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Cloud business Intelligence: Is it the right approach for your business?
Cloud computing has reshaped the service delivery map for countless technologies. The cloud provides easy, on-demand access to these technologies, minus the need for upfront investment in, or ongoing maintenance of, the underlying infrastructure. And in an era of near-continual financial belt-tightening, it’s little wonder that convenience and ready-made budget controls are proving so popular.
The business intelligence (BI) market is no exception. Globally, the BI software market was valued at $35.13 billion in 2023 and is projected to reach $64.74 billion by 2030. Meanwhile, the market size for cloud BI tools is estimated to be $17.2 billion by 2030.
The big choice for many companies when picking a BI tool is between a traditional on-premises deployment or cloud BI?
Determining whether deploying in the cloud is the right option for your BI strategy comes down to specific needs, budgets, timescales, resource availability and accessibility preferences. The remainder of this article should help you make a more informed decision about whether cloud BI is right for you.
And whether you choose a cloud or on-premise BI solution, Process Intelligence should be next on your list of enterprise solutions to examine. Where BI provides detailed insights about historical and current business performance, Process Intelligence can help pinpoint the root causes of these trends and suggest the most effective ways to optimize processes. It can even simulate the likely future impact of process changes and help orchestrate automated process improvements. Simply put, Process Intelligence helps transform insights from ‘actionable’ to ‘actioned.’
The remainder of this article should help you make a more informed decision about whether cloud BI is right for you and whether your business might benefit from deploying it alongside Process Intelligence.
What is cloud business intelligence?
Cloud business intelligence refers to the delivery of actionable insights to support informed decisions using cloud infrastructure rather than traditional on-premises BI software or hardware. The data storage and data processing, along with the platform for data analytics and visualization, are hosted and managed by the cloud BI vendor – rather than within the organization's tech stack. Cloud BI tools are accessed via a web or mobile interface and are therefore accessible from anywhere with an internet connection. There is no requirement to be ‘at the office’ or to remote login via a business’s secure VPN.
Like other SaaS (software-as-a-service) implementations, cloud BI solutions typically offer scalable, flexible ‘pay for what you use’ access to pre-packaged tools and technologies. However, while there are arguments as to the relative merits between cloud business intelligence tools and their on-premises counterparts (discussed below), ultimately their key outputs are comparable.
Check out this comprehensive review of BI and its benefits.
How does cloud business intelligence work?
With on-premises BI you are primarily responsible for establishing, managing and optimizing BI systems and infrastructure. Should you opt for a cloud BI solution, these burdens pass to the service provider.
Organizations using a cloud BI tool progress through a set of core steps toward insight generation.
Data integration: The cloud BI software connects and collects user-selected data from across the organization’s tech stack – from internal applications and spreadsheets to third-party integrations such as CRMs or ERPs. This data is consolidated within a centralized cloud environment ready for processing, cleansing and alignment – increasingly with the help of artificial intelligence (AI) systems to accelerate the process.
Data transformation and storage: Before it’s ready for data analysis, the consolidated business information has to be cleansed, put in a standardized format and loaded into the BI model. To do this, cloud BI tools typically carry out an ETL process (that extracts, transforms, and then loads the data) or an ELT process (which extracts, loads and then transforms the data within the cloud storage environment). The aligned, cleansed data is stored in a cloud data warehouse or data lakehouse environment using a format that supports optimized analysis and easy scalability.
Data analytics and visualization: Cloud business intelligence platforms provide the business user with the tools to explore the data, generate insights and bring them to life. Stakeholders can dig into the data, filtering and querying it to gain greater understanding of business performance. A cloud BI tool also typically provides advanced analytic functionality to help uncover trends and connections between datasets. All of these insights can be shared across the business via extensive BI reporting options and visualizations.
User collaboration: A cloud business intelligence tool makes it simple not only to share insights between users, but also for users to engage in real-time BI collaborations. Cloud infrastructure enables anywhere access to the BI solution and shared datasets – putting multi-department, multi-location collaboration within easy reach.
