Business intelligence in a multi-cloud era

Until recently, the relationship between business intelligence systems and cloud providers has been simple. BI tools have traditionally been built with a single-vendor architecture in mind, allowing for straightforward integration with any one cloud infrastructure. 

However, since the cloud market has matured and become mainstream, things have changed. Companies are now taking advantage of the many different possibilities available to them, and in turn, shifting the way that business intelligence tools are used.

This has resulted in a new era, in which organisations are increasingly opting to take a multi-cloud approach to BI, rapidly embracing the benefits of a build your own, bespoke offering. Every organisation’s data environment is as unique as its business, and success requires an analytics platform that supports your unique data stack.

Multi-cloud means multi-choice

By next year, it’s expected that more than 80 per cent of all enterprise workloads will be cloud-based, with many businesses using cloud strategies to boost ongoing digital transformation efforts and achieve greater agility.

While public cloud engagement will no doubt play a key part of this spike in adoption, organisations are increasingly looking for solutions that are capable of going beyond the usual deployments, seeking those that also support IaaS, SaaS and private infrastructures. It’s unsurprising, therefore, that enterprises are opting for a more tailor-made approach to meeting their cloud infrastructure needs, outside of current individual offerings.

No longer required to pick just one of the vast amount of vendors and technologies available, 85 per cent of businesses are already choosing to operate in a multi-cloud environment. Over the next few years, as emerging functions such as Artificial Intelligence (AI), the Internet of Things (IoT) and Machine Learning (ML) continue to change the nature of business functions and operations, this will no doubt grow even greater.

Business intelligence as a service (BIaaS)

As part of the dynamic and evolving world of multi-cloud – in which personalisation reigns supreme – it’s essential that businesses are also entitled to flexibility when it comes to their data platforms. This freedom of choice allows organisations to change approaches as and when necessary, based on a variety of different infrastructures, applications and needs.

While some BI features may appear similar on the surface, regardless of which vendor supplies them, access to capabilities can sometimes be limited, depending on what an organisation and its data team is trying to achieve. Through a multi-cloud business intelligence approach, enterprises can avoid being locked down by one vendor, instead leveraging a catalogue of strengths.

This chop-and-change approach is also favoured for those wanting to keep costs down or stick to a specific budget, as vendors are forced to keep pricing low in order to remain competitive. With the playing field levelled, time-consuming and costly migrations are out of the picture. 

Data development and dialect your way

Because not every BI tool is created equally, an agnostic approach to multi-cloud databases is understandable and often necessary. If an organisation is modernising its data infrastructure, retiring old systems or even adding new technologies, then any platform being implemented needs to be able to support and simplify the process, not add to the confusion.

This requires the ability to automatically change the SQL dialect as needed for the new system, meaning your existing data models and business logic can be reutilised in your new database, instantly relieving pressure. In a multi-cloud world, every database is different and speaks a slightly different dialect of SQL, so creating universally applicable SQL queries is near-impossible.

Multi-cloud business intelligence platforms are much more likely to be able to take on this task, with many having already been integrated to support multiple versions of dialect and more being continuously added. Another new approach also involves abstracting your query from the underlying SQL dialect, allowing data teams to write a query just once. Not only does this leave one less thing for enterprises to carry out manually and on a regular basis, but it also takes away the burden of needing specific expertise within the company to manage the process.

For example, HR tech company Namely use the same platform across two different databases as they migrate between enterprise data warehouses (EDWs). This gives them the benefit of not having to rewrite all their queries to make them work with a new database, which is crucial for data privacy and allows them to focus on putting data in the hands of users, wherever it’s located.

 All too often, data tools lock users into a single way of viewing and utilising data, with many older approaches to dashboard analytics heavily limiting the value organisations can extract from data. To combat this, businesses need to ensure that they are deploying open systems, letting them deliver data in the way that they want, to who they want. In a multi-cloud environment, this means being able to take immediate action on data and connect users to the insights that are relevant and useful to them. Modern data platforms make it easy to operationalise data and insights, by plugging directly into workflows using connected systems like Slack and Jira, allowing users to deliver data in a setting where collaboration is done in real time.

As the importance of multi-cloud for the future of business intelligence continues to accelerate, now is the time for organisations to work out what is important to them and go on to define their approach to data. Regardless of sector or department, BI’s growth cannot be ignored and neither can its role in businesses wanting to transform themselves digitally.