{"id":11338,"date":"2021-07-13T16:23:04","date_gmt":"2021-07-13T14:23:04","guid":{"rendered":"https:\/\/www.digdash.com\/?p=11338"},"modified":"2023-04-26T11:25:23","modified_gmt":"2023-04-26T09:25:23","slug":"how-to-choose-and-integrate-a-data-visualization-solution","status":"publish","type":"post","link":"https:\/\/www.digdash.com\/en\/news-articles\/business-prospects\/how-to-choose-and-integrate-a-data-visualization-solution\/","title":{"rendered":"How to choose and integrate a data visualization solution?"},"content":{"rendered":"

A crucial challenge for all types of companies and organizations, data is still too often under-exploited.<\/p>\n

In fact, many structures are faced with a major problem: how to make sense out of the raw data and make them understandable to everyone? It is to meet this challenge that data visualization<\/strong> was designed, as it can represent data in a readable and aesthetic way.<\/p>\n

However, deploying a data visualization solution<\/strong> is not a project to be taken lightly. So, where to start?<\/p>\n

Identify your main selection criteria<\/h2>\n

To choose a data visualization solution adapted to your needs, it is necessary to rely on precise selection criteria. There are a multitude of them and each organization has its own priorities. However, there are a bunch of essential criteria to consider.<\/p>\n

Versatility<\/h3>\n

A good data visualization tool should not only generate visualizations. It should also allow upstream structuring and preparation of data <\/strong>for their optimal processing. In addition, it is preferable that your solution integrates advanced or even predictive analysis features <\/strong>in order to project yourself into the future and make the best decisions.<\/p>\n

Another important detail: the accessibility of the tool.<\/strong> To express its full potential, a data visualization solution must be usable by data specialists, but also by business users.<\/p>\n

Cost<\/h3>\n

The cost of your data visualization tool is, of course, an significant selection criterion. Make sure that the solution you choose has a price that is adapted to your organization<\/strong> and its size. For large companies, with a high number of users, it is essential to ensure that the rates are decreasing. In other words, the business model must be compatible with large-scale deployment.<\/p>\n

The type of offer can also have a significant influence on the price. Thus, all-inclusive software <\/strong>has the advantage of integrating all the functionalities, with a completely transparent price. “Custom-made” proposals<\/strong>, on the other hand, offer additional payment options, the accumulation of which can be very costly.<\/p>\n

Performance<\/h3>\n

Data processing capacity is crucial for a data visualization tool. It must be able to handle a large volume of data<\/strong> while offering exemplary performance. In addition, a good data visualization solution must be able to handle multiple data sources and import all types of files. This allows you to view different data sets from a single interface for simplicity.<\/p>\n

Adaptability<\/h3>\n

Organizations have different needs depending on their size and line of business. From finance to retail, including local governments, a data visualization tool must be able to adapt to the specific needs of each structure.<\/strong> It is therefore necessary to take a close look at avenues for functional evolution of the solution.<\/p>\n\n\n\n
To learn more, see:<\/p>\n

15 essential criteria for selecting your Business Intelligence solution<\/span><\/u><\/a><\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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Evaluate the different data visualization solutions<\/h2>\n

Now that you have analysed your various selection criteria, it is time to pre-select the data visualization tools likely to meet your expectations. Do not hesitate to carry out a benchmark<\/strong> based on a precise evaluation grid, in order to highlight the strengths and weaknesses of each solution.<\/p>\n

If a solution has caught your eye, carrying out a POC <\/strong>(proof of concept) is strongly recommended before making a final commitment. It is a kind of prototype intended to demonstrate the feasibility of the project and to evaluate the solution with concrete achievements.<\/p>\n

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Integrate your data visualization solution<\/h2>\n

Now that you’ve made your choice, all you have to do is deploy your new data visualization solution within your organization. Here are some key steps to follow to ensure that the project runs smoothly.<\/p>\n

Define your data visualization project<\/h3>\n

To effectively integrate a data visualization tool, it is necessary to precisely define your project, your expectations and your constraints<\/strong>.<\/p>\n

It is necessary to answer the following questions especially:<\/p>\n