Companies continue to look for tools to analyze data for decision-making and efficient business execution. At the forefront is business intelligence (BI) software. Business intelligence (BI) is about providing the right information to the right person at the right time, and cloud BI is a way to access data quickly.
Cloud Business Intelligence (BI) applications are hosted on virtual networks such as the Internet. Companies are increasingly using cloud-based tools such as customer relationship management (CRM) applications (Salesforce), online file collaboration and storage (Dropbox, Box), and help desk software (UserVoice, Zendesk). This trend also includes business intelligence tools that incorporate cloud agility and accessibility.
Why is business intelligence important?
Companies that aim to make factual decisions more efficient understand the importance of business intelligence. Business intelligence also uncovers critical patterns and trends in business data and provides insight into organizational processes, consumer behaviour, and internal productivity. This insight is critical to decision-making and performance optimization.
The quality of the data:
Having high-quality data is critical to achieving good business analytics. Poor data leads to poor business intelligence. There are two main reasons why data quality is a challenge. Data is getting older, which can easily happen in large, complex organizations. Second, companies don’t have time to practice proper data hygiene.
Critical data is buried in different systems:
Siloed data is when the data is on a different system and cannot be accessed by other systems, either because the software is incompatible or because the business unit has tight control over user rights. The problem here is that if your critical data is siloed, your data will be locked up, and you will only have a partial view of your data, so your business intelligence will be incomplete. By working with a good ETL tool (extraction, transformation, loading), you can make data from different systems available for analysis in bulk.
A lack of expertise
Using business intelligence tools requires considerable expertise. In other words, only some key people in your organization can have the skills to use business intelligence tools effectively, which can be a bottleneck.
Key Benefits of Cloud Business Intelligence (BI)
Cloud Business Intelligence offers several significant advantages over on-premises applications. Here are some of them.
Ease of deployment:
Internet-based software allows users to quickly install cloud BI solutions without waiting for overworked IT staff to arrive.
Cost versus effect:
In the case of cloud computing, companies do not need large-scale hardware or software upfront budgets. Companies can look at the BI infrastructure as a service, pay only for the compute resources they need, avoid the cost of acquiring assets, and maintain low entry barriers.
High-quality cloud BI tools are designed with easy-to-use dashboards and an intuitive design, so users can start deploying and using them without having to worry about complicated instructions.
Advanced data sharing:
Cloud computing applications enable seamless access and sharing of data between remote locations. They usually remain outside the corporate firewall.
Employees are no longer tied to their desktops to access information. We can access Cloud BI solutions from our phones or tablet.
Only large enterprises could deploy software that provided insight into business intelligence in the past. The growth of the cloud and its economic benefits have enabled small and medium businesses to access valuable intelligence. Moreover, companies of all sizes in the industry will leverage cloud BI tools to create a fairer competitive landscape.
Democratization of data
Cloud BI software makes data available to all users and provides tools for manipulating data in various ways. So, with a basic knowledge of data, users can integrate the necessary data sources with pre-built connectors, visualize the data with drag-and-drop tools, and delve into the data with advanced filters. With AI technology, users can identify trends and outliers in data and make accurate predictions. In addition, the software cleans and converts the data to ensure quality and accuracy.
Types of different Clouds:
Web-based BI solutions and some (such as data storage) can work with three cloud types.
Public clouds are the most affordable option for cloud BI. It’s a great option for small businesses with limited budgets and big data workloads.
For example, a project with science software hosted a big data analytics solution on the Azure and AWS clouds to enable market research firms to respond to the continued growth of data and effectively process it with storage and computing cloud resources. At the same time, the budget requirements were met with the reasonable pricing of the public cloud.
The model is similar in technical characteristics to a public cloud and in terms of autonomy and security to an on-premises solution. So, the company is the sole owner of the cloud and operates a cloud server located in a dedicated data center. The servers are sometimes provided externally, but the company is responsible for maintenance and infrastructure customization. Therefore, considerable investment is necessary.
If you can’t afford to put your entire BI solution on a private cloud but need to comply with stringent regulations (HIPAA, GLBA, GDPR, etc.), a hybrid cloud is a right choice. This computing environment combines the characteristics of a public cloud with a private cloud. This option allows you to, for example, store and analyze sensor data in a private cloud and experiment with big data in a public cloud.
As with cloud computing, the potential of cloud BI is staggering. Companies are moving to the cloud and already enjoy benefits such as lower costs, faster deployment, and ease of use. Cloud applications now have the same computing power as on-premises applications. It can also provide users with deep functionality that previously only locally installed software could provide.
Cloud BI has the potential to be a key part of a company’s analytics and BI strategy, including self-service BI, by providing end-users with real-time access to business-critical data.
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