1. Solution Value
Business intelligence (BI) enables organizations to take reams of transactional data and discover patterns, trends, and otherwise hidden information about the organization. Business users can take advantage of these capabilities on a self-service basis, regardless of technical skill level. As such, BI enables data-driven decision-making, increasing the organization’s overall competitiveness.
Vendor-managed cloud BI can improve time to value, eliminate administration costs, and reduce deployment hassles compared to on-premises or self-hosted BI platforms. Rather than having to size, procure, and manage servers or worry that further BI adoption in the organization will overwhelm the deployed infrastructure, customers can get what they need on-demand under the management of the vendor.
Another benefit is the ease with which new platform features can be adopted. Rather than the customer deploying new versions as they are released—or dealing with the user dissatisfaction that arises when older versions are not updated—new releases are deployed automatically by the BI vendor. Providing consistently high performance becomes the vendor’s job by scaling the infrastructure as needed, easing the administrative burden on the customer.
2. Urgency and Risk
For organizations using BI to run their business in a data-driven fashion, using self-hosted software and self-managed infrastructure–whether on-premises or in the cloud–is no longer the mainstream approach. Taking on this burden can invoke hardware and personnel expense, forcing organizations to choose between the disruption of frequent software deployments or missing out on new capabilities, causing a competitive disadvantage. Organization-wide analytics and data-driven operation are critical, and software-as-a-service (SaaS) BI facilitates it best. Any organization dedicated to self-service analytics must clear the hurdles that on-premises or self-hosted deployment presents.
Risks exist with any migration, and mitigation is essential to seamless operation. Measures that must be taken to avoid discontinuity include configuring on-premises data sources for access by cloud-based BI and being aware of the differences between single-tenant infrastructure with core-based licensing and multi-tenant infrastructure with per-user licensing. Users also need to expect new versions and features to roll out with every version release rather than in big, infrequent upgrades.
BI should be treated as a consumable service rather than a self-managed product. Just as electrical customers no longer generate their power and instead pay public utilities for it as a service, SaaS BI lets organizations focus on using their BI platform for the advantages of data-driven operation without feeling encumbered by the hassles, risks, expenses, and complexities of installing and managing it. Tableau Cloud invokes a range of benefits, all of which increase time to value:
- Reduced capital expenditure, as most costs become regular, manageable expenses
- Lower administration costs, with Tableau managing the infrastructure and guaranteeing uptime
- Better performance, with Tableau implementing and optimizing the compute environment
- Streamlined adoption of new releases, as these are deployed on an implicit, slip-stream basis
4. Best Practices
Rather than “lift and shift” self-hosted deployments to the SaaS-based cloud, most customers use cloud migration as an opportunity to optimize, take advantage of the newest platform features, and implement data governance. In the case of Tableau Cloud, organizations should consider:
- Expanding automation processes to reduce overhead and streamline data access.
- Taking advantage of the latest AI features, like Tableau’s Ask Data, Explain Data, and Salesforce Einstein Discovery in Tableau.
- Driving a data culture by identifying specific users as champions to promote user enthusiasm, centralizing Published Data Sources or Virtual Connections, and removing stale or unused content.
- Optimizing discoverability of retained content and improving permissions structure.
Post migration, it’s important to acclimate users and help them further implement the changes in environment resulting from the above initiatives. These changes include a new governance structure and reworked content access, as well as new projects, user groups, and permissions.
5. Organizational Impact
On-premises, self-hosted, and SaaS cloud BI deployments may all utilize the same software, but in shifting from one of the first two to the third, policies and modes of usage will change, and these changes should be planned for. This is especially true for organizations that have adopted cloud computing in other domains. For example, single sign-on (SSO) arrangements for organizational users with cloud provider accounts should be implemented. A shift towards cloud-based operational databases should be considered along with migrating to SaaS BI.
The move to user-based billing (versus core-based pricing) may require organizational chargeback measures. This shift in billing basis may require changes in user behavior. For example, certain users may no longer merit access to the BI platform. Conversely, broader availability, with access for more users, may be warranted now that it no longer invokes new infrastructural or managerial costs. More widespread access will, however, invoke training needs, which should be planned and budgeted for proactively.
