To understand our business, we need a lot more data, such as the average customer’s lifetime value, and perhaps personal data about the customer themselves such as their age, spending habits or income level would also be useful! AI is useful here because it can attempt to interpret all the data together and produce predictions about what the potential lifetime value of a customer may be based on everything we know – whether we understand the connections ourselves.
As it becomes increasingly important that everyone within an organization is empowered to act on data-driven insight, new ways of communicating these findings are constantly evolving.
VR can be used to create new kinds of visualizations that allow us to impart richer meaning from data, while AR can show us directly how the results of data analytics impact the world in real-time.
Soon, we should expect to see new ways of visualizing or communicating data, widening accessibility to analytics and insights.
Cloud computing is another technology trend that has had a massive impact on the way Big Data analytics are carried out.
The ability to access vast data stores and act on real-time information without needing expensive on-premises infrastructure has fueled the boom in apps and startups offering data-driven services on-demand.
While those in DevOps roles manage ongoing technology processes around service delivery, DataOps is concerned with the end-to-end flow of data through an organization.
Is your business needs more understanding of how to utilize data for gaining profits?