Cost of poor data quality

The increase in the amount of data being processed is constantly growing. This does not mean that there is a better chance of making decisions. Data is used for a lot of decision making, but if the quality of the data is not good, it can have huge repercussions on the company.

Data quality management is an essential and essential part of today's business. As a result of data, important decisions are made in companies and their performance is measured in order to grow. There is a growing awareness of the importance of having good quality data, to be able to make a correct analysis and with less tolerance to errors, which allows companies to remain competitive. However, if the data is not entirely accurate, it can negatively affect the health of an organization with economic and opportunity losses.

Approximately 95% of companies use data to improve certain parts of their business, but 91% of them warn that poor data quality leads to a waste of a large amount of revenue. In addition, experts estimate that 25% to 30% of a company's quarterly revenue can be lost due to poor data quality. - Captio.net

On the other hand, as shown in an IBM report, organizations consider that poor data quality can cost an average of 15 million dollars a year, with economic and reputational impact, opportunity costs and a progressive loss of revenue. Trust in the veracity of data and data quality is a very important point to take into account when using data for decision making. Data are values that in themselves say nothing, but when they are processed and passed on to the analysis phase and combined with the experience of previous events, valuable conclusions can be drawn. Based on the conclusions drawn, important decisions will be made for company processes, which is why the quality of the data being collected is so important for decision making. You cannot have optimal KPI's if the quality of the data is poor or not completely accurate.

It is clear that data quality is an aspect to take into account in an organization, and that is why in the growing IoT sector it is vital to know what data quality is being collected and based on these metrics to make decisions. AirTrace provides an effective, simple and decentralized way to manage the quality of the data being collected with IoT devices.

ADOS to calculate data quality

The operation of ADOS (AirTrace Decentralized Oracle System) will not be explained in detail in this section because there is a detailed article. However, it is not a bad idea to recall one of the essential parts of AirTrace technology.

The main objective of ADOS is to capture anomalies between data collected by different sensors and provide a degree of reliability of useful data. By using Artificial Intelligence to provide a Data Quality Factor (DQF) and a distributed oracle system on the iExec platform, ontological relationships between sensors in the market can be leveraged to detect anomalies in the readings collected from IoT sensors. In this way, data quality can be obtained from the data being collected from IoT devices and in a decentralized manner.

Benefits of good data quality

Controlling the quality of the data and the accuracy with which it is obtained, provides a high quality of data that results in various benefits.

• Minimize the risk of poor decision making in IoT projects.
• Identification of new opportunities or understanding of what is going wrong.
• Saving resources and time spent for the exploitation of the collected information.
• Better adaptation to standards and a better way of accurate metrics.
• Improved image and reputation with customers and competitors.
• Optimal and effective decision making that allows for a higher probability of success.
• Value generation through quality information.
• Clean and enriched database

The security of your data is important

Finally, as we have been talking about in previous articles, the continuous increase in the amount of data in circulation leads to constant hacking attempts to steal or falsify data. That is why it is not enough to maintain a good quality of the data collected, but it must be done in a secure way and have protection mechanisms that prevent attackers from stealing one of the most precious assets of a company: data.

Average organizational cost to a business in the United States after a data breach from 2006 to 2020. (in million U.S. Dollars)

AirTrace has also thought of a unique solution for data security through a disruptive technology: the Blockchain. No matter if you do not know what the term 'Blockchain' is, you do not need to have knowledge about this technology to be able to use our platform and secure your data in a decentralized way. The data will be recorded in the chain and cannot be modified, stolen or falsified, because they will not be on any particular server, but will be in a distributed network of nodes that is responsible for keeping the data in order, without having a single control over the data that is entered.