The impact on team members is limited, as the software, its user interface, and its capabilities remain essentially unchanged. In the cloud world, however, newly developed product features roll out frequently rather than within occasional upgrades, which requires a change in training strategy. Rather than synching time-limited training efforts with these infrequent rollouts, more routine training will need to be provided.
Also, with the move to user-based licensing, departmental usage may need to be metered by a central IT or analytics group, along with commensurate departmental chargebacks to ensure cost loads are distributed equitably.
Customers should plan on taking a variety of approaches to training and raising awareness of new platform capabilities, including:
- Continuous, sustained training efforts.
- Providing training through different methods and media, including feature-based “snackable” video vignettes.
- Encouraging peer-based training within business units, with supporting collateral and assets.
- Leveraging telemetry to determine the most popular features as well as useful features that may not be heavily adopted.
- Gamification and contests for creative use or promotion of new BI functionality.
Customers with less than 100 users often choose to self-migrate, making their cost a function of hours spent and opportunity costs. Larger customers often work with vendor professional services teams or systems integrators (SIs), where fees vary, to handle their migrations.
Post-migration, annual costs may well go down. A baseline Tableau Server implementation involving five creators and 100 viewers invokes a total annual spend of $40,600* (USD), including licensing, hardware, and administration costs. For initial comparison, an equivalent Tableau Cloud implementation requiring Tableau Bridge for integrating on-premises data sources carries an annual cost of only $35,200, yielding a conservative total cost of ownership (TCO) reduction of 13.30%. Larger customers requiring this configuration will also likely save on hardware, although typical savings come from reduced overhead.
A more dramatic comparison involves the cost of an equivalent Tableau Cloud implementation without Tableau Bridge. Such a configuration would cost $25,200 annually, representing a sizable 37.93% TCO reduction over the baseline Tableau Server implementation.
Larger organizations like Splunk report greater cost savings (upwards of $300,000) in reduced overhead from shifting to a SaaS deployment. It’s also common for companies like F5 to see not only reduced overhead but a significantly faster analytics adoption due to enhanced agility and security provided by a SaaS offering. No longer limited by infrastructure requirements, organizations can take advantage of new features faster and be more agile without concern for performance impacts that otherwise prohibit innovation.
Licensing is per-user/per-month (billed annually) with role-based differentiated pricing for those using Tableau Viewer, Explorer, and Creator. Creator licenses include access to Tableau Desktop and Tableau Prep Builder, in addition to Tableau Cloud. Embedded analytics allows developers to provide their own customers, who may not have Tableau licenses, use of Tableau functionality within those developers’ applications licensed on a usage-based or per-user basis.
As a SaaS product, Tableau Cloud can be activated immediately, compared to complex setups in self-hosted scenarios. Compared to on-premises use cases, Tableau Cloud also avoids supply chain-related delays that may be involved in provisioning servers and storage.
*Assumes $10,000 annual cost to host Tableau Server or Tableau Bridge on a virtual machine and an average of 3 FTE hours per week no longer spent managing Tableau Server. Customer costs may vary.
6. Solution Timeline
Migration timelines are determined by user, data source, workbook, site counts, and governance rework needs. SMB customers often complete migrations in as little as three to four weeks. For larger organizations, the majority of migrations are completed within four months.
Plan, Test, Deploy
Many customers implementing Tableau Cloud will be migrating from self-hosted deployments rather than implementing from scratch. This will accelerate plan/test/deploy cycles significantly. Below are thoughts on each phase with these circumstances in mind.
- Plan: This phase will hinge on facilitating user authentication in the cloud and assuring continuity of access to all data sources, including those on-premises.
- Test: A prudent risk-mitigating approach to testing involves pilot migrations with particular business units or groups of users.
- Deploy: Once successful pilot migrations have been implemented, other user groups and business units should be onboarded to the SaaS BI platform, proceeding cautiously, then accelerating rapidly to onboard the rest of the organization.
Ongoing Deployment: Depending on the organization, cloud migration may facilitate a broader deployment of the BI platform than was pursued when it was self-hosted. As such, a phase for onboarding brand-new users, in addition to the initial migration deploy phase, should be planned and budgeted.
