What is Cloud Business Intelligence?: 5 Critical Points

• November 29th, 2021

Feature Image - Cloud Business Intelligence

Businesses today, store and generate vast volumes of data from which they can obtain actionable insights using Business Intelligence (BI) for faster and better decision-making. The diversity and complexity of this data necessitate the development of efficient and cost-effective data analytics. Cloud Data Warehouses and Cloud BI Technologies are increasingly being used to solve such problems.

In this article, you will be introduced to Cloud Business Intelligence and its advantages. Different Deployment Models for Cloud Business Intelligence and some popular Cloud BI softwares will be explained. 

Table of Contents

What is Cloud Business Intelligence?

Cloud Business Intelligence refers to the deployment of Business Intelligence tools over Cloud Infrastructure which can then be accessed using virtual networks including the Internet. 

They are used to provide firms with business intelligence data such as dashboards, KPIs, and other types of Business Analytics. There are three qualities that distinguish a Cloud service from regular web hosting which are, the Cloud is sold on demand, it is elastic, and the Cloud services are totally handled by the provider. Users’ interest in Cloud Computing has grown as a result of advances in virtualization and distributed computing, as well as greater access to high-speed internet.

Cloud-based technologies such as Customer Relationship Management (CRM) systems (Salesforce), online file collaboration and storage (Dropbox, Box), and help desk software are becoming increasingly popular among businesses (UserVoice, Zendesk). Business intelligence technologies that embrace the Cloud’s agility and accessibility are part of this trend. The Cloud Business Intelligence Applications are accessible through a variety of devices and web browsers.

Key Advantages of Cloud Business Intelligence

Cloud Business Intelligence offers some significant advantages over on-premise applications. Some of them are mentioned here: 

  • Cost Effective: In the case of Cloud Computing, businesses do not require a large-scale, up-front hardware and software acquisition budget. Companies regard BI infrastructure as a service, paying only for the computing resources they require, avoiding the costs of asset acquisition and maintaining a lower entry barrier.
  • Scalability of Deployment: Cloud Business Intelligence solutions have given technical users immense flexibility that can be adjusted fast, allowing them to access additional data and processing resources while experimenting with the analytics model. Furthermore, by enabling a large number of concurrent users, Cloud resources may seamlessly and quickly scale in and out. Customers can easily expand software consumption without having to wait for additional hardware or software to be installed.
  • Easier Setup and Operation: End-users find Cloud BI solutions, like other Cloud applications, simple to use and set up. As a result, IT involvement and expenditures are decreased. Users can easily deploy a cloud BI solution using internet-based software instead of waiting for overworked IT professionals to arrive.
  • Reduced Overhead Expenditure: One of the main advantages of the Cloud model is its cheap TCO [Total Cost of Ownership]. Companies can use the cloud to only pay for services that are actually used. Cloud Computing, as a result of this approach, allows businesses to better regulate the CAPEX and OPEX associated with non-core activities. The number of on-site servers and employees required to operate day-to-day operations is reduced with Cloud solutions. Expenses that were previously allocated to IT can now be applied to other areas of the business.
  • Advanced Data Sharing: Cloud computing apps allow data to be accessed and shared remotely, as well as across locations in a seamless manner. These are typically deployed over the Internet, and they remain outside the company’s firewall.
  • Improved Reliability: The use of numerous redundant sites can improve reliability by offering reliable and secure data backup storage places. Because these resources may be shared among several users, Cloud Computing is an excellent choice for disaster recovery and business continuity.

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What is the need for Cloud Business Intelligence?

  • Businesses of all sizes desire to improve their business workflows and increase the value of their strategic decisions. That is exactly what business intelligence enables them to do. BI enables the appropriate people to obtain the right information at the right time, in the appropriate format.
  • Cloud Computing, on the other hand, is gaining great popularity as a result of technological advancements and has evolved from technological innovation to a commercial imperative.
  • Until a few years ago, Cloud-based Business Intelligence was mostly employed by startups and small businesses that couldn’t afford to deploy expensive BI systems. However, as businesses of all sizes have begun to embrace Cloud Computing for their business intelligence plans, Cloud BI has become commonplace.
  • Cloud-based business analytics brings together two of the most powerful business tools. When businesses need to gather data from a variety of devices and sources – anytime and anywhere – Cloud Computing serves as a storehouse for massive volumes of data and creates an ideal platform for providing business intelligence applications.
  • Cloud Computing has considerable scalability and flexibility, making it a great complement to corporate information solutions.
  • Cloud Computing acts as a storehouse for both Structured and Unstructured data, making it a perfect platform for delivering data to business intelligence applications from a variety of devices at any time and from any location. The Cloud’s scale and versatility make it excellent for business intelligence efforts.

Through the use of storage, networking, and tools that can sift through huge data; the cloud’s “democratization” is now allowing enterprises that have employed business intelligence with on-premises applications and on a restricted scale to reach a whole new level (coupled with analytics capabilities).

Many firms are unable to staff or master the complexity required to run a BI infrastructure; however, with the Cloud, these businesses can delegate the operation and management of the infrastructure as well as the business intelligence applications to their service provider. When compared to On-Premises infrastructure, this can be a more cost-effective and better means to share information.

What are the various Cloud Business Intelligence Deployment Models?

