The Internet of Things is already becoming more and more commonplace in the world around us. Forbes mentions that by time 2025, the IDC expects as much as 152,000 new IoT devices to be connected every minute. While this in itself is a staggering number, one must remember that the data collected by these devices is only useful if it is processed and turned into actionable information. The IoT is just the framework. The collection of data creates opportunity, but only if utilized correctly.

The Inherent Value of Collected Data is Zero

Towards Data Science mentions that data itself has no inherent value, and whatever it does possess comes from the virtue of it being processed. IoT data is no different. Despite the terabytes of data streaming into the system from a myriad connected nodes, the information that aggregates in a company's lake is about as valuable as the dust that settles on its IoT devices after years of use. Figuring out how to make that data relevant comes from determining how to process it.

Collecting Relevant Data

Not all data that IoT devices send is relevant to a company's needs. Business intelligence systems need to have consistent data streaming in from devices and combine it with existing data to generate insights. Processing this data starts with collecting it and putting it into a usable form that can then be consumed to give the results the company is looking for. 

Creating Consumable Data

Big Data is mostly noise. Industry Week compares finding insights in Big Data like finding a needle in the proverbial haystack. IoT data, because of the sheer volume and the amount of noise contained in it isn't easily consumable. Collecting the data an IoT project requires could take as much as one or more months. A business aiming to profit from its IoT data needs to make that data searchable and allow users to find what they want from it. Cataloging and curating that data allows for much easier usage by the average consumer.

Use IoT Data in Existing Applications

Not all IoT Data is suitable for use in all facets of a company's business. However, by taking a look at what the company does and what it provides, data from IoT devices may be useful in more than just marketing or processing. Sales and marketing can combine existing IoT data to give feedback on how the company approaches the way it creates and interacts with customers. Better customer experience can, in turn, lead to better lead generation and potentially better sales numbers.

Using Data as a Service

Data as a service streamlines the process of creating consumable data. By aggregating data, like Adeptia does, from disparate sources such as local databases and unprocessed IoT data, the system can allow users better access to data stores and speeds up how quickly they can recover insights from that data. Datastores can be accessed and manipulated by each user using utilities produced in R or Python to help get a better picture of what they're working on.

Open Source Architecture

Data analytics relies heavily on open-source architecture. With the right training, anyone can be a data scientist and bend collected information to their will, coming up with insights that can impact the functionality of a company on a fundamental level. Open source processing methods make it easier for users to tap into existing collections. They can also save the company lots of money by ensuring it doesn't have to pay for an enterprise-grade data processing solution. As a result, the overhead is lower, and the value of the insights can be seen in how it pays the company back.