The impact of self-service analytics on the industry
Self-service analytics is going to change the entire analytics industry. Even though this version of analytics is not as powerful as other analytical platforms, self-service is going to transform the industry with the value it brings to organisations. Self-service in analytics is possible because of the rise and convergence of several technologies, like AI, big data and data visualisation. I believe that this form of analytics is going to have a transformative effect on the industry, so I am going to take the time to explain why I think this.
What is self-service analytics?
Before going into its transformative impact, I need to explain what is meant by self-service analytics. It refers to data analytics platforms that are accessible and usable by business-minded people or those who don’t have a background in data analytics. Such an analytics platform is not as advanced as other platforms, but the benefit is that it can be used by non-technical people to perform basic functions. Basic functions like generating reports, performing queries and accessing relevant data. With this form of analytics, users can perform day-to-day operations without having to consult an analytics team.
Benefits of self-service analytics for organisations
There are several benefits to using self-service analytics. The first is better productivity because organisations can get tasks done by themselves because they do not have to contact their data analytics team for the smallest task. With basic functions covered by other professionals, the data analysts’ time is free to do more advanced work, making better use of their time. Furthermore, self-service analytics democratises data analytics, making it more accessible to people who don’t have a background in data analytics.
Impact on the industry
There are several benefits to using self-service analytics, but what impact will it have on the analytics industry, as a whole? For starters, it opens the door to more analytics platforms. Self-service analytics is built for different end-users who want to complete different functions. These functions include, but are not limited to workflow integration and operations reporting. It opens the door to a wide variety of data analytics platforms with different functions and capabilities, enriching the industry with different product types.
The biggest impact of self-service analytics will be felt in big data. With end-users able to process data on a basic level, there is going to be an explosion of valuable data produced by organisations. Organisations and their data analytics consultants need to set strict standards on how data is accessed, processed and protected. Although, if organisations want to encourage a culture of data exploration, they should adjust their data governance standards to be lighter and flexible.
Finally, self-service analytics completely changes the relationship between data analytics professionals and their clients. With organisations being able to perform analytics services, they will no longer call on analytics organisations for basic services. This means analytics teams have the option to offer higher-value services to their clients. The 2018 State of Embedded Analytics Report reported that over 49% of organisations saw a reduction in the number of ad-hoc requests from clients once self-service analytics was implemented.
Is self-service analytics going to replace data analysts?
It’s easy to think that self-service analytics is going to replace data analysts, at least in theory. However, reality tells a different story. The fact of the matter is, people with a non-technical background don’t have the time (and in some cases, the inclination) to become familiar with more advanced data analytics platforms and even learn other techniques, like data mining. Hence, while self-service data analytics is perfect for executing basic functions, it is no replacement for data analysts because they are not suited for more advanced functions. At least for now 😉
The future of data analytics
Self-service analytics are a preview of what we can expect for the future of analytics, i.e. making analytics more accessible. Previously, data analytics was restricted to a handful of experts, and only to large corporations who had the scale and scope to invest in analytics. Cloud computing and AI combine to open analytics platforms to parties that never had access to it before. It is an exciting time for data analytics because its benefits will be accessible to organisations of all sizes. Some analytics organisations are adjusting to this reality either by providing self-service analytics or on-demand analytics made possible through cloud computing.