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A сomprehensive guide
to cloud business intelligence solutions
March 6, 2025
Cloud business intelligence solutions enable users to access, collect, analyze, and visualize business data through the internet, reducing the costs and complexities associated with on-premises BI infrastructures.
For 15+ years, Itransition has been providing business intelligence services to help companies across industries benefit from scalable cloud BI solutions, facilitating informed business decisions, fostering collaboration, and driving business growth.
Cloud BI solution deployment types
Public cloud
This model is based on multi-tenancy with multiple companies using data storage and computing power provided by the cloud vendor paying for the resources used.
Pros
This option is the most attractive for SMBs with limited funds or for companies that need to store and process large amounts of data.
Cons
Security concerns, such as lack of transparency regarding where your data is kept and who has access to it and the challenge of meeting specific data governance requirements in public clouds, can negatively impact business operations.
Public cloud providers
- Amazon Web Services (AWS)
- Microsoft Azure
- Google Cloud Platform (GCP)
- IBM Cloud
BI tools
- Microsoft Power BI (accessed through Microsoft Azure)
- Google Looker (integrated with GCP)
- Tableau Online (cloud version supports AWS, GCP, etc.)
- Amazon QuickSight (integrated with AWS)
Private cloud
According to this model, only one tenant uses the allocated cloud resources, so it resembles an on-premises solution in terms of autonomy and security.
Pros
The company doesn’t share the cloud computing power and storage capacity with others. This significantly increases the solution’s security and reliability, as well as the transparency of operations.
Cons
If the vendor maintains and manages a private cloud infrastructure of their BI solution, it usually costs more than using a public cloud. If it is the company that is responsible for infrastructure maintenance and customization, the solution requires considerable investment.
Private cloud providers
- VMware Cloud
- Red Hat OpenStack
- HPE GreenLake
- IBM Private Cloud
BI tools
- Power BI Report Server, MicroStrategy (supports deployment on a company’s private servers or in a private cloud)
- Qlik Sense Enterprise (can be deployed in private cloud environments)
- SAP BusinessObjects BI Suite (commonly used for private deployments within large enterprises)
Hybrid cloud
This model combines the possibilities and characteristics of those mentioned above, allowing companies to rely on multiple deployment models. In a hybrid cloud, solution components can be distributed between a private and a public cloud linked by middleware, APIs, and other connectivity solutions that ensure flawless communication and synchronization.
Pros
This model allows companies to keep sensitive data and critical assets in a private cloud and work with big data in a public cloud. This way they can increase data security and avoid vendor lock-in issues. Many companies view a hybrid model as their preferable option and include deploying a BI solution in the multi-cloud infrastructures into their IT strategy.
Cons
This model is only applicable if it makes sense to split data and operations between different types of environments for added security or operational flexibility. Additionally, it often requires more time, effort, and financial investments to manage a BI environment deployed across multiple clouds simultaneously.
Hybrid cloud providers
- Microsoft Azure (Azure Arc)
- Google Cloud Anthos
- AWS Outposts
- IBM Hybrid Cloud
BI tools
- Tableau Server (supports hybrid deployment, including across multiple clouds)
- Power BI Premium (can be configured for hybrid deployment)
- Domo (supports deployment in public and private clouds)
Community cloud
Within this model a specific group of companies share the cloud infrastructure and storage and, hence, the costs.
Pros
Lower costs. It’s a cost-effective option for companies from the same sector that have similar requirements in terms of cloud infrastructure security and governance that public clouds cannot meet.
Cons
Companies that share cloud resources must have shared data governance and usage protocols that are complex to establish and maintain. Plus, companies have to share storage, computing resources, and bandwidth, which can slow down the speed of operations.
Community cloud providers
- IBM Cloud for Government
- Microsoft Government Community Cloud
- AWS GovCloud
BI tools
- SAS Business Intelligence (widely used across governmental and educational sectors)
- Tableau Server
Real-life success cases
50%
increase in productivity
Cloud BI for vehicle manufacturers
Itransition re-engineered the customer’s legacy BI system, migrating their BI suite to a cloud-first, mobile-ready, microservices-based architecture and switching the service model to SaaS. The new solution helped the customer achieve a 100% predictability of business processes across teams in multiple locations and 70% faster time-to-market.
8%
conversion rate increase
AI-enhanced BI platform for a fashion retailer
Itransition delivered a cloud-based serverless solution hosted on Amazon Web Services (AWS) that helped gather and analyze massive amounts of data in near real-time while keeping the infrastructure costs low. It also featured AI-powered recommendation capabilities, enabling our client to provide tailored experiences for individual customers via a website and mobile app.
Ready to transform your business operations with a modern cloud BI solution?
Business intelligence solutions: selection guide
Choosing the right cloud-based business intelligence solution for your company is key to getting a positive return on investment. To find the best-fitting cloud-based BI software, pay attention to the characteristics listed below.
