5 Steps to Connect Business Intelligence to IoT Solutions

Piyush Goel -
business intelligence iot
Illustration: © IoT For All

The world now has over 10 billion active IoT devices delivering personalized data to organizations. Even more impressive is that this number is on track to more than double by the end of the decade. IoT solutions are the future of many operations. The challenge for organizations is no longer how to track data but how to analyze it effectively. Business intelligence platforms can visualize the data from IoT solutions for various industries, including, but not limited to, healthcare, logistics, and manufacturing. The article below discusses how to connect IoT devices to business intelligence platforms to ensure organizations get the most value from the data that they collect.

5 Steps to Connect Business Intelligence to IoT Solutions

1. Create a Plan

The first step requires determining what information to collect and analyze from IoT solutions into a visual dashboard.

For example, a trucking company may want to ensure that their trucks are maintained and drivers are safe on long, cross-country trips. They can add low-energy tire pressure sensors to each vehicle. The data can be sent to an IoT hub for analysis. Then, the data can create mobile-accessible reports that truckers and staff can access whenever and wherever needed.

This all starts with a plan for how an organization plans to use the data collected. The organization can then decide how the data will best be distributed and displayed to those that need it.

2. Store Data in the Cloud

The next step to turning IoT solutions into valuable data is having a place to store it. The leading cloud storage services for business intelligence are Azure, AWS, and Google Cloud. Each service tools make it easier to visualize the data it stores.

For example, the Microsoft Azure Data Factory is a serverless tool, which uses ETL (extract, transform, and load) processes to upload data from IoT devices to the cloud. Healthcare organizations can use cloud services like Azure Data Factory to store massive amounts of data collected from wearable devices that monitor many chronic conditions such as heart disease, diabetes, depression, and seizures.

3. Prep and Train the IoT Data

Data stored in the cloud is static. If an organization wants to make sure they can turn the data into more than a pile of numbers or statistics, the organization needs to prep and train the data to work based on your requirements.

Tools like Amazon SageMaker uses machine learning tools to understand data sets. Organizations can use machine learning to simplify how they receive the data from IoT devices into specific models that make it easier to visualize the data.

Plastic companies, for example, can connect a service such as SageMaker to a business intelligence platform to detect defects. Business intelligence visualization tools show where issues are occurring in their manufacturing process. They can optimize the products they deliver with the same workforce.

4. Analyze Data

Data analytics programs like Azure Synapse Analytics model the data, so it is ready to visualize. Essentially, the software makes it possible to search for specific information to analyze the data at scale. Furthermore, they provide powerful analytics to ensure your organization can understand their data.

Many types of manufacturing firms can benefit from these analytics. Synapse Analytics can connect to business intelligence software to provide up-to-the-minute analytics. This way, executives at a manufacturing company can read instant results from the IoT devices on the plant floor.

5. Visualize Data

Once the data is stored, prepped, trained, and modeled, the next logical step is to turn this data into something useful. Business intelligence excels at turning data into something organizations can review and evaluate to make more strategic decisions with the most current data.

For example, Tableau connects multiple tools to visualize data across multiple IoT cloud tools. Tableau takes in data and provides relevant ways for users to understand the data. Visualization software like Tableau creates the right charts, graphs, and other analytical visuals to make data easy to read.

The analysis ensures organizations are for workers on the floor and better understand their upcoming schedule to reduce unplanned downtime.

Final Thoughts

These steps bring together the power that business intelligence and IoT solutions each provide. Combining business intelligence and IoT solutions together allows organizations to use more data in real-time to improve their operations.

Piyush Goel - CEO, Beyond Key Systems

Guest Writer
Guest Writer
Guest writers are IoT experts and enthusiasts interested in sharing their insights with the IoT industry through IoT For All.
Guest writers are IoT experts and enthusiasts interested in sharing their insights with the IoT industry through IoT For All.