HomeBUSINESSThe Role Of Business Intelligence In Multi-Cloud Environments

The Role Of Business Intelligence In Multi-Cloud Environments

Cloud technology is now considered an indispensable complement for more efficient operational processes and employee productivity. Whether public, private or hybrid cloud: companies are faced with a wide range of offers from which they can choose the right product for their technology stack. This growing abundance often leads to establishing a multi-cloud approach in companies. But how do multi-cloud and business intelligence tools fit together when the latter was traditionally designed for the cloud architecture of a single provider?

An organization’s tech stack is unique and has different requirements: When considering cloud computing, it should be ensured that systems, applications, and platforms are integrated and can interact to provide the best IT environment for business creation. Not every cloud provider offers the same services as its competitors. For this reason, a multi-cloud landscape has established itself in many companies – i.e., the procurement of IaaS, SaaS, and essential business functions from several different providers. This prevents the operation from being tied to the offer of a single provider by lock-in and promotes significantly more flexibility. After all, the decision-making authority remains with the user.

Today, 85 percent of companies already prefer to use a multi-cloud environment. In the coming years, this trend will continue even further as concepts such as Artificial Intelligence ( AI ), Machine Learning ( ML ), and the Internet of Things ( IoT ) will transform business functions and operations.

The Bitkom Cloud Monitor Report 2019 shows why companies are increasingly opting for a multi-cloud environment. Most (55 percent) see the benefit of providing dedicated cloud services offered by different providers. In addition, the ability to distribute workloads and resources to different cloud services at full utilization (24 percent), reducing the potential for failure (20 percent), and reducing costs (6 percent) are other significant advantages.

Gartner also looked at the reasons for implementing a multi-cloud strategy. Companies would like to circumvent a lock-in and thus have to rely on the (limited) offer of a single provider and fully exploit the strengths of several providers concerning their requirements. This so-called best-of-breed approach contributes significantly to cost savings since the competing cloud providers have to keep their prices low to remain competitive. As a result, time-consuming and costly migrations are no longer an issue.

Business Intelligence In A Multi-Cloud Infrastructure

However, using a multi-cloud approach also means that data is located in different databases. In day-to-day business operations, data is constantly being generated and collected, which provides information on the market, product and competition developments, and internal processes. Business intelligence tools offer companies the necessary agility to make the right decisions based on data in the event of critical changes. They automatically analyze this data, prepare it and visualize it via an interactive dashboard.

But the potential of business intelligence goes far beyond reporting functions. The knowledge generated from the automated analysis acts as an essential insight into the current status quo and trends, and future perspectives. Together with the general structure, the management must use this information to make company-relevant decisions and initiate appropriate changes and (optimization) measures.

Once companies have a significant amount of such BI data at their disposal, databases become essential for business success. The requirements for specially operated database servers are constantly increasing. Maintenance, modernization, and licenses are expensive for companies. Therefore, it is not surprising that these are also being moved to cloud servers. Companies can take advantage of several different offers from the various cloud-based databases that suit their operational processes. However, a problem is associated with using different databases from different providers that should not be neglected: Each database uses its SQL dialect – Amazon Redshift, Snowflake, Google BigQuery, or Microsoft Azure SQL. This makes the creation of universally applicable SQL queries almost impossible.

BI Tools Enrich The Work With Different SQL Dialects

On the one hand, BI tools that collect and evaluate data from cloud-based databases must be able to differentiate between the different dialects to make them usable. On the other hand, it also means that existing data models and business logic must be reusable in the new database. This requires automatically adapting the SQL dialect to the new system if necessary. Multi-cloud business intelligence platforms can take on this task, as many of them are already designed to support multiple dialect versions, and new features are constantly being integrated.

Another new approach is abstracting the query from the underlying SQL dialect, so data teams only have to write a query once. As a result, they no longer have to worry about manual and regular execution. This minimizes the associated risks, such as data overload, and eliminates the effort dependent on specific specialist knowledge within the company to manage the process.

Conclusion

Often, organizations are limited in viewing and using their corporate data, primarily when they rely solely on dashboard analytics and reporting. However, this data reveals much more. The solution is to use open systems that allow them to receive data that best suits their unique business needs. In a multi-cloud environment, users must receive the data and insights relevant to them to react quickly to changes and trends.

As the implementation of multi-cloud strategies related to business intelligence becomes more important in the future, now is the time for companies to find out what is essential for them and their business development and to define how they deal with data. Regardless of the industry or company department: The relevance of BI can no longer be dismissed out of hand, nor can its role in companies that want to convert digitally.

ALSO READ: Self-Service Machine Learning Platforms

RELATED ARTICLES

LATEST ARTICLES