Core Capabilities of Data-Driven Organizations
This content is part of Tableau Blueprint—a maturity framework allowing you to zoom in and improve how your organization uses data to drive impact. To begin your journey, take our assessment(Link opens in a new window).
At the heart of every data-driven organization, you will find three core capabilities—agility, proficiency, and community. The three capabilities are supported by organizational intent, change management, and trust.
A consistent approach to governance establishes guardrails around data and content security, access, and processes, allowing you to create a trusted and secure analytics environment for every department, team, and person in the organization. Governance is central to all successful self-service analytics initiatives, and it will help your organization start, grow, and evolve the use of data and analytics.
Scaling these efforts also means measuring and proving their impact on the enterprise’s transformational goals with data and analytics. This means understanding which metrics best capture the cumulative impact of your iterative deployments, governance practices, increasing analytical skillsets, and community growth. Suitable metrics—especially for measuring behavioral changes—will vary for each organization, and should be evaluated at regular intervals as analytics practices evolve.
Deployments must possess agility and provide choice and flexibility to meet your technology needs today. as well as adapt to where they go in the future. For on-premises and public cloud deployments of Tableau Server, you should operate on iterative, repeatable processes that begin with establishing a baseline architecture for a secure, stable, and trusted server platform. Given that analytics become mission-critical, agile deployments with proactive monitoring will maintain sufficient availability, capacity, and headroom while minimizing resource contention. Because modern BI platforms often see fast growth, you will need to assess server utilization and user engagement—and likely even change your topology—more frequently than with other enterprise technology platforms in order to remain responsive to the increased use of data and analytics. Alternatively, you may choose Tableau Cloud, the fully-hosted, SaaS analytics solution where Tableau scales and maintains the platform.
This workstream is focused on deployment, monitoring, and maintenance, which are typically IT-led efforts that rely heavily on understanding the broader business strategy and requirements.
- Deployment — Both Tableau Server (on-premises or public cloud) and Tableau Cloud (fully-hosted SaaS) leverage your existing technology investments and integrate into your IT infrastructure to provide a self-service, modern analytics platform for your users. For Tableau Server, your systems administrator along with the Tableau Server Administrator will install and configure. For Tableau Cloud, you will work with select IT roles to integrate. A desktop administrator will deploy client applications to licensed users of Tableau Desktop and Tableau Prep Builder. For mobile use cases, Tableau Mobile can be published to your organization’s mobile device management solution. Tableau Deployment walks through the entire installation & configuration process and provides best practices along the way.
- Monitoring — Data is critical to doing analytics at scale. Ongoing, proactive hardware and application monitoring are required to deploy and operate Tableau Server and meet business requirements and performance expectations of your user community. Without monitoring, a “set it and forget it” mentality will likely be met with inadequate resources that fail to support the workload of highly-engaged users. Administrators should work together to ensure performance and stability of the platform to meet evolving business needs. For Tableau Cloud, it is critical to understand job status for data refreshes, site size, and licenses. For more information, see Tableau Monitoring.
- Maintenance — Regular maintenance activities will keep your Tableau deployment running in top condition. For Tableau Server, you will operationalize change management processes to support the increased use of analytics, including performance tuning, load testing, capacity planning, and server upgrades. Monitoring data will be the driver behind many maintenance decisions. For both Tableau Server and Tableau Cloud, you will plan client and mobile software upgrades. Tableau Maintenance outlines activities and tools to keep your deployment in optimal condition.
For people to skillfully analyze data that's relevant to their jobs to make decisions that drive the business forward, they must develop proficiency. Beyond data capabilities, this also means employees actively seek using data over decision-making by instincts or feelings. Maximizing analytics investments and capitalizing on the transformative potential of data means that everyone encountering it—regardless of skill levels and data fluency—must be able to turn data into insights.
This workstream is focused on user education, measuring adoption and engagement, and increasing data fluency within your organization through best practices.
- Education — To integrate modern analytics into the fabric of your company, it’s essential to build a scalable and ongoing learning plans for all your users by evaluating their relationship to data. Tableau Education will help you design and build the right education programs for your organization.
- Measurement — Similar to the monitoring requirements to achieve agile deployment, measurement helps Tableau Site Administrators understand user behaviors, such as who is creating and consuming content, which is important for managing and growing your team’s use of analytics. For more information, see Measurement of Tableau User Engagement and Adoption.
- Analytics Best Practices — Enable your users with the Cycle of Visual Analysis and repeatable processes to author, share, analyze, and collaborate, then extend it with your own organizational standards. For more information, see Analytics Best Practices in Tableau.
Community creates a network of users within your organization who use data to share and collaborate. This will continue to drive adoption and learnings around analytics and the insights they discover. The community leader will coordinate efforts to document enablement resources, connect users within your company, and generate enthusiasm among a group of people founded on the common cause of putting data at the center of every conversation. Internal user communities also benefit from integration with and support from the broader, global Tableau Community.
This workstream is focused on enabling user growth and evangelizing analytics through communications, engagement activities, and support.
- Communications — Establishing internal communications and user enablement resources promotes adoption to scale data and analytics more efficiently by guiding their learning and usage. Tableau Communications outlines how to build strong communication channels, including an enablement intranet, analytics blog/newsletter, and discussion forums/chat.
- Engagement — While building excitement around the use of Tableau, engagement activities accelerate and reinforce the vision for modern analytics, and ultimately, fuel your organizational transformation. Engagement activities are used to create and nurture an environment for more productive, results-driven people. Tableau Community Engagement defines types of activities to cultivate a thriving user community, including the internal user group meetings, knowledge transfer sessions, and competitions, as well as external community activities.
- Support — As your user base grows, it is critical to put the appropriate processes in place to efficiently and effectively support the user base. Tableau Support Processes defines the ways to support users with traditional helpdesk support requests, Data Doctor, champion development, and mentoring.
Developing a comprehensive plan and approach for each of the topics within these three workstreams will ensure that you are taking a holistic approach to accelerate company-wide adoption of data and analytics.