How to take advantage of data from the Internet of Things?

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More and more devices are connected to the Internet and are collecting data. According to the consulting firm IDC, by 2025, 80 billion devices will be connected, generating 180 trillion gigabytes of new data in that year alone. While we know that data is key to running organizations today , how can such a large amount of information be managed to extract knowledge applicable to improving business processes? In this article, we will answer the question.

The obstacles of the Internet of Things (IoT)
IoT-generated data will undoubtedly become increasingly important to the functioning of businesses, but too much of it can be overwhelming and distract analysts , slowing down decision-making. The challenges of IoT, however, do not end there: the risk of irrelevant information slipping through is great , so if it is not collected in a business-friendly manner and is not presented in a user-friendly way for analysts and users, companies will not obtain any value from the data. This translates into a loss of time, money and the opportunity to advance their businesses.

Approaching the “analytics of things”
To make the most of a large amount of data (Big Data) and implement an IoT-based analysis process, a series of basic guidelines must be followed:

Quality control
IoT data comes from multiple sources and formats through indonesia number data continuous streaming. The first step to being able to use the information is to separate the useful from the irrelevant, automating data cleansing as much as possible to save costs, time, reduce the margin of error and promote integration with other internal and external sources.

The key is to find information that is actionable and capable of creating real and meaningful change . It is necessary to establish limits and benchmarks to filter the data and isolate the most relevant ones that will be sent to the users.

Place of analysis
In parallel with the increase in data in IoT, the migration of information and processes to the cloud or cloud platforms is taking place.

Cloud storage options include public, private, and hybrid models. If a company has sensitive data that is subject to any regulatory compliance requirements that require increased security, using a private cloud would be the best option. For other companies, a public or hybrid cloud can be used for IoT data storage.

There are several ways to build an analytics infrastructure that fits the needs of the business, the type of data collected, and the IT team that the organization has:

Move IoT data to a centralized location to combine it with other data and prepare it for analysis.
Analyze data inside IoT devices and move the results to a Business Intelligence (BI) platform for visualization.
Create an architecture with a well-defined division of analytics between the device and the cloud.
Purpose of analysis
The reason for the analysis depends on what answer you want to find in the data. In this sense we have:

Descriptive analysis: what happened?
Predictive analytics: what will happen next?
It allows you to plan better and avoid costly downtime or routine maintenance. It will lead to accurate decision making to solve everyday business problems that impact overall performance.

Prescriptive analytics: What should be done in a given scenario?
An action is recommended based on what happened in the past, what may happen in the future, desired outcomes, specific scenarios, and current and historical data collected.