Big Data Veracity, Effects, and How to improve Accuracy

The 5Vs of big data and how it works

When data is in petabytes or exabytes, it is considered big data and there are three main types of big data, which are structured, unstructured and semi-structured data.

Whichever type of data, you need to be able to measure your data completeness and to achieve that, there are 5 major characteristics or qualities of big data.


The Vs of Big Data

They are referred to as the 5 Vs of big data, which are Velocity, Volume, Value, Variety, and Veracity.

Some schools of thought summarized these to three Vs, some to two Vs, and some others extended these properties of bid data by adding vocabulary, vagueness, and viability, making the 8 Vs of big data.

Many are aware of the first four important V’s of big data which include Volume, Value, Velocity, and Variety.

However, the fifth component which is Veracity is not much talked about.

The meaning of the veracity component in big data is all about the abnormality and noises in the data.

Big data is reliant on the huge amount of data that is collected, stored, and mined.

The processed data should be meaningful in the end.

In case the big data faces veracity of the collected data, then it will create a huge disturbance in both the velocity and volume components of it.

While the large chunks of data are helpful and unavoidable at this rate, it is important for companies to continuously clean the data and remove the junk.

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By processing the unwanted data from the stored data regularly, the collected data can be kept clean. There are various tools available to help with this process.

The 5Vs of big data and how it works

The Importance of Data Veracity in Business

While businesses keep investing more and more in terms of technology, there are corresponding demands for data related to it.

This makes the technology prone to data veracity which will impact the right decisions as the numbers might be altered.

Data accuracy and integrity are very important. As a business owner or manager, you should ensure the accuracy of the data collection.

Not only that, you should comply with the best practices and ensure the accuracy of the data is improved by setting your data quality goal, running scans on the data, and clearing out junk.

When these data are not checked properly, then it will lead to several automated actions which will the result of the data veracity.

Without any atom of doubt, it will impact companies across all industries and the existence of the business might even be shaken.

Because of this, companies should show more interest in the field of cybersecurity and technologies which are related to data veracity.

While the abundance of data is in one way advantageous for companies, it will however not be profitable if the given data is not accurate and reliable.

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The business can not make ideal decisions based on the received data. By achieving the right data, there will be trust and reliability in terms of numbers and terms of income source.


The Tools for Data Veracity

Businesses can not avoid big data due to this issue as the use of big data in making their business grow is something that can not be avoided.

While this is the case, there are tools to help overcome this. This data veracity tool will give access to data lineage and help in determining the formation of the given data.

It will also help in showing the origin of the data as well as the receiver of the data.

Apart from this, the entire flow of the data, including the details of how it was managed will be disclosed.

This kind of traceable tool will help in increasing the security of the data.
There are also data governance tools that will give control over the data.

With the governance of data, the formation of the data can be identified too.

These data intelligence tools can be applied to the existing set of cybersecurity programs too.

It is not necessary to bring in a whole new program and change the whole system.


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When to implement it

Since data veracity can create major changes in the system as the amount of data is huge, it is better to implement the tools in the early stages of the business itself.

The data intelligence or data governance tools for data veracity will help in eliminating any kind of suspicious activities with the given data.

Since the data streams will be large and will be used to make major decisions in the business, the quicker the implementation of these tools the better.

Also, the implementation of the data veracity tools will bring in changes to the system, whether it is added right from the scratch or to an existing system.

This means that it will require time for the employees of the business to get used to the changes in the existing system.

Due to this fact, the early implementation of the tools will not cause a major time lag and there will not be a major change in the process.

This will allow the process to run smoothly and the staff will not face major adjustment issues.

These tools will save the system from any future threats which will cause major damage to the system.

By implementing these tools, the volume, variety, and velocity of big data can be utilized optimally and it will pave way for the development of the business.