How to Leverage IoT Data for Your Business

The Internet of Things (IoT) is enabling businesses to collect large amounts of data through the use of sensors from a variety of sources and touchpoints.

IoT data offers a broad perspective into many business activities, and its use is limitless — from reducing maintenance costs to avoiding equipment failure, improving operational efficiency to understanding consumer behaviors and delivering targeted marketing campaigns — and it’s only going to expand as we find more efficient ways to utilize the information. It’s estimated that 28 billion sensors will be in use by 2020, with $1.7 trillion in economic value. The scale of such data is mind-boggling.

The question is no longer how to collect the information but how to aggregate and extract insights from the data. In this article, we’ll look at how you can start to make the data collected from IoT add value to your business.

The Business Value of Using Data Generated by IoT

There are many types of marketing and operations data that you can gather from IoT, such as consumer insights from wireless home devices (e.g., Amazon Echo) or wearable technologies (e.g., fitness trackers,) weather records and telematics captured by smart home systems, and driving behaviors and traffic patterns gathered from GPS systems. Depending on the nature of your business, you can use such data to inform many decision-making processes, including:

• Delivering targeted marketing messages to specific customer segments.
• Serving higher value content based on subscribers’ preferences.
• Analyzing product usage to inform marketing and distribution.
• Understanding customers’ interaction with in-store displays to optimize services.
• Conducting social analytics to gain actionable insights into the personalities and behaviors of individuals and groups.
• Defining usage-based policies and rates.
• Fine-tuning fees based on demand and trends.
• Managing delivery fleet and other logistics operations to increase efficiencies and reduce costs.
• Performing preventive maintenance to avoid costly failures.
• Identifying and understanding quality control issues.
• Maintaining pipelines and network loads to avoid accidents and outages.
• Conducting video analytics to optimize operations, improve safety, and manage crowd movements.

The Challenge in Extracting Insights From IoT Data

The true power of business intelligence obtained from IoT data lies in the integration and analysis of a broad mix of data sources — ingesting them, normalizing them, and making them available to business users and data analysts for analysis and decision-making. Unlike data in a CRM or ERP system, data from IoT is often unstructured and isn’t easily organized into rows and columns on a spreadsheet for analysis.

The real challenge lies in the ability to manage this wide range of data, go beyond analyzing individual pieces of information and uncover patterns and relationships among various data sets from different sources. As such, you need to be able to access and integrate both structured and unstructured data types, as well as the ability to easily aggregate and correlate the data to get quick answers.

The traditional way of analyzing structured data — by squeezing them into rows and columns on a spreadsheet — is falling short in today’s big data environment that includes both structured and unstructured data.

With a large amount of data and the concern of governance and privacy, a better system is required for access control and policy.

Taming Your IoT Data

The new frontier of IoT data analytics requires an agile, cloud-based approach to working with the data and extracting value from it.

Data Discovery

You need to start with understanding what data you have, by type, size, age, etc. Such data discovery services allow you to automatically discover and report on the information regardless of type, so you don’t have to spend hours wrangling the different sources and formatting the data into spreadsheets before you can extract insight from it.

Data Unification and Organization

Implement a data organization service that allows you to unify, de-dupe and clean, and organize data into groups based on types that can be utilized in a way that’s easier to recognize patterns and relationships.

In addition, it’s important to be able to filter access rights based on data type, size, history, and object metadata when organizing data so you can apply better governance to protect the data.

Data Analytics

The ability to query and analyze information no matter what form it comes in is critical to fully utilizing and extracting insights from unstructured data gathered from IoT.

To do so, you need a data analytics service that allows you to aggregate, correlate, and analyze all the information in one place by automatically normalizing the information regardless of the source so you can quickly query and analyze any data.

Get Ahead of the IoT Data Game

Now that everyone can collect every piece of information and track everything, you have to win the game of IoT data by having the ability to organize it and run queries so you can respond to the real-time questions without going through the lengthy process of cleaning and organizing the information.

Learn more about how to more easily and cost-effectively wrestle your IoT business data.