Three Tricky Trends in Business Intelligence

Business intelligence and data analysis are big trends in business management. However, the technology and practices in BI are changing quickly. Lose track of these three critical trends and you could find yourself playing having to play catch-up, which would negatively affect perception of your professionalism.

1 – Artificial Intelligence

Whether you refer to machine learning, machine intelligence, or automated systems, artificial intelligence is one of the most critical changes that will come to BI. Rather than depending on people to analyze everything and find all the notable patterns in data, machines can do much of that.

The concept isn’t new in a way. Algorithmic-driven predictive engines have been available for businesses since the late 1990s, usually in the context of a specific application like supply chain management. The sophistication has grown over the years. AI technologies can even analyze the deductions and decisions people make based on data and then learn how to apply the same steps at future times.

But besides being a big area of knowledge to acquire, there are also significant limitations. If the examples and decisions used to instruct the learning system are flawed, the AI-driven results will be as well. Patterns can also have multiple meanings. If you work for a cable company and an AI system identifies the most loyal customers based on data, that might be fine, or it might have accidentally pointed to the percentage of the customer base that was unemployed and sitting home, watching TV.

2 – Mobile BI

Everyone wants mobile everything these days, whether they need it or not. That may seem coy, but it’s true. There’s a growing assumption that if capabilities aren’t available on mobile, there is something wrong with the service.

That actually makes a good deal of sense. Examine the way people use technology and you see more and more time on mobile devices, less on desktops and laptops, and even the number of mobile devices sold outstripping traditional PCs.

Moving BI to mobile faces big challenges, with one of the biggest being screen size. The change in available visual landscape means that old assumptions about how to present conclusions, trends, and data are no longer applicable. Even the input side of user interfaces will change. BI professionals can’t simply adapt what had worked before. They need to create new ways to effectively communicate.

3 – Internet of Things

The Internet of Things, or IoT, refers to the embedding of communications and computer processing in all manner of products or parts. The assumption has been that the massive amounts of data that can be taken from items in the context of actual use can help design, engineering, customer insight, and even marketing.

But the data flows are more floods. BI experts will have to master techniques for quickly analyzing large real-time amounts of data. Having the right processing techniques on hand is critical. So is the ability to tell when data may not be so useful. It will be important to emphasize utility over ability.

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