Looking forward, Tableau has new capabilities in the near-term pipeline for customers, combining generative AI, headless BI, and more. Coming improvements include:
- Tableau GPT: A suite of capabilities that bring generative AI to Tableau, simplifying and democratizing data analysis and insight consumption at scale. Tableau GPT reduces repetitive tasks for the data analyst with smart suggestions and in-product guidance while maintaining data security and privacy.
- Tableau Pulse: A reimagined data experience for analytics consumers with personalized, contextual insights delivered directly into their flow of work, enabling data-driven work. Pulse will enable consumers to receive personalized metrics that are easy to understand and act on, will automatically generate insights in plain-language format, enable on-demand exploration, and accelerate data model and dashboard creation so that organizations can deliver analytics at scale.
- VizQL Data Services: A data product programming layer that will sit on top of customers’ published services and dashboards. Applications include automated business workflows or chatbots that can, in turn, integrate Tableau analytics.
Migration to Tableau Cloud will enable organizations to take advantage of these cutting-edge capabilities more quickly than remaining on Tableau Server would allow. Tableau Cloud enables Tableau to innovate faster and facilitates customers’ faster adoption of those innovations.
7. Analyst’s Take
Cloud BI offers a fast track to data-driven operations through enriched insight and faster and better decision-making. This acceleration is due to vastly reduced complexity in setup and operations, lower costs for the software itself, and streamlined overhead due to simplified administration.
Tableau is using generative AI to enlarge the BI tent, enabling people in more roles not only to explore and analyze their data, but to build bona fide data products for internal users and their customers. Tableau Cloud allows organizations to roll out BI capabilities to more people in more roles more quickly than has been possible with self-hosted BI. With Tableau Cloud, organizations can shift their focus from the logistics and complexities of deploying and updating software to the application of BI and data-driven practices to their business.
8. Report Methodology
This GigaOm CxO Decision Brief analyzes a specific technology and related solution to provide executive decision-makers with the information they need to drive successful IT strategies that align with the business. The report is focused on large impact zones that are often overlooked in technical research, yielding enhanced insight and mitigating risk. We work closely with vendors to identify the value and benefits of specific solutions, and to lay out best practices that enable organizations to drive a successful decision process.
9. About Andrew Brust
Andrew Brust has held developer, CTO, analyst, research director, and market strategist positions at organizations ranging from the City of New York and Cap Gemini to GigaOm and Datameer. He has worked with small, medium, and Fortune 1000 clients in numerous industries and with software companies ranging from small ISVs to large clients like Microsoft. The understanding of technology and the way customers use it that resulted from this experience makes his market and product analyses relevant, credible, and empathetic.
Andrew has tracked the Big Data and Analytics industry since its inception, as GigaOm’s Research Director and as ZDNet’s original blogger for Big Data and Analytics. Andrew co-chairs Visual Studio Live!, one of the nation’s longest-running developer conferences, and currently covers data and analytics for The New Stack and VentureBeat. As a seasoned technical author and speaker in the database field, Andrew understands today’s market in the context of its extensive enterprise underpinnings.
10. About GigaOm
GigaOm provides technical, operational, and business advice for IT’s strategic digital enterprise and business initiatives. Enterprise business leaders, CIOs, and technology organizations partner with GigaOm for practical, actionable, strategic, and visionary advice for modernizing and transforming their business. GigaOm’s advice empowers enterprises to successfully compete in an increasingly complicated business atmosphere that requires a solid understanding of constantly changing customer demands.
GigaOm works directly with enterprises both inside and outside of the IT organization to apply proven research and methodologies designed to avoid pitfalls and roadblocks while balancing risk and innovation. Research methodologies include but are not limited to adoption and benchmarking surveys, use cases, interviews, ROI/TCO, market landscapes, strategic trends, and technical benchmarks. Our analysts possess 20+ years of experience advising a spectrum of clients from early adopters to mainstream enterprises.
GigaOm’s perspective is that of the unbiased enterprise practitioner. Through this perspective, GigaOm connects with engaged and loyal subscribers on a deep and meaningful level.