The different cloud deployment models
Within the broader definition of cloud business intelligence, there are three main types of cloud in which a BI tool and all source data can be accommodated:
Public cloud: A public cloud environment is managed by a cloud service provider (such as Amazon Web Services (AWS), Google Cloud Platform or Microsoft Azure) and shared by several separate cloud ‘tenants’ – including, in this instance, the cloud BI tool. Public cloud deployments tend to be more economical as the cost is shared between the tenants.
Private cloud: A private cloud deployment is typically preferred by businesses with particularly strict data security or regulatory requirements. With this model, the cloud business intelligence platform is hosted within a dedicated cloud environment – either within the organization’s own data stack or externally. While more expensive, a private cloud typically offers a greater level of BI infrastructure control, data storage and customization options.
Hybrid Cloud: A hybrid cloud allows organizations to draw upon the benefits of both the private and public cloud models. Any sensitive BI data can be stored and analyzed within the private cloud environment, with the remainder hosted in the more cost-effective public cloud.
Any conversation with a cloud BI vendor should include confirmation of their ability to provide business intelligence services across your preferred cloud models.
The benefits of cloud business intelligence
A cloud BI solution offers organizations of all sizes a BI platform that’s purpose-built to evolve alongside business needs. Some of the main reasons for opting for cloud business intelligence over on-premises solutions include:
Faster to deploy, faster to insight
With the key infrastructure already set up by the cloud BI provider, no hardware to install and no networks to configure, cloud solutions can be up and running a lot faster than on-premises alternatives. This, plus cloud BI’s tendency towards intuitive interfaces offering numerous self-service options (a growing BI trend), can shorten the time from data processing to actionable insights.
Lower upfront costs
With cloud business intelligence solutions the immediate financial commitments are much lower than with an on-premises BI platform. This is because there’s no need to purchase new equipment or hire new personnel. The infrastructure, software and maintenance is all managed by the BI provider.
Competitive leveling-up
While on-premises options can be prohibitively resource draining for smaller businesses, the lower upfront costs and outsourced infrastructure management common to cloud computing allows companies of all sizes access to BI tools. This enables them to compete on a more level playing field with larger rivals, by leveraging business intelligence insights.
Flexibility and scalability
A cloud business intelligence solution can flex according to the changing demands of its users. Whether it’s a surge in demand for BI insights or a sudden shift in market dynamics, Cloud BI platforms are built to scale up (or down) without compromising service standards or investment in new hardware.
Easy to use
Cloud BI solutions tend to deliver intuitive out-of-the-box user experiences. As there is much less configuration for individual business requirements, cloud BI relies on a broad appeal to businesses with a range of needs. Cloud interfaces tend to be designed for simplicity of use and quick results for a wide cross-section of business users (not just data scientists). This allows non-technical users to be up and running in no time, querying the data, building reports, dashboards and data visualizations.
Easy access, easy collaboration
If a BI system resides in the cloud, it’s available everywhere to anyone with an internet connection. It’s also accessible and on any type of device, including mobile. This allows for easy access and frictionless, collaborative insight generation across teams irrespective of location or function.
Automatic maintenance, automatic R&D
With cloud BI, service providers are responsible for ensuring maximum platform availability, and addressing any maintenance requirements (including bug fixes and applying security patches). These fixes are applied automatically, with little or no need for intervention by internal IT teams. Beyond that, cloud BI vendors are compelled to ensure their platforms evolve to adopt new approaches and new technologies in order to stay competitive with rivals.
Organizations using a cloud business intelligence system benefit from their provider’s research and development programs. Software updates and new platform features (for example applications of machine learning and predictive analytics) get rolled out to all business users as they are developed.