Ease of integration
When taking on decisions, businesses usually rely on multiple data sources, so your business intelligence software should be able to ingest data from all of them, be it your legacy system, third-party apps, CRMs, ERPs, and such. When you select a tool, pay attention to:
- The number of pre-built connectors the vendor currently offers and the availability of those you need.
- Data point limits. If there are any and you hit them, you will have to either pay for extending the limits or change the tool altogether.
- Available cloud data storage capacity and the rates for extra resources.
Visualization options
Data visualization is one of the essential features of the BI and analytics tools. Business users shouldn’t
struggle through endless spreadsheets of dry data. Modern cloud-based self-service BI solutions make
analytical insights easier to read, which helps identify patterns and trends that might be difficult to see
otherwise.
Therefore, cloud platforms should feature rich data visualization capabilities. Look for a tool that enables
users to mix and match data visuals, like charts, graphs, and maps. Even better if the tool allows you to customize
the visualization without the need to code, like dragging-and-dropping or adding forecasting lines and confidence
intervals to your charts.
Self-service capabilities
Data democratization and collaboration must become corporate standards to allow all business users to interpret data and make data-driven decisions. In addition, cloud business intelligence tools enhanced with artificial intelligence capabilities enable users to ask questions in natural language and receive replies as visuals. If you want to nurture data culture in your organization with the help of self-service BI solutions, look for the tools with:
- An intuitive user interface, preferably supplemented with NLP capabilities
- Drag-and-drop tools
- Easy-to-use customizable dashboards and dashboard templates
- Dynamic data modeling for modifying, extending, and exploring data without additional coding
- Augmented analytics functionality
- A learning portal for mastering new skills independently
Ad-hoc reporting
This feature enables team members with varied technical backgrounds to quickly create role-specific reports when needed and share them on the fly, which fosters data-powered decision-making. This allows employees to use real-time data to get necessary insights in record time, optimizing the resource usage.
Best cloud BI platforms
Features
- Accessing over 100 data sources, including Salesforce, Excel, Google Analytics, and Microsoft Dynamics 365, through pre-built connectors and APIs
- Seamless integration with Azure Data Lake Storage Gen2, Azure Synapse Analytics, Microsoft Azure SQL database, Azure Machine Learning Studio
- DAX, Power Query, SQL, R, and Python support for in-depth data analysis
- Self-service data preparation, analysis, reporting, and visualization
- Intuitive visual-based data exploration
- Ready-made and custom visuals
- Data storytelling and advanced analytics capabilities
- Querying data using natural language
- Team collaborations and content subscriptions
- Robust security features, including row-level security with role-specific data protection and row-level security measures
- Mobile support
- Embedded BI
- Augmented analytics capabilities
Pricing
- Power BI Desktop
free - Power BI Pro
$10 per user/month - Power BI Premium
$20 per user/month - 2-month
free trial for each new user
Features
- Connectors to 80 data sources, including local files, spreadsheets, relational and non-relational databases, data warehouses, big data, and cloud-based data sources
- Self-service data preparation, analysis, and reportings
- Collaborative tools
- Drag-and-drop interface for simplified dashboard creation
- NLP capabilities
- Row-level security
- Mobile support
- Embedded analytics capabilities
Pricing
- Tableau Creator
$75/user/month - Tableau Enterprise Creator
$115/user/month - Tableau Explorer
$42/user/month - Tableau Enterprise Explorer
$70/user/month - Tableau Viewer
$15/user/month (fully hosted by Tableau) - Tableau Enterprise Viewer
$35/user/month - 2-week free trial
Features
- Native SQL-centered data source integration (Google BigQuery, Snowflake, and Amazon Redshift)
- Custom data analytics models
- Predictive analytics and big data services
- Embedding analytics content into corporate applications
- Pre-analysis of raw data with LookML
- Self-service BI capabilities
- Various visualization options, including charts, graphs, scorecards, and dashboards
- Scheduled and ad-hoc reporting
- Team collaboration and sharing
- NLQ interface
- Mobile capabilities
- Robust security capabilities, including authentication, activity tracking, access controls to databases, rows and/or columns, role-based permissions
Pricing
- Available
upon direct request - Free trial
Features
- Pre-built connectors to file-based, on-premises, cloud-based, and web sources
- Self-service AI-powered data preparation, analytics, and reporting
- Automated visual recommendations and data storytelling capabilities
- Intuitive drag-and-drop report and dashboard creation
- In-team sharing and collaboration
- Support for multiple types of users
- Natural language interface
- Row- and column-level security
- Mobile support
- Embedded analytics capabilities
Pricing
- Standard plan
from $825/month - Premium plan
from $2,500/month - Enterprise plan
custom pricing available upon request - Free trial
available
Benefits of cloud BI solutions
Compared to on-premises BI solutions, cloud BI offers a long list of advantages, including faster implementation and enhanced scalability, accessibility, and data democratization, which makes it a perfect choice for companies looking for a competitive advantage.
