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Crunching IoT data for practical insights

Cloud services provide versatile and efficient choices for rapid deployment and time-to-value for IoT setups. Here are some popular tools and database architectures that can be spun up quickly.

When you consider every connected device or machinery in your organization, it could seem like an endless stream of data coming from hundreds of locations. Each device or machine is like a small port of data in a big lake. Every device that has the ability to connect to the network will be contributing to this data lake.

In order to utilize the benefits of data collection from networked IoT devices, there a couple of key factors to consider.

Any device that is connected to the internet has the potential to be a repository of data. The Internet of Things doesn't just include smartphones, tablets, and laptop and desktop computers. It includes any type of device that contains embedded technology with the sole purpose of communicating with the external environment, all via the Internet.

Data can be stored in various formats. Each device can have its own method of storing data. Data can be stored in a media format, a raw form, relational or non-relational, each with its own data type.

The volume of data will vary. The data can be event- or process-related meaning it can accumulate in seconds depending on the device or machine. Data can be compiled as a batch or individual transactions. Some data may lose its meaningfulness over time.

It would be in the best interest of a technology professional to choose a solution that can manage heavy volumes of data, and produce meaning information by mining it.

The most well-known methodology for handing large amounts of data is Hadoop. Hadoop is a low-cost solution for managing data that can be spanned across different servers. Hadoop is not limited, as it can handle various types of data and data sources. In working within the Apache construct, it can handle any data type as well as media streams.

Microsoft's Azure Cloud provides a solution to managing Hadoop based data within its SQL Data Warehouse and Azure Blob. By establishing an account with Microsoft Azure along with a storage account, you will have the ability to move your IoT related data into a relational database format.

Microsoft utilizes a programming language similar to SQL called Polybase. Polybase is a data related programming language that allows you to access relational and non-relational data. By using this language, the user creates 'external tables' to move the data from an Azure Blob into a relational data structure.

By selecting a methodology that brings all your data together, you will gain the greatest benefit from all of your IoT related devices. You will be able to utilize time sensitive data and take a deep dive into the inter-workings of how each connected device is being used within your organization.