Why Business Intelligence isn’t enough anymore

Why Business Intelligence isn’t enough anymore

Business Intelligence or BI software combined with a data lake is a household staple in a lot of companies. Combining different data sources in a visual dashboard helps organizations make the right business decisions or makes it possible to predict future sales. Useful, but if you really want to get the most out of your data, BI alone just won’t cut it. With the tagline ‘BI is dead, long live BI’ in mind, we’ll look at where BI comes up short, but also why you shouldn’t give up on it just yet.

An abundance of new applications

In recent years, a lot of new opportunities to use your company data have emerged. Most of those use cases have been around for a while, but as technology evolves, they’ve become more readily available. Consequently, businesses are more than eager to put them to use in an attempt to get a leg up on their competitors.

One of our customers, for instance, wanted to do more with data they gathered from IoT sensors. While they could use the data in BI to get a status report on their factory or office, that would be just the tip of the iceberg with today’s technology. Add a dash of Machine Learning and a sprinkle of Advanced Analytics and suddenly you’re automating inventory management and AI is guiding your production based on sales, seasonal data and even information on your competitors. Even more, it’s also better for the consumer side of things thanks to Microsoft’s cognitive services, for example. You can create a chatbot that can look up the production status of a customer’s order without having to manually sift through your ERP software, resulting in a better and faster service and less work for you.

The four Vs of a smart data platform

New applications, such as creating a recommendation algorithm like Netflix does, won’t be possible within BI. Why not? Because all these new use cases need a so-called smart data platform that adheres to the four Vs. And even if we try our hardest, we just can’t say that BI software combined with a data lake does that.

  1. Variety: different sorts of data keep popping up. Each and every one is valuable, but BI only works with a small portion of them. Unstructured data such as images or video can’t be analyzed by it.
  2. Volume: you need to be able to handle different volumes. Whether you have a data set of several MB or a couple of GB – and it more often will be the latter – your environment should be able to handle any size you throw at it.
  3. Velocity: you need to be able to access data quickly. Often even in real time. Thousands of data points constantly fire data at you and it needs to be useable asap. If you let AI guide your production, you don’t want to do it with last week’s data.
  4. Veracity: the sheer volume of data being generated by a smart data platform can pose one major question for data analysts: can the data be trusted? That trust depends on whether the data is representative, without discrepancies, and suppresses biases. It’s crucial that the information that’s being analyzed is relevant to the problem that you’re trying to solve. If your data is redundant, biased or abnormal, your efforts may prove futile.
smart data platform architecture as alternative to traditional business intelligence

Example of a smart data platform architecture: Lambda architecture for big data processing represented by Azure products and services. Note, other Azure solutions can be placed in the mix if needed based on specific requirements.

Why it isn’t over and out for BI

So, is BI useless then? Of course not, but if you want to unleash the power of data in the best possible way, you’ll have to also look beyond Business Intelligence applications. Nevertheless, the technology is still perfectly suited for what it does best: collecting business data to find information by asking questions, reporting, and online analytical processes. And in many organizations that’s what BI is all about: operational reporting by collecting historic data and presenting it in a visual dashboard. If you need statistics on how your sales performed last quarter, your best bet is still BI processing data gathered from a data warehouse . At every point, however, you should ask yourself whether BI is the best tool for the task you want to accomplish. Compiling a report and then using it as a base to make forecasts, might be something that’s better and more efficiently handled by Advanced Analytics driven by a smart data platform

 

If you want to know more about smart data platforms, and how it can help your organization to become data-driven, register here for a free workshop