How to choose the best Data Visualization Services for your Big Data?

How to choose the best Data Visualization Services for your Big Data? - Thinklytics

When you have a pile of data, then you must get confused about which data points matter. Also, it’s also important to identify in what ways they relate to your business’s interests. Here, we will cover the ways to identify the best data visualization services that can help you resolve these issues.

There are several tips for choosing tools that work and maximize their utility. Hence, interactive visualizations play a very important role in any company, fitting the needs, priorities, and standards.It is very crucial to choose the correct service as it affects the health of a business.

Here are a few criteria that will help you choose the best data visualization tools to help your business achieve its goals. These criteria help you take care of user interaction, employee performance, customer experience, and overall expenses.

It can strongly affect decision-making at critical moments. However, this is only possible when data analytics is easy to understand for non-tech people.

Tips for Choosing the Best Data Visualization Services for your Big Data –

1. Differentiate between presentation and graphics

There are majorly two types of Data Visualisation forms, i.e., Presentation Graphics and Exploratory Graphics. Presentation graphs are similar to mathematical theorems. They only have the conclusion, not the procedure through which the result has been reached.

They offer convincing support for its conclusion. On the other hand, Exploratory graphics are used for understanding the results and how we come up with this answer. The data visualization service used in exploratory graphics should be fast and informative rather than slow and detailed. Since it directly includes answers rather than details.

2. Data visualization should follow its function

The visualization must reveal the –

  • Questions you are trying to ask
  • Properties of your data
  • Way of presentation, for example – pie chart, bar charts, etc.
  • Insights that are to be communicated

For example, if we want to show the impact of covid on the economy theme, we have to show the relationship between all the affecting factors and their impact. It requires a different visualization for every element.

3. Draw a blueprint of your visualization

Before deciding which tools you want to use, prepare an outline or a blueprint of your data. It depends on your skills and the purpose of the visualization. Also, take care of the time constraints and other factors. When you have a rough blueprint of your visualization, it will be easier for you to select the most suitable tool.

4. Look for tools with intuitive dashboards

The dashboard of your data visualization tool should look great. It needs to be clear and colored with adequate whitespace. There must be a balance in the colored view for a more attractive appearance. The dashboards and reports should accurately summarize all the essential data.

5. More clarity and less visual bloat

Whenever we want to represent something graphically, then it must be informative. Being informative does not mean extraneous information, although it should cover the major details. All the data represented should be authentic and must have true values. It must be relevant to your business. And the most important thing is it must be clear and unambiguous.

6. Make your data more meaningful

The data depicted graphically must have some meaning or utility; otherwise, it is of no use. To increase the effectiveness of your presentation, must keep this in mind throughout the data analysis process.

The data visualized through the selected tool must inspire the action of your audience. The purpose of the information should determine the format of the data visualization practice.

7. Balance between functionality and needs

Choosing the right data visualization tool means balancing the needs of the data analysts and technical requirements. You have to determine whether you need to add components to your current technical architecture or not.

Sometimes, it might be possible that the choice of data visualization services and your needs do not favor each other. In that case, a balance must be there between your need and functionality. There are several web based tools, from which you can choose. 

 

8. Merging with multiple data sources

Your metric values have different components in real time. The next thing you must take care of should be the multiple data sources from which you have to derive data. It would help if you used such a tool for data visualization compatible with various data sources like databases, spreadsheets, etc. Your tool must be able to visualize how the different pieces contribute to the overall performance.

9. Animation and dynamic data

Animation effects are the next essential thing users should look for when selecting data visualization applications. It will also ensure ease of use and optimal functionality. Animation is the trait of advanced tools. Also, the tool must include the characteristics like dynamic data, visual querying, personalization, and actionable alerts.

10. Expertise in using that tool

Though most of the data visualization platforms have similar features, there will be differences that you will face. For example, Power BI or Tableau public is different from Google Charts. It can be anything from design style to developer limits. So, it is very much needed to know before using the tool which one is easily accessible. We can consider the ease of Integration, operational cost, technical expertise, deployment duration, and supported data. 

11. Beautiful data visuals

Google has a vested interest in making the analysis beautiful. In this way, it attracts people to invest in it. Usually, pretty things grab attention, and attention makes people pay. Data visualization also needs to do this for you. Interactive data visualization helps surface valuable marketing analytics that might be very important to your business.

12. Visualized data highlights unique opportunities

Several organizations are using predictive analytics to uncover the strength of sales. It also helps customers to provide additional support. Visualized data can provide better experiences to the customers as well. It opens up several unique opportunities to generate more revenue.

Conclusion

Overall we can say that both data and data visualization is important for a business. Implementing the visual presentation of data is nearly as important to the effectiveness of the data being represented. Your visual must incorporate data as a piece of evidence to support your claim. Irrelevant data only distract your customers and lead to wrong decisions.

So, no need to show everything, as the audience doesn’t have the time to devote. It is the job of the assessment team to analyze, interpret and display the data that is pertinent to the findings. So, anyone that can perform all these activities can be the best data visualization service for representing your data. Thus, incorporating all these features Thinklytics is the best data visualization service provider. 

References –

  1. callminer.com

 

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