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The transition to a modern business intelligence model requires IT to adopt a collaborative approach that includes the business in all aspects of the overall program. This guide focuses on the platform evaluation and selection. It is intended for IT to use collaboratively with business users and analysts as they assess each platform’s ability to execute on the modern analytics workflow and address the diverse needs of users across the organization.
This evaluation guide aims to support IT organizations as they evaluate and select a modern BI & analytics platform suitable for a broad, enterprise-wide deployment.
The transition to a self-service-based, modern BI model requires IT to adopt a collaborative approach that includes the business in all aspects of the overall program (see Redefining the Role of IT in a Modern BI World). This guide focuses on the platform evaluation and selection aspect of a modern BI program. It is intended for IT to use collaboratively with business users and analysts as they assess each platform’s ability to execute on the modern analytics workflow and address the diverse needs of users across the organization.
The modern analytic workflow is a cycle of inter-related capabilities.
IT enables the modern analytics workflow, but it is primarily driven by business users and analysts throughout the organization. And its successful implementation requires collaboration and participation from all roles. In order to select a modern BI & analytics platform that can be adopted and widely deployed, organizations should consider the following set of foundational core attributes throughout the evaluation process which are covered in detail in the “Core Platform Attributes to Consider” section below:
• Platform integration & accessibility
• Ease of use
• User enablement
• Deployment flexibility
• Pricing and packaging
This guide assumes the following core role types will be represented and available to participate in applicable aspects of the evaluation:
Throughout the guide, a primary role will be identified for each stage within the analytics workflow as this is the lead role for that specific stage of the evaluation. However, it is imperative that every stage of the evaluation includes participation and input from all of the above role types to ensure all needs and concerns are addressed through the process.
It should also be noted that for some organizations, the same person may serve multiple roles so it would not be uncommon for a single person to evaluate a platform from more than one perspective. Ultimately, the modern approach to business analytics will evolve to the point where it will no longer be possible (or necessary) to differentiate between an enabler, a producer, or a consumer of analytics within an organization.
In order to conduct a comprehensive evaluation of a modern analytics platform, the following tasks should be completed prior to kicking off the evaluation process.
This guide primarily focuses on evaluating specific inter-related capabilities that are important when selecting a modern BI & analytics platform. However, it is critical that the evaluation team considers the following list of non-technical core attributes that are essential to the successful implementation and execution of the modern analytic workflow in an organization. These attributes should factor heavily into the ultimate decision as they collectively serve as the glue that holds together the individual capabilities of the workflow and are foundational in nature.
As organizations begin the transition from a traditional top-down approach driven by IT to one based on self-service, it is often advantageous for IT (or a centralized BI team) to develop an initial set of trusted data sources and analytic content. Business users can then access and use this content as a starting point for their analysis. Over time, as users are encouraged to ask and answer their own questions as part of the modern analytics workflow, the domain of available trusted content will grow organically. Users will have access to a wider range of analytic content for self-service. For the purpose of this section, we will disregard the origin of content available to end users, and the evaluation criteria as it pertains to getting into a governed state will be addressed in the “promote & govern” section.
The evaluation criteria for this section will first be addressed from the perspective of the IT/BI professional who is ultimately responsible for the administration of the centralized environment where analytic content is stored and maintained, and data sources are administered and monitored.
IT/BI professionals should be able to:
The second perspective in this section to consider is that of the information consumer who drives the specific usage requirements and parameters that the IT/BI professional is responsible for successfully delivering.
Information consumers should be able to:
The interact phase is an extension of the initial access-and-view phase of the analytics workflow. It offers information consumers need to perform guided analysis of available content within predetermined fixed boundaries as set by the content publisher. The following considerations should be the focus of the evaluation for this section from the perspective of the information consumer:
This phase of the modern analytics workflow spans a broad spectrum of user needs, and it is imperative that the platform seamlessly addresses these needs. This phase is of particular significance in the workflow as it differentiates data-visualization tools used to build charts from rich visual-analysis tools that use visualizations as the primary metaphor for analysis. As users interact with dashboards and generate new questions, users will inevitably encounter barriers and roadblocks as they reach the limits of the guided experience offered by existing dashboards. When this occurs, users require a self-driven, autonomous framework for asking and answering new questions that have emerged. Users of all skill levels must be able to “visualize as you analyze” and access the analytics capabilities of the platform while in the flow of analysis without having to move to a different module or product in the suite.
