Primary and secondary data to explain big data and data depletion

Big data is already well known to many companies, while data exhaustion is much less so. Big data is raw data related to the core of your business, while data depletion is secondary data that is created day by day.to. Primary and secondary data will help us explain a little bit about big data and data depletion today.

To see the differences between Big Data and data mining based on primary and secondary data, we will see 5 things you need to understand about data mining to understand the pros and cons of this type of data.

1. It is essentially all the Big Data that does not belong to the core of your business..

The term data escape has been used for more than a decade, Y emerged as a result of new smartphone data streams. Today, more accessible data tools are bringing data exhaustion to the fore.

Primary and secondary data have a lot to do with this. If big data is primary data related to the main function of your company, Data escaping is secondary data, Or what is the same, everything else that has been created along the way.. For instance, a bank would consider all data on debits and credits of its customers' accounts as primary. Secondary data can include information such as a percentage of customer transactions that occur at ATMs rather than at a physical branch.

There are no standard definitions or schemes for data depletion, which tends to be gross and unstructured, but In many ways, is equivalent to the by-products associated with a company's machines and the core of online activities.. May include web browser streams, accessories, log files, Internet of Things devices and more.

2. It is usually bigger than Big Data

The term Big Data is itself a relative term that essentially boils down to anything that is so large that it cannot be manually inspected or worked from one record to another.. In general, data exhaustion tends to be even higher, mainly because there are few limits to what a company can collect.

To understand this better, we can say that google is the leader here. Literally collects everything, even before they know what to do with it.

That brings another cool feature of data escaping related to primary and secondary data: Secondary data from the data escape can become primary data once a use is found for it..

3. Has great potential

Data mining can be enormously helpful. In the banking example, knowing where consumers conduct most of their transactions can lead the bank to do a better job.

Not critical to the transaction, but it can be important to raise customer service to a better level. Proporciona un nivel de comprensión y contextualización de esta transactionThe "transaction" refers to the process by which an exchange of goods takes place, services or money between two or more parties. This concept is fundamental in the economic and legal field, since it involves mutual agreement and consideration of specific terms. Transactions can be formal, as contracts, or informal, and are essential for the functioning of markets and businesses.... o servicio principal que los clientes desean cada vez más..

Data exhaustion May contain important information that you may not be looking for today, but that could be useful in the future..

4. There may be risks associated with data exhaustion

It is generally about things customers may not be willing to give you. Therefore, there is potential Legal risks, marketing and public relations., around the use of this data, and you could end up moving your database away from customers or partners, when they know that you know things about them that they didn't want you to know.

The implications can be subtle. If an insurance company that uses GPS to locate your car in case of theft, took advantage of the fact that you can see the GPS location of all the parts where you have recently parked your car, for instance, could increase rates for customers. who habitually park in high crime areas. Without pretending to do it directly, you could build an algorithm that ends up discriminating rationally.

Another potential risk is saving primary and secondary data that will never be useful..

CIOs must balance the value of data depletion with the waste of keeping tons of useless data forever. But that is very difficult to do right now..

5. You have to make some decisions

The conclusion is that It is essential to be selective about what data is saved..

It is important to start making some decisions about what to dispose of. For instance, when it comes to smartphones and other devices, it is well known that much of the data is data associated with transmission, which is doubtful if it is useful.

And what is more, employees must approach the core of the business, in contact with the data. They may have immediate questions that show the relevance of some data right away.

From a technical perspective, companies need scalable storage technologies, as well as tools for data access. One of the hardest parts of working with data escaping is getting a single, consistent view around it. Cleaning and unifying that data can be challenging.

With primary and secondary data, companies do not usually worry at the time of collection, but it is important that at least the secondary data is cleaned. It is important to realize that it is not just about saying “here is this whole stack of data”. We need to do something with them.