As technologies develop, not access to data but usability gains importance. Because it is now easier to access data thanks to new generation technologies. Especially since the concepts of Big Data and the Internet of Things have emerged, almost all kinds of information can be accessed in a short time. However, what is important is the way the information is processed in order to keep it up-to-date, accurate and to make accurate analyses. In the era of big data, not more information, but relevant and usable, better quality and timely information is needed. Data visualisation is very important at this stage. So what exactly is data visualisation? How is it done, what does it do?
Data visualization makes it possible to quickly obtain information by visualizing data regardless of format, type or source. It also allows the presentation of information that is not visible at first glance about what the data means in a clear and clear way. For example, all organizations collect more data every day. This includes data on sales figures, marketing performance, inventory levels, staffing, and other KPIs. It is quite difficult to extract practical information and management information from this raw data. Data visualization is an ideal solution for this.
Data visualization is the graphical representation of data so that data can be transformed into easy-to-understand information. The goal of data visualization is to make trends, outliers, and patterns in the data transparent and understandable. The human brain is also more likely to benefit from graphics and images than a complex spreadsheet. Data visualization is therefore done in the form of all types of (interactive) graphs, tables, animations, dashboards and reports.
Data is valuable to everyone, but it is quite difficult to make this data valuable. The data becomes useful through its analysis and interpretation by professionals in the field. Financial data is out of this field because financial professionals, who have been important users of data analysis for years, are capable of numerical analysis and are therefore good at turning data into action. This is why data analysis has never been a problem in the field of finance. But it does not apply to other departments. This is where data visualization comes in.
Properly visualizing the data helps them interpret the data correctly, turning it into professional decisions. That is why good data visualization aims to make data more accessible to everyone, for example, through diagrams, graphs and maps. As a result, professionals in their field can gain an excellent insight into patterns and different values in the visualized data and thus discover trends. In the hands of a marketer, customer data only becomes valuable in this way.
Visualizing the data makes the information visible and accessible. You no longer need to analyze entire spreadsheets with data and perform complex calculations. The information obtained from this data is easy to visualize in one or several images. You also learn about the development of trends in sales, marketing, purchasing and HR, allowing you to quickly make data-driven decisions. Other advantages of data visualization can be listed as follows:
· With data visualization, you can contribute to the growth of your company. With management information from dashboards and reports, you gain a competitive advantage, realize growth and work more efficiently.
· The human brain cannot process large amounts of data at the same time. This means that managers make choices without understanding all the information. Data visualization facilitates faster processing, assimilation, and interpretation of data.
· The amount of data continues to increase as time and resources continue to shrink. Using data visualization allows you to overcome these challenges.
· Modern data visualization tools enable professionals to increasingly perform their own data analysis. With a modern data platform in the cloud, organizations can access and connect more and more data sources.
· You can also connect these modern and intelligent data platforms to data visualization platforms. Good toolkits provide powerful capabilities to data professionals such as data scientists and business intelligence professionals.
· Allows team members to develop standardized boards where they can share ideas and information among themselves or between teams.
· Data visualization is not just an ideal way to convey information. You can now navigate through the information and adjust the variables again thanks to the visualizations. Thus, it gains a clearer insight and its complex data can be seen clearly.
· Simple rows and columns show values, patterns, trends, and links that are not visible. Because images can tell more than words.
You can visualize data with a (2D) chart, diagram, map, illustration, or infographic. It is converted into pictures because pictures often give more insight. They are easier and faster to understand than normal data. Virtual reality, on the other hand, makes a visualization 3D, immersive and interactive. Examples of data visualization can be listed as follows:
· The architect visualizes the construction drawings. In this way, they can discuss and decide on the design together with the customer. Thus, the entire structure can be displayed at scale, and certain points can be adjusted again instantly.
· The Wall Street's 21-year visualization of the Nasdaq stock price published in 2015 is also an ideal example. The graphic presented in the form of a rollercoaster has become much more impressive and understandable than the contents of a list or excel.
· The data presented in the form of graphs is a visualization method that almost every company uses. Thanks to this, everything is clearly visible, from accounting to the share of the company in the sector. For example, when a new campaign is made, the increase in sales over a certain period and the comparison of the stationary period is done quite easily with the graph. In this way, what needs to be done can also be seen more clearly.
Data visualization is the most important part of the analysis phase. But it is extremely important that the visualization is done correctly. At this stage, attention should be paid to the use of colors, the correct transfer of values, simplicity of the image, design and data quality. Tips for data visualization to be useful:
· Use of color: The use of color is the basis of visualization. Colors can also lead to confusion, or even worse, misinterpretation. Therefore, you should use shapes and colors that are easy for people to see, choosing your colors carefully to convey the message correctly.
· Use of pie charts: Pie charts are a visualization method that has maintained its popularity for a long time. But slices that are too thin can be confusing. Instead, you can prepare several cakes that address the issue from different angles and make it simple, understandable.
· Scratching visual clutter: when you visualize too much data, it becomes difficult to handle the whole. Therefore, plain visuals are always more understandable. Analyzes can also be erroneous, as it distracts from the final goal with the unnecessary element.
· Design: Design determines not only how it looks, but also whether visualization is useful. Effective visualizations combine design elements that contribute to better transmission of data. That's why you can add striking points instead of just creating boards.
· Data quality: Successful visualizations start with good data. If your visualization reveals unexpected results, you may doubt your data quality. Before you start data visualization, you need to discover and solve problems in your data.
As a result, data visualisation is not just about graphics and dashboards. Data accuracy, quality and visualisation are also very important at this stage. In order to analyse your data correctly, you can benefit from our partner Qlik and Looker technologies in Turkey.
Qlik ensures accurate processing of data transferred from complex and multiple environments for analysis of your complex data. With Qlik, you can enjoy more than interactive analytics, self-service data visualization, customized & clothed displays, and analytics. On the other hand, you can also choose Looker, one of the services offered by Komtaş. Because Looker not only provides a dashboard for you to turn your data into value, it also allows you to perform important analytics for your organization. By creating many datasets, you can improve customer experience and satisfaction, and guide your company based on user profile.
The main tasks of data analysts are to collect, process and analyze data, as well as prepare reports that can consist of graphs, diagrams, tables and other visuals.
A relational database consists of tables that are related to each other, and each table contains data of a specific data type - an entity. The relational model defines reality and usually has as separate tables as the number of entities. A relational database attempts to display all data items only once.
Data virtualization is the reproduction of real data in a virtual environment. In this way, tests, experiments and analyses performed when working with real data can be carried out without compromising the accuracy and security of the real data.
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