The Internet of Things, a concept also known by the acronym IoT , refers to the technology that allows everyday objects in our daily lives to be connected to the internet, receiving and sharing data.
You indeed make or have used the Internet of Things in the last few years. Items such as cars, television sets, and even refrigerators are just a few that worked 100% offline until recently. Still, they can now realize connections with the internet and thus promote significant changes and challenges in how businesses in various areas deal with collection e data analysis.
In practice, when we talk about business, some of the main changes provided by processing data collected from the Internet of Things are reducing resource waste, greater operational efficiency, and a decrease in downtime.
Do you like the idea and want to know more about the benefits that data from the Internet of Things can represent for your business? Below, we have selected and explained 5 of them for you.
More Innovation In Your Day To Day
Data obtained via the Internet of Things represents an opportunity for organizations to embrace new ideas and reinvent themselves. Seeking more innovation and promoting the emergence of more creative ideas within your company is one of the ways to stay competitive and win new customers.
Improvement In Crisis Management
A crisis is the kind of thing that everyone tries to avoid, but eventually, it happens. What we can do, then, is to be prepared to deal with the situation in the best possible way. And having quality, up-to-date data on hand is crucial for crisis management to be carried out effectively. With the Internet of Things, your organization has more data to draw on and make the best decisions to overcome crises and come out stronger on the other side.
Going Deeper Into Your Customers’ Demands
How to know your customers’ habits and desires more profoundly and accurately? The answer can be found with the Internet of Things. Every day more objects connected to the internet are acquired and activated, creating new volumes of data that can and should be collected and analyzed to obtain Market Intelligence and anticipate trends.
Discovering Opportunities For Growth
Embracing the changes coming from the data collection and analysis of the Internet of Things opens your eyes to new and better business opportunities that might otherwise go unnoticed. These growth opportunities can even be decisive for the healthy future of your company.
When it comes to analyzing data and extracting useful information from it to meet the objectives established in each strategy, team, or area of the company, specific details cannot be neglected.
Some of these details, such as the types of data analysis, the ethical approach to data processing, and the volume of data, have already been covered here on the blog. Today, the subject is different.
Giving Productivity A Boost
Using the information obtained by collecting and analyzing data from the Internet of Things to promote improvements within your organization can be a way to review routines and processes and thus increase the productivity of your company as a whole.
The External Characteristics Of The Data
External data characteristics, or simply metadata, include attributes such as data volume, structure, and timeliness.
An example of metadata is the properties that describe the data or technical information. Elements such as title, subject, creation date, usage license, size, and compression are examples of metadata.
In other words, external characteristics assist in classifying data and are fundamental to data analysis. For example, they are used to identify problems in the quality of the collected data.
The Dependencies Between Data
When we talk about data collection and analysis in practice, it should be noted that datasets, by and large, do not exist in isolation. What happens is that data is stored in structures such as data lakes or data warehouses.
Something quite common when it comes to big data is the derivation of one data set into another. Unstructured data, For example, unstructured data is transformed into structured data. Or, disparate groups of incomplete data are merged to give rise to a more complete and up-to-date volume of data.