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Insight Paper 12.17.2020

Level-Up Existing Analytics Capability with a Data Visualization Platform

Maximize the ROI of your data by implementing a visualization platform that is aligned with your organizational strategy.

Data Visulization Platforms and Analtic Capabilites

The human brain is designed for visual processing. In fact, people are able to process visuals 60,000 times faster than text. When large stores of information, specifically data sets, need to be examined, it is far more efficient to process the information in a visual manner. Companies of all sizes are increasingly utilizing analytics to drive strategic decision-making using data visualization platforms.


It is important to first have defined analytics goals that are aligned with the organization’s overall strategy to realize the value of your data. Even with the correct data visualization platform, organizations with unaligned goals will have trouble capturing the full value of the platform. Trexin’s Strategy, Assessment, and Roadmap (STAR) Methodology is an effective way to document an analytics strategy; focus on goals and desired future state, align the organization, and a plan to execute the steps needed to achieve the roadmap.


Studies show that data scientists spend around 80% of their working hours preparing data. Not only is this typically unenjoyable work that can lead to burnout, but it decreases the amount of available time to analyze the processed data to answer business questions. Because data visualization platforms often include features to automate data preparation, this frees up user’s time to perform value add activities such as in-depth analyses and build standardized dashboards and reports.

In addition to saving data scientists’ time, the visual organization of data inherently provides opportunity to drive insights and capture value that may otherwise go unseen. Furthermore, many platforms open the door for organizations to use analytics in a broad and collaborative capacity. By organizing data visualizations in a centralized location, business users can self-service data by adjusting filters as well as share information with others through exports of PDFs or PowerPoint.


Data visualization platforms encompass a suite of tools, with varying levels of features – at the most basic level, there is simple visualization enablement using Microsoft Excel charts or dashboarding in PowerPoint. At the other end of the spectrum exists full suite platforms that use automation to handle tasks such as preparing and refreshing data. Full suite platforms such as Tableau or PowerBI offer additional features such as the ability to tell stories about data, and publishing abilities that allow for self-service business use. The most advanced of the data visualization offerings offer the ability to effectively manipulate data with the assistance of AI and machine learning. These platforms unify data, enable predictive analysis, and use machine learning to allow further insights.

With the many quantitative and qualitative benefits of using data visualization platforms, implementing one may be an obvious choice. Figuring out where to start and choosing one can be difficult. Trexin’s Vendor/Solution Selection Methodology offers an organized framework for selecting a vendor.

With organizational strategy and analytics goals in mind, consider the below factors when selecting a data visualization platform:

  • Cost
    • Understand which features are desired, both in current state as well as further down the roadmap as upgrades may be necessary. A scalable visualization platform will be cost efficient versus planning to implement an entirely new system.
    • Licensing structures and up-front costs vary between providers, is your organization prepared to cover larger implementation costs up front? Are ongoing costs aligned with the organizations budget?
  • Mobility
    • Where will users need to interact with visualizations? Determine whether interacting and editing on mobile devices is needed.
  • Data Sources/Integration
    • Ensure the data visualization platform is compatible with the existing data architecture.
    • What is the likelihood that your organization will need to integrate additional data? Ensure the ease of this process is in alignment with realistic needs.
    • Are there reports or key performance indicators (KPI’s) that require input from real-time data? Ensure the existing data architecture and data visualization platform support a live connection to data.
    • How do the analytics goals relate to maturity of the data architecture? The visualization platform should be nimble enough to scale and support roadmap planned architectural changes.
  • User Interface
    • Assess the skillsets of both the editors and interactors to determine the necessary level of ease of use.
    • What level of training is your organization prepared to provide? Ensure the platform is appropriately intuitive for stakeholders to import data, create visuals, and interact with dashboards.
  • Features/Customization
    • What data preparation processes are currently in place? Are there features in the data visualization platform that automate these in an efficient way?
    • What level of complexity will the visuals require? Does your organization have goals that would be easier to meet with the help of predictive analytics? If so, platforms that feature AI and machine learning should be considered.
  • Collaboration
    • How is your analytics team structured? Can calculated measures, fields, hierarchies, and other business intelligence meta-data be shared across reports and developers?
    • How will users access visualizations? Will reports be used in a static manner (i.e. PDF attachment emailed to a distribution list), or should the platform be centralized for users to access and engage?
  • Security
    • Review the security requirements of your organization’s data set and ensure that the chosen data visualization platform meets or exceeds them.
    • If the platform will be used in a collaborative manner, ensure role-based access management can be implemented for various levels of users.

There are numerous factors to consider when implementing a data visualization platform to enable your analytics strategy. When assessing these factors, it is important to first assess overall analytics goals as part of your organization’s strategy and determine how a data visualization platform will increase the value capture from your data. When careful thought has been put into the selection and implementation of the platform, organizations can reap many benefits and increase the ROI of their data by enabling their analytics capability with a data visualization platform.

Need help with organizational readiness or vendor selection? Connect with a Trexin Advisor regarding our STAR and Vendor/Solution Selection offerings.


Tagged in: Analytics