In today’s world, enterprises need quantifiable information to help them make optimal decisions. This can be accomplished through business intelligence technologies. Not all of these, however, are created the same. Making sense of modern business intelligence architectures can help organizations achieve greater results in today’s competitive landscape.
Bringing Data to the Cloud
One of the most important elements to understand when making sense of modern business intelligence is the difference between on-premise, cloud, and hybrid applications, and what these things mean for an organization. The key distinction to know here is between on-premise and cloud architectures.
Here are some of the key points:
- On-premise is a locally deployed solution that is run entirely through an organization’s internal hardware and backend.
- Cloud services are software-based and are hosted and secured largely or entirely through third-party providers.
- Hybrid solutions combine these two elements together in one or multiple ways.
There are pros and cons to each of these options. In general, however, most enterprises are moving toward cloud or hybrid cloud architecture. Advances in technology are just the beginning of why cloud and hybrid solutions are becoming more popular.
For instance, it’s much easier to scale cloud and hybrid solutions than on-premise, as an outside provider handles the hardware and servers. Additionally, cloud and hybrid solutions typically have solid customer support on standby, as well as more flexible pricing options.
Data usability is another major reason to consider the benefits of a cloud-first architecture. When business intelligence technologies are connected to the cloud, it’s much easier to collect, clean, and pull data when it’s needed for analysis. When utilizing the cloud, you can have a technology like Matillion or FiveTran help seamlessly pull data where it’s needed. By opting for a cloud-based BI platform, where data can be instantly taken from different sources, organizations can do a far better job of quickly deriving actionable business insights.
Leveraging AI for a Better UI
Those who follow the developments of BI technologies probably know the cloud is generally where the most action is happening right now. As already mentioned, there’s far more flexibility, and greater possibilities, when using cloud versus on-premise BI for data analysis. But this isn’t the only area in which cloud can make a difference.
The user experience of business intelligence technologies is a huge factor that needs to be considered. Their architecture plays a big role in determining usability. ThoughtSpot is an outstanding example of a BI platform leveraging artificial intelligence to improve its architecture and user interface.
Through AI-powered analytics, it’s possible to build applications and tools that can be used by far more employees. Search-driven analytics is just one prime example of how AI can vastly improve BI architecture. With this, it’s possible for individuals without data expertise to run queries based only on questions, much like using a search engine. This is a total revolution in terms of how enterprises are able to use their BI when so many more people can extract value from these tools.
The Need for Scalability
As already mentioned, one of the prime benefits of opting for a cloud-based architecture is improved scalability. There are several ways the cloud makes scaling BI easier than it has been in the past.
For starters, not having to deal with servers and hardware makes scaling inherently easier when using cloud-based BI technologies. But beyond this, your data and BI applications can also scale up and down based on the needs of your organization. Having this kind of flexibility can take organizations to a higher level of optimization.
Organizations have a lot they need to consider when adopting new business intelligence technologies and practices. Consider all these factors before making a final decision on what’s best for your enterprise.
