6 best practices for deploying your data visualization software

The deployment of a data visualization software is a crucial step that must be perfectly orchestrated to guarantee the success of the project. But how can you put all the chances on your side? What are the pitfalls to avoid? Here are 6 best practices you can follow for a successful implementation.

1) Define your data visualization project precisely

Before deploying your data visualization software, it is essential to know in which direction you want to go. Specifically, you must define:

  • The objectives of data visualization within the company.
  • The user profiles that will use the software.
  • The expected number of users.
  • The volume of data to be managed.
  • The indicators you want to track.

This questioning is essential to properly define the project and take stock of your organization’s expectations and constraints. The better prepared you are, the more you can anticipate possible problems and facilitate your deployment.

In order to design KPI performance indicators, it is also necessary to locate important data. Wherefore the need to take stock of your data and review the data you are interested in while controlling their quality. In fact, the slightest wrong information could distort your indicators and hinder your decision-making. This step is especially important if you have a large amount of data to manage.

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Data management : 6 tips for managing large volume of data 

Data management: 6 tips for managing large volumes of data

2) Audit the internal requests and needs

To be effective and provide real added value to your company, your data visualization tool must meet you users’ needs.

Hence, the interest in carrying out an internal audit in order to review various criteria:

  • Functionalities: what do users want to do with the data visualization software, depending on their business, position or IT skills?
  • Governance: How will the data be collected and used? Who will have access to it?
  • Customization: Should dashboards and graphical representations be standardized or, instead, customizable?
  • Ergonomics: Should the software be intuitive and accessible to everyone or is it reserved for technical profiles?
  • Access to the software: Should the tool be installed as is on the workstations or accessible from a web browser?
  • Embedded analytics: Should the data visualization solution be integrated directly into a site, software or an intranet portal?

Of course, many other criteria can be considered, depending on the needs and peculiarities of your organization. In any case, if users have a clear idea of what they are looking for, it can be interesting to make models of the desired visualizations.

Whatever the case, you need to ensure that your data visualization tool is designed to meet your business needs, combining performance and ergonomics. With DigDash Enterprise, users can design and use their dashboards independently, regardless of their role. Decision-makers can monitor their business in real-time to make the best decisions. All this with a strong capacity of functional improvement allowing it to respond to all the needs in the long-run.

3) Support the conduct of change

The deployment of a data visualization software cannot be improvised: this step often entails radical changes in the way the company operates. This is why it is essential to support employees during the implementation of the project.

This approach includes the setting up of various workshops:

  • Presentation of the tool.
  • Definition of indicators.
  • Training workshops.

The provision of user guides, video tutorials, and other media is also of interest to internal communication around the data visualization project. Finally, it is recommended that you designate key people to oversee the project and be available to answer collaborators’ questions: project manager, infrastructure manager, etc.

DigDash: training for all your needs

DigDash supports you in the deployment of your data visualization software with training courses dedicated to all needs and profiles: business users, analysts, administrators, dashboard designers, etc. Experienced consultants offer you monthly customizable workshops, on site or in e-learning to help you perfectly master our solution.

 

4) Organize your data carefully

To succeed in your data visualization project, you need to be perfectly organized. First of all, you need to locate all the data whether it is inactive (stored in files or on workstations) or in transit (i.e. contained in e-mails or transferred files, for example).

The second step is to categorize the data. Thus, customer data and banking information will not be treated in the same way, particularly in terms of security and confidentiality. Next, it is necessary to prioritize the data according to its frequency of use, but also according to its relationship with the different business lines of the company. Not all data have the same level of priority and sensitivity.

But, if data architectures need to be schematized, it is also necessary to automate the data feedback. Automation allows avoiding human errors and to simplify the reading and processing of data. Also, it is really a time saver and a way to make more informed decisions in real-time.

Customer Testimonial:

AGIRC-ARRCO: facilitating project monitoring thanks to data visualization

Agirc-Arrco: facilitating project monitoring thanks to data visualization

5) Get key users involved in dashboard designing

To deploy a data visualization solution, your project must comply with your organization and human resources (not otherwise). It is not up to your company to adapt to the needs of data visualization, it is the other way round.

This is why you must systematically take into account the needs and expectations of target users at every level: functionalities, ergonomics, customization, etc. Better still, users must be involved in the process by taking part (directly or indirectly) in the integration of the software.

The realization of a POC is often essential to implement a data visualization project. From this prototyping phase, it is essential to collect feedback from users in order to refine the solution. This will allow us to know precisely what their needs are and to offer them a perfectly adapted tool.

In the long-run, after the deployment of the data visualization software, it is important not to stop collecting feedback. Quite the contrary, the analysis of the real use of the solution will bring new ideas to improve on functionalities.

DigDash in the news:

DigDash, the Data visualization tool goes fully online

DigDash Enterprise goes fully online

6) Take into account internal and legal constraints

Organizations are subject to internal constraints related to access to data. The key question to be answered is: “Who can see what?”

To secure the information, it is important to define access rights to the various dashboards depending on the role and level of each user. You also need to ensure that your data visualization tool offers an adequate data customization system that can meet these different constraints.

From a legal perspective, companies are also subject to numerous obligations regarding their data, including:

  • Compliance with the General Data Protection Regulation (GDPR).
  • Compliance with the CISPE’s European Code of Conduct for data protection.
  • Compliance with the code of conduct on data reversibility.

This is especially important if you want to deploy a cloud-based solution. The choice of location for data storage and processing, for example, must comply with local laws. In addition, specific certifications are required to host certain types of data. The legal environment must therefore be carefully studied in the context of your data visualization project, etc.

DigDash: an HDS-certified cloud offer

Eager to meet all the requirements of security and data confidentiality, while complying with the legislation in force, DigDash was the first purely French solution to offer HDS-certified cloud hosting (Health Data Hosting).

This type of cloud is distinguished by an increased level of security: the cloud infrastructures of each user are physically isolated from each other, which means that the data security is optimal. In addition, DigDash HDS Cloud Hosting secures access to all sensitive actions, adopting a Zero Trust approach, and is ISO 27001, HDS and SOC I and II compliant.

 

Deploying a data visualization solution is a complex process that requires excellent technical and organizational preparation, as well as a genuine change management approach.

This is why DigDash is at your side throughout the project, from the technological and functional scoping to the turnkey delivery of your solution. A personalized support that sets us apart from the giants of analytics and data visualization.

Go for this experience: Request a personalized demo of DigDash Enterprise.

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