Big data has been hot topic for a while now. Still, many organisations are behind when it comes to the optimal usage of business intelligence (BI). It’s often used on a low-key basis, because organisations are often reluctant in investing in the right tools and skills. The right interpretation of data can mitigate risks and deliver opportunities. Not only the lack of knowledge on management level, but also the bias on data IT departments have to deal with limits organisations in answering to market demand. In 2018 it’s time for organisations to move over to a next level if they want to avoid complete disruption by competitors. What are the trends to follow and to incorporate in the BI strategy for next year, thus most likely to invest in?
Most trends are not new, but will evolve into a more advanced version. Not only will certain trends unravel the complexity of the immensely growing amounts of big data, it will also deliver smart tools. BI will become more accessible for a larger group of people in the business; people outside the IT department and business intelligence domain. In order to reach that level organisations need to grow in their adoption and maturity degree.
Factors that will change the market and influence the practise of business intelligence are digitisation, mobile, cloud, analytics, agile work and artificial intelligence (AI). More data means more opportunities, but when growth and complexity exceed the ability to get the right information out of all the big data, it will overleap itself. How can you manage this intensity of information processing?
The maturity level is measured by the form of BI usage :
Five key trends in business intelligence
It’s important for organisations to undergo a shift in which big data will be considered a source of opportunities instead of a cost driver to get to that maturity level that will boost their business. What should organisations focus on to increase their maturity level of business intelligence?
1. Quality before quantity
The business lines are responsible for the quality of source data. Data driven decisions are only reliable if the information is correct, which is still a huge challenge in many organisations. So, this might be the first step to evaluate in any BI strategy.
2. Self-service BI is the new standard
Analysis and reporting tools enable the business to make reports without the involvement of IT departments, as well as to take care of data integration. So it reduces the gap between IT and business where the need for information lies. Speed and flexibility of available information is crucial. Many companies still struggle with the speed in which change and developments present themselves.
3. Augmented Analytics
Augmented analytics is automating data insight by the use of machine learning and natural language. It will let you automate data preparation and enable data sharing. So it’s highly connected to self-service Bi and a data-driven culture. This technology simplifies data and translates it to clear results. Also it provides business users with tools that helps them to make reliable day-to-day decisions.
4. Predictive analytics
This is an instrument to predict future actions and behaviours, so BI can expose risks and spot opportunities. The technique that is mostly used is Machine Learning, which discovers patterns in big data and is able to subsequently create a new algorithm based on these patterns. (letting the machine learn means it will discover new patterns) Predictive analytics offers a broad variety of possibilities, from prevention to marketing. It can for example help organisations to detect fraud, optimise maintenance of machinery and develop smart apps that adapt to users.
5. Creating data-driven culture
In order to create a data-driven culture an organisation needs to merge BI platforms and collaboration tools to improve the way teams make data-driven decisions. This way sharing information and ideas becomes easier, as will be cutting down time wasted on duplicate effort. Teams will be enabled to reach decisions much faster. There’s a strong focus on problem-solving, constructive communication and brainstorming ideas. To do this cloud plays a crucial role . It helps organisations to improve accessibility of information and tools. Many organisations are using or developing architectures that still connects cloud to on-premise solutions. But cloud analytics will truly offer faster and more scalable solutions to improve collaboration.
To disrupt means growing up fast
Focussing on targeted search for patterns and data sets will help organisations to get forward. When it comes to BI professionals, they need to be able to master data modelling and be able to establish early links. Especially integration of cloud, agile working and artificial intelligence in the form of machine learning will eventually define the BI maturity level of an organisation. 2018 will separate the front cover of the wheat while business intelligence will let organisations disrupt the markets they’re in.
I firmly believe that the future is very bright for data scientists (until they get automated). Next to that the nature of the business is already changing fast based on data-driven models. You need to get into this or your business will fail. No GDPR can save you.