Technological trends that will shape the future of analytics
In one of our previous blog posts, we discussed where analytics will be in 2019. Now, it is time to see where analytics will go in the future. As the volume of big data grows, organisations are realising the full value of data analytics and look to incorporate it into their processes.
It is important to look at the future of analytics to see what role the technology will play in the years to come. 5G and IoT are around the corner and will have a huge impact on data analytics. Hence, we need to take a look at the direction analytics will go and what that means for businesses.
Data analytics is an invaluable tool, but the future of analytics will see a huge focus on cleaning and leveraging data. One of the biggest challenges organisations face is keeping data cleaned and prepped for analysis. Analytics is a great tool for generating insight, but if the data is not accurate or clean, then the insights generated will not be useful or valuable. Therefore, organisations will invest a lot of resources into the data architecture that cleans data by replacing missing feature sets and deleting irrelevant features.
The next stage of analytics
Data analytics comes in five different stages: description, diagnostics, discovery and predictive. Currently, most organisations are in the diagnostics and discovery stages of analytics. However, as organisations become more experienced at leveraging analytics and AI, they will eventually move into the predictive phase, and even beyond, into the proactive phase. Proactive and embedded analytics is the next stage, where an analytics component is embedded in the applications to get real-time insights faster than before.
The proliferation of analytics and AI
Data analytics and machine learning have been the realm of large corporations because they had the data volume and resources needed to invest in analytics. However, the future of analytics will see small and medium-sized businesses leverage affordable AI and data analytics tools. Thus, the future will see small firms, like trade businesses and local stores, leveraging analytics to access services that were only available to large corporations like Just-In-Time (JIT) Supply chain computing. Automation will also play a huge role with over 40% of tasks being automated by 2020.
The deconstruction of big data
Big data is a useful asset for large organisations. However, the future of analytics will focus on breaking down the big data into smaller components. When big data is broken down, it is easier for organisations to derive actionable and useful insights to meet specific business objectives.
The ability to breakdown data is especially important when one considers the depth and breadth of variety that comes with big data. It is no longer just text that counts as information, but also unstructured data, like images and videos. Hence, it makes sense to ‘focus’ the data by breaking it down into smaller chunks based on business goals. However, there is a drawback to this trend. Data that does not look relevant at first glance might contain valuable information when analysed more deeply.
Even though data analytics algorithms are accurate, they are by no means perfect. Hence, when professionals become more comfortable with technology, they are more likely to get critical about their findings.
Instead of following the information blindly, experienced professionals will verify their findings, especially if the findings make little sense. As an experienced data analyst, I encourage professionals to scrutinise and verify their data before making a business decision. If industry veterans discover mistakes, they can correct data findings, but most importantly, the machine learning algorithms will learn from this error and not do it in the future.
The future of analytics is taking shape…
The future of analytics will see businesses of all sizes implement and realise the benefits of analytics. Analytics becoming accessible to small and medium-sized businesses will be one of the biggest changes we see because it can lead to other trends like accelerating the democratisation of data as small businesses share information to compete. In fact, we think there is a future for data analytics to shape public discourse, similar to the way social media has like crowd-funded analytics.