The concepts of platform integration and ease of use are covered in the “core attributes” section at the end of this guide in greater detail, but they are most critical to consider here. The transition from the “interact” phase to “analyze & discover” is often where the analytics workflow is disrupted due to lack of overall continuity of platform components needed to
ask the next level of questions.
The first scenario to consider is from the perspective of an information consumer who has generated new questions that cannot be addressed by any available dashboards. The following considerations should be the focus of the evaluation for this scenario:
The second scenario to consider is from the perspective of a content creator who has new questions that cannot be addressed by any available dashboards or any trusted data sources within the environment. The following considerations should be the focus of the evaluation for this scenario:
Content creators should be able to:
The approach to sharing content has evolved. Within traditional BI platforms, sharing meant the delivery of static printed or exported reports to an inbox or a user’s desk. Within the modern analytics approach, sharing now includes collaboration and aspects of social interactions that we have grown accustomed to with all of our business tools. This transition is driven by the simple fact that information is outdated as soon as the report is printed or exported. And this doesn’t align with the needs of today’s consumer seeking the latest information. Some aspects of content sharing involve making information broadly available to users while others aspects entail collaboration as a core component of the analysis process. Both scenarios will be included in the evaluation criteria for this section.
The push model of making information accessible to a broad range of users will be addressed first. This is a more reminiscent of the traditional approach; however, modern platforms should also enable organizations to make information broadly accessible to a wide range of internal and external users. Many of these tasks fall into the domain of the IT/BI professional and the following criteria should be evaluated from that perspective.
The second scenario is that of true collaboration where both trusted and untrusted content is discussed, reviewed, and validated at the peer-to-peer, workgroup, or enterprise level.
This collaboration should be an integral step in the process of deriving new insights and as an input into the governance process. The primary participant in this scenario is the content creator which should be the perspective of evaluation for the following criteria.
There are various approaches to governance. And every organization is going to fall at a different point on the spectrum ranging from an IT-led, highly-governed and control environment to one with little to no controls, with many organizations landing somewhere in between. Often times, even within one organization, the governance requirements may vary depending on the user needs within that area as well as the data itself.
When choosing a modern analytics platform, flexibility is important to consider in order to meet those varying needs of the business and to ensure that you can alter your governance needs as you scale. An organization may choose to facilitate the transition from traditional to modern by initially using the modern platform in a traditional manner then gradually expanding the range of capabilities that are accessible to users through self-service. It is equally as important to evaluate a platform’s distinct capabilities in the separate but related areas of data governance and analytics governance (as depicted below) to ensure that an adequate amount of flexibility is afforded within the platform to put the most appropriate governance model in place and adjust over time as needed.
For most modern analytics use cases, a self-service-driven organic approach to governance will lead to greater adoption, deeper insights, and improved business outcomes. As such, this is the approach that should be considered primary for the purpose of this evaluation.
In this approach, a subset of content creators, referred to as information stewards in this guide, are primarily responsible for defining and navigating the overall governance process. The sections below will consider aspects of both data governance as well as analytics governance from the perspective of the content creators as well as the IT/BI professional.
The task of defining and ensuring compliance with an organization’s governance framework is a core responsibility of the content creator and as such, the following data governance- related items should be considered from that perspective:
Administration and enablement of the entire governance process is largely the responsibility of the IT/BI professional, and as such, the following data governance-related items should be considered from that perspective:
The responsibility of defining and ensuring compliance with an organization’s governance framework is a core responsibility of the content creator, and as such, the following analytics governance-related items should be considered from that perspective:
Administration and enablement of the entire governance process is largely the responsibility of the IT/BI professional, and as such, the following analytics governance-related items should be considered from that perspective:
The shift from traditional BI platforms to modern analytics platforms is one that is necessary to truly realize the impact data can have on an organization. Modern analytics platforms bring together self-service and governance to empower the entire organization with trusted data to gain insights into the business. These platforms should be evaluated through a different lens as they break the mold of traditional, IT-run BI platforms.
Tableau, a proven leader in the modern analytics space, enables organizations to explore trusted data in a secure and scalable environment. It gives people access to intuitive visual analytics, interactive dashboards, and limitless ad hoc analyses that reveal hidden opportunities and eureka moments alike. As well as the security, governance, and management you require to confidently integrate Tableau into your business—on-premises or in the cloud—and deliver the power of true self-service analytics at scale.
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