Faster deployment & adoption
Сloud BI apps usually pose fewer adoption barriers for end-users than on-premises solutions because they require neither buying, installing, and maintaining on-premises servers, nor local setup or dedicated IT infrastructure. Additionally, with SaaS BI solutions, companies can often try out the solution using free trials or free editions before committing to it.
Scalability & flexibility
Cloud BI services allow for a quick expansion of storage capacity, computing power, or functionality to support the company’s growth and accommodate a larger number of users. Similarly, if a company no longer needs certain storage or features, it can scale down and pay only for the resources it uses.
Data democratization
Cloud BI software with sophisticated visualization and self-serving capabilities makes data available to all users regardless of their location, giving them tools to interact with it in different ways and adopt such concepts as data storytelling or mobile BI. Though on-premises solutions can offer similar features, cloud-based tools usually realize them better due to their ultimate accessibility and agility.
Better data accessibility & collaboration
Cloud solutions can easily connect to multiple data repositories and allow authorized users to access the required data on demand via any device from anywhere in the world. What’s more, cloud software creates an environment where remote teams can explore data side by side, share insights, streamline reporting, and engage in collective decision-making to reach common ground for critical or ambiguous issues.
Competitive edge enablement
BI tools are usually maintained by service providers, requiring significantly less effort and expenses from the organizations than on-premise software. They are also continuously updated to incorporate top-notch technical capabilities. Organizations can leverage such updates to implement innovative technologies into their processes and gain a competitive advantage in their market.
Cloud BI implementation challenges
Implementing cloud BI platforms often poses a substantial challenge to organizations. It’s best to learn the most common obstacles to BI tool adoption and cost-effective strategies to overcome them before the implementation process starts.
|
Companies that previously relied on an on-premises BI solution and still use a number of on-premises tools
and services must integrate a new cloud BI solution with their IT ecosystem and transfer large volumes of
business data to the cloud, which is a complex operation.
| Use ETL tools and data integration platforms to automate datasets’ ingestion and transformation. Adhere to data governance best practices to ensure security, consistency, and minimal disruption of your workflows during migration. This will help you make the transition process more smooth and ensure full integration of your cloud BI solution into your company’s IT ecosystem. |
|
Secure data management is a priority for many organizations, especially in the financial or healthcare
fields. Storing such data in the cloud can raise concerns about potential data breaches.
| Cloud-based BI platforms and data repositories aren’t necessarily less secure than on-premises ones. Implement a BI solution with security measures that go beyond traditional capabilities like encryption and access controls to keep your data safe. For example, employ data masking to hide sensitive information. Additionally, prepare an emergency response plan in case of unexpected data breaches or other security threats. |
|
While many cloud-based business analytics tools help reduce the upfront infrastructure management costs,
some pricing models cloud BI vendors offer can turn up unexpected expenses.
| Evaluate different pricing models before committing to a particular solution. BI solution consultants can help you get a comprehensive view of future expenses, including potential hidden costs. Use cost-monitoring tools to optimize your spending within the pay-as-you-go model, and consider prepaid or reserved instances for predictable workloads. |
Our cloud business intelligence services
Consulting
We help companies maximize the value of their BI investments by developing BI roadmaps, designing solutions, selecting optimal technology, and assisting with data governance frameworks setup.
Implementation
We handle every step of the implementation process for companies that need to adopt a comprehensive cloud-based BI solution: from initial business needs analysis to successful implementation.
Development
We build custom BI solution components and comprehensive custom cloud business intelligence systems to help companies cover their specific business needs and non-trivial data management requirements.
Facilitate data-driven decision-making with cloud BI software
Cloud BI solutions are an effective tool that can help companies derive valuable data insights from their data
and succeed in the modern market. This type of software fosters a data-driven organizational culture by making
data accessible to distributed teams and allowing companies to focus on their core activities instead of wasting
time and resources on IT infrastructure maintenance.
Turn to a reliable implementation partner like Itransition to ensure your BI software implementation success, regardless
of whether you’re opting for a ready-made or custom BI solution.
Need assistance with your cloud BI solution implementation?
FAQs
Cloud BI tools can still be considered “traditional”, thus it’s incorrect to compare the two. However, we can compare the traditional BI solution to the self-service tools which emphasize real-time processing of data and interactive analytics. It’s true that many self-service BI solutions have a cloud-native architecture, but not exclusively. On-premise BI tools can have self-service capabilities as well, depending on the solution.
Cloud BI use across various industries depends heavily on the industry’s specifics. In healthcare, for example, it is used to analyze patient data to improve diagnosis and treatment outcomes. In finance, it helps detect fraud and optimize investment portfolios. All in all, it can also be used to derive actionable insights that help personalize clients’ experiences and increase the efficiency of the company’s business operations in most industries.
SaaS BI is a sub-type of cloud BI. While cloud BI simply refers to hosting BI tools and services on external servers, SaaS BI means that the solution is provided on a subscription basis. Users can access the software’s features via the internet while they pay for it, and the provider handles everything for them, from routine upgrades to urgent bug fixes.
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