A Cloud-based Business Intelligence solution can be deployed using these 3 Cloud types:

1. Public Cloud

Public Cloud Illustration - Cloud Business Intelligence
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The infrastructure expenditures of a Public Cloud are shared across Cloud tenants, making it the most cost-effective alternative for Cloud BI. It’s an excellent choice for small and mid-sized enterprises on a tight budget or those working with large data sets.

2. Private Cloud

Private Cloud Illustration - Cloud Business Intelligence
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It is recommended to deploy a BI system in a private cloud if you’re concerned about regulatory compliance or data security. The private cloud is the most expensive cloud option and provides dedicated storage and computation resources solely for your company’s use.

3. Hybrid Cloud

Hybrid Cloud Illustration - Cloud Business Intelligence
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A hybrid cloud is a way to go if you can’t afford to put your entire BI system in the Private Cloud but must adhere to tight standards (HIPAA, GLBA, GDPR, etc.). The characteristics of a public Cloud and a Private Cloud are combined in this computing environment. You can, for example, store and analyze sensor data in the Private Cloud while experimenting with big data in the Public Cloud if you choose this option.

More information about the Cloud deployment of BI tools can be found here.  

Which are the top Cloud Business Intelligence Softwares?

Some popular Cloud Business Intelligence softwares are as follows: 

1. Power BI

Power BI Logo - Cloud Business Intelligence
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Power BI is a well-known leader in the field of analytics and business intelligence software. Microsoft Power BI is at the top of our list because of its affordable pricing, user-friendly design, and ability to tackle a variety of analytical difficulties. Offerings from Power BI include Power BI Pro, Power BI Premium, Power BI Mobile, Power BI Embedded, and Power BI Report Server.

Service OfferedPricing Details
Power BI MobileFree
Power BI Pro$9.99/user/month
Power BI Premiumstarting from $4,995/dedicated resources/month

More information about Power BI can be found here

2. Looker

Looker Logo - Cloud Business Intelligence
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Looker is a Web-based Data Visualization and Business Intelligence platform used by various organizations to create Business Reports and real-time Dashboards. It is capable of transforming Graphical User Interface (GUI) based user input into SQL queries and then sending it directly to the database in live mode.

The pricing of Looker is not released publicly and can be obtained as a customized quote for your business organization. 

More information about Looker can be found here

3. Tableau

Tableau Logo - Cloud Business Intelligence
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Tableau’s user-friendly interface allows it to perform tasks such as large-scale data integration, augmented data preparation, advanced data analysis, rich visualization, secure collaboration, and more. Offerings from Tableau include Tableau Prep, Tableau Server, Tableau Online, Tableau Data Management, Tableau Server Management, Tableau Mobile, and Embedded Analytics.

Service OfferedPricing Model
Tableau Creator$70/user/month
Tableau Explorer$35- $42/user/month (depending on the deployment model)
Tableau Viewer$15/user/month

More information about Tableau can be found here

What is the role of Cloud Data Warehouse?

Business intelligence is built on the foundation of data warehouses. They collect data from various sources and store it in a repository that may be used as a Single Source of Truth for analytics in an organization. For analytics processing, the repository is structured and optimized. Data warehouses used to be On-Premises systems with set processing and storage capacities, which meant they couldn’t expand readily or rapidly in times of heavy demand. Cloud data warehouses are a popular alternative for many firms adopting new systems today, as they replace some aging on-premises systems.

Snowflake, Amazon Redshift, Microsoft Azure SQL Data Warehouse, and Google BigQuery are examples of Cloud Data Warehouses that house various advantages over On-Premises Systems, including scalability, cost efficiency, and security. Data engineers, database administrators, and other data specialists assist in the identification of data sources and the construction of a data warehouse for their company. They then use ETL technologies to extract, convert, and load data from the data sources to populate it.

Using a Cloud-Based ETL technology that replicates source data to the data warehouse on a regular basis can help businesses simplify and streamline data import.

An ETL tool automates the process of connecting to and extracting data from sources, as well as loading the data into the destination, instead of requiring a data expert to build the ETL code and manage the infrastructure surrounding it (such as alerts and reporting). Hevo is one such ETL tool that can be used to carry out this process. 

What are the Challenges with Business Intelligence Cloud Hosting?

Some of the most significant obstacles in hosting Business Intelligence on the Cloud include the following:

  • Compliance with Architectural Standards: Compliance of business intelligence applications with web services architectural standards, which are set by either SaaS [Software as a Service] or PaaS [Platform as a Service] suppliers.
  • Server Management Issues: Using huge parallel data-warehousing systems with an equally distributed query load and consistent response time patterns across all database servers. For meeting on-demand resources, IaaS [Infrastructure as a Service] providers must efficiently leverage virtualized server array management and expansion.
  • Network Architecture Issues: The network architecture must be constructed in such a way that the query load is dispersed fairly among the array’s servers. This ensures that the servers in an array process query quickly. If the server array uses storage area networking to store the XML data files and OLAP cubes, the data must be equally distributed from the various storage devices using an appropriate network connection.


In this article, you were introduced to Cloud Business Intelligence and its advantages. Different Deployment Models for Cloud Business Intelligence were discussed and the reasoning behind opting for Cloud-based solutions was explained. Details for some popular Cloud BI software were provided and challenges with cloud deployments were explained. 

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