vulnerable for overall data integrity. It increases risks to data security. Such driving measures encourage the participation of all the users in decision-making drive across the overall organizational ecosystem. Enabling insightful participation enhances business performance.

    As we have already discussed, democratization gives enterprise-wide free access to data, which everyone gets benefits from. Here metaphorical term of enterprise does not represent businesses only. Humanity itself can be defined in terms of an enterprise where all human beings get benefit from the democratization of data. In this human definition of an enterprise, the printing press sparked a massive rise in the democratization of data. It has accelerated the pace of giving access to an ordinary person with important information and data. However, in the context of this tract, we are giving heed to the roadmap towards data democratization and visualization. Which is only from the perspective of the corporate data of an organization.

    Now, here comes the question, how effectively data can be democratized through the visualization of data? In more simplistic terms, we are concerned with the role of data visualization in the democratization of data. Graphical representation of data involves multiple tools and techniques for the effective visualization of information. Commonly used visual elements are graphs, charts, and maps, etc. These visualizing tools provide an easy-to-understand interpretation of patterns, outliers, and trends present in the data.

    These are some common types of data visualization tools and techniques:

    1. Graphs

    2. Charts

    3. Maps

    4. Infographics

    5. Tables

    6. Dashboards

    While, more specific models of data visualizations revolve around multiple representations of Area Charts, Bubble Clouds, Cartogram, Gantt Charts, Circle View, Box and Whisker Plot, Bullet Graphs, Matrix, Polar Area, Streamgraph, Text Tables, Scattering Plots including both 2D and 3D, Networks, Histograms, Heat Maps, Dot Distribution Maps, Radial Trees, Bar Charts, TreeMaps, Timeline, Word Cloud, Wedge Stack Graphs, and any combination of above-mentioned visual representation in a more intuitive and creative way.

    When it comes to present data in different patterns whether physical or colorful. It becomes easier and error-prone to visualize and understand the information available in the data. We can more easily and quickly distinguish between Red and Green than two different numerical numbers. Numerical representation of numbers is more complicated to analyze. We are culturally more visual. Every visual aspect in our surroundings extracts our attention more effectively. Art, design, TV shows, movies, and advertisement, every visual storytelling technique creates a greater impact on our psychology. That is in fact, the real essence of data visualizing tools which is an evolved form of visual art. Such visual art grabs our attention and keeps us intact with the overlay information. It helps us to easily digest the message being delivered in the specific piece of visually represented data. For instance, looking at a massive spreadsheet may not give you inference of the specific trend present in it. But graphical representation of the same spreadsheet can easily serve the purpose without any excessive heed.

    The most important purpose which data democratization and data visualization serve is the internal decision-making capability. However, data visualization techniques including pie charts, scatter plots, and data tables, etc. are being implied for a long time. These data visualization tools help to report information and present a concept in a useful way. But their usefulness had always come under excessive limitations when these techniques were implied to complex, and multi-level data insights. Under such circumstances, the role of an analyst always became of crucial importance to interpret the data. In such cases, dependence on data analysts always increases. Democratization of data was always challenging in such scenarios dealing with big data. However, advanced data visualization techniques and algorithms have made it easier to collect, format, and organize data. It helps to develop useful storytelling features out of the visually represented data in an effective way.

    When we come to interact with the world of big data. It becomes obvious why we are in utter need of data visualization tools for effective data democratization. It is essential to employ visualization tools to analyze the massive amount of information. Such information is always hidden in the raw data available in bulk form. Balancing between form and function, highlighting essential information, and removing noise from data give rise to effective visualization. Without efficient visualization of data, trillions of data rows being produced every day, are incapable to infer any important information. Data-driven decisions can only be successfully contemplated through data visualization technologies.

    In this age of Big Data, data sets are increasingly transforming into valuable commodities for organizations. It is impossible to extract useful information and hidden trends from big data without effective deployment of data visualizing techniques. Without it, the whole of the data set is of no use nor the purpose of data democratization can be served. The impact of information visualization on the democratization of data is not a new revelation. We can easily observe thousands of infographics being posted on multiple social media platforms are serving the purpose. These infographics help the viewers to easily understand the message in a time-efficient way. It also helps to infer decision-making conclusions from it. Thus, democratizing the data through data visualization.

    Data democratization and visualization are the most important practices and tools of all the professional industries. We can not think of any practical field which is not getting benefit from the practices and techniques of data democratization and data visualization, respectively. Education, Health, Industry, Banking, Finance, Sports, Marketing, and Administration, each sector is relying on data democratization and data visualization. The purpose is to make their information systems more understandable for all the viewers and users of the system. In fact, visualization has emerged as one of the most professional and useful skills required to be developed. The better you can deliver your message, the more you are probable to convince your audience. The better you convince your audience, the more successful you are probable to be. That is how good visualization skills can serve the purpose of visual representation of data whether on the dashboard or in the slide decks to make your audience more engaged with your message.