But in the near future we might see BI take another direction: Rather than companies merely purchasing dashboard reporting software for the purposes of internal usage, we’ll be seeing a surge in companies looking to integrate advanced analytics and reporting into their own products. Welcome to the world of embedded analytics.
What Embedded BI is All About
Simply put, embedded analytics (or embedded BI) means adding features normally associated with BI software – such as dashboard reporting, data visualization and analytics tools – to existing applications. This can generally be achieved in two ways:
- In-house development — i.e., the app manufacturer builds its own analytics platform and includes it in its existing product
- Purchasing and embedding out-of-the-box software — i.e., turning to an external developer and integrating its analytics solution in the application
To Build or not to Build, That is the Question
While both of these solutions are viable ways of adding a BI platform to existing software, it’s widely accepted nowadays that most companies simply don’t have the required technical expertise and resources to develop a truly robust analytics tool.
Business Intelligence is a complicated field that requires specialized knowledge, and if the software developer doesn’t already possess the required manpower and background, acquiring them could be extremely time and resource intensive.
Hence, any developer that hopes to provide an analytics feature that can provide actual unique value to its end customers, and who doesn’t have endless time and endlessly deep pockets, should probably be looking at embedded analytics solutions.
Why It’s Getting Big
So what advantages does embedded BI offer to software developers? Why is it poised to be the next big thing in business analytics? Because companies are beginning to realize the power of data and the added value that can be derived from it – not just for themselves, but for their own customers as well.
Collecting data has become easier than ever. Any software application that processes large amounts of data (marketing automation applications might be seen as a typical example, but other examples can be found in a wide range of industries) can also record this data and store it in a fairly structured form — in an automated manner and without the need for any kind of human intervention.
And if you’re already collecting all this data – why let it go to waste? Giving your customers access to it can make your own product that much more valuable. However, raw data is usually less than entirely useful without the means to “crunch” (i.e., clean, analyze and visualize) it. This is usually done with the use of BI software.
Still… Why Embedded?
But since plenty of dashboard reporting tools exist, including quite a few that can integrate with existing platforms or csv exports, the question remains – what is the unique value of embedding the analytics platform within the application that’s collecting the data?
The answer is simple: to keep things simple. Users don’t want to alternate between platforms and to become accustomed to a whole new user interface and framework. If they’re dealing with data that is generated or exists within a certain application, it’s much easier for them to proceed to handle that data within the same application rather than being forced to purchase, install and become familiar with an additional tool. This also shortens the time periods that pass between the data being generated and the its analysis, which makes for more effective analytics.
For these reasons, embedded BI provides a much cleaner and friendlier user experience for customers, and therein lies their major advantage over solutions that require two separate platforms.
Why It Will Get Even Bigger
We will venture to guess that the increased adoption of embedded analytics solutions in recent years will not be a passing trend; in fact, it would appear that we will be seeing much more integrated BI solutions in the near future.
This prediction is based on the fact that data, and data analytics, are becoming much more of a commodity — and are no longer seen as a luxury item for the larger and richer corporations, but as a must have for almost any kind of data-driven business, and even for consumers and individuals who would like to be making better informed decisions in their day to day lives. And with the Internet of Things and the growing propensity of mobile and wearable device usage, the amounts of data anyone can be exposed to at any time grow considerably.
For example, we could easily imagine a reality in which shoppers have a mobile app that analyzes recent changes in product prices — allowing the consumer to decide whether to purchase a certain product on the spot (e.g. when standing in front of the counter at the supermarket), or wait for a better time. Navigation apps are already analyzing traffic data to find the shortest routes, but giving the customer direct access to this data might let him also learn what would be the most gas-efficient or safest one as well, or come up with his own insights. Wearable devices can track a person’s heart rate, speed and other variables during his or her work out — data analytics could later be used by this person to determine which workouts or exercises were the most effective.
Truly, the possibilities are close to endless. Once consumers realize how much they can better their own lives using data (whether Big or small), they will begin to demand manufacturers to provide them with tools they can use in order to analyze this data themselves. Accordingly, we expect to see an increasing amount of products coming with an embedded analytics feature, presenting a new opportunity for software and application developers and BI vendors alike.