Improved data visibility
With cloud BI, the core unified dataset, along with all data visualizations and reports, remain visible to business leaders. They can rely on all business intelligence being drawn from the approved, cleansed, up-to-date information and have a comprehensive view of all BI activity and outputs. With desktop, on-premises BI, it’s possible for business intelligence silos to form and for overall BI visibility to be lost.
For example, where users download data to their own devices it becomes difficult for IT teams to track how it is being used. This can lead to the gaps in the certification status of BI outputs – whether reports are using the latest information, whether the data is still accurate, or whether it has been collected and used in a compliant manner.
Cloud business intelligence challenges and considerations
There’s a lot to recommend cloud BI, particularly for organizations making their first forays into business intelligence. However, there are also some potential downsides to the model, or at least considerations to keep in mind, including:
Total cost of ownership
There’s no question that cloud BI solutions levy lower upfront fees than on-premises options. However, with on-going subscription fees or pay-as-you-go charges plus the potential for growing data storage costs, a cloud based business intelligence solution may not be cheaper in the long term. You need to decide whether total cost of ownership or short-term cash flow is the more compelling financial motivation when implementing BI.
Control and customization
Cloud platforms offer less opportunities to tailor BI configuration to specific business requirements. The downside to speed of deployment is an absence of customer control over the infrastructure, reporting or service level agreements – cloud BI is often harder to customize. This makes it particularly important to verify that a cloud BI solution is able to integrate with your various data sets and offer reporting capabilities you require before committing to it.
Security and compliance
Careful due diligence is also essential before committing sensitive data to the cloud. While cloud data security has advanced rapidly, it’s vital to ensure that your cloud BI provider adheres to strict security protocols and is compliant with all data regulations (such as GDPR or the CCPA).
Vendor lock-in
With cloud BI, your data, reports, and applications become more intertwined with the specific cloud provider’s ecosystem and proprietary technologies. This increased reliance on the vendor can make it more difficult, expensive and disruptive to switch cloud BI providers down the line. Being locked-in like this makes it hard to respond to, for example, price hikes or any deterioration in service standards. There are a number of steps you can take to diminish these risks, such as:
Adopting a multi-cloud or hybrid cloud solution (which reduces dependence on an individual provider and increases the opportunity to tailor cloud BI provision to individual needs).
Extensive due diligence on providers and your organization’s current and potential future needs. Seek out testimonials and case studies from comparable companies as well as evidence of on-going investment in emerging technologies (like AI).
Discuss an exit plan with your cloud BI provider before you commit to them, ask how they manage easy vendor transition should it become necessary (including provision of data backups).
Consider selecting a cloud service provider that employs open rather than proprietary standards (tied to their own technology). Open standards are technical specifications that are publicly available and not controlled by any single vendor.
Dependence on internet connectivity
Cloud BI relies on reliable, fast internet connectivity. Any disruption to online access or significant reduction in speeds can leave your BI function either completely or partially inoperable. The increasing availability and reliability of internet connectivity makes this arguably less of a concern than in the past.
All good options
Cloud BI versus on-premises BI is not the Jets versus Sharks or Jedi versus Sith, the past versus the future. Each approach draws together disparate business data sets into a single interrogatable resource capable of producing business-wide reports, dashboards, and visualizations. Each democratizes the availability of business data. Each offers a solid data analytics foundation, creating an accessible forum from which to identify and address business performance trends.
Each approach also benefits hugely from the additional deployment of Process Intelligence. The Celonis Process Intelligence Graph uses object-centric process mining (OCPM) technology to extract process data from organizations’ IT systems to create a living, breathing digital twin of an organization’s processes and how they interact with each other. Then, standardized process knowledge and best practices are combined with this process digital twin, providing the optimal platform for process optimization and business value creation.
If you are in the process of building or updating your business intelligence systems, here are some other useful resources to help you land on the right solution:
10 trends that will shape the future of business intelligence
Business intelligence reporting: All you need to know to start right now
What is Business Intelligence and how can process intelligence maximize BI's value?
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