Primary and secondary data to explain big data and data exhaust

[shukla7789]

Big data and data exhaust are primary and secondary data related to the core of your business and other data that is created daily respectively.
Big data is already well known by many companies, while data exhaust is much less so. Big data is primary data related to the core of your business, while data exhaust is secondary data that is created every day . Primary and secondary data will help us today to explain a little about big data and data exhaust.

primary and secondary data.jpg

To see the differences between Big Data and data exhaust based on primary and secondary data, we are going to look at 5 things that need to be understood about data exhaust in order 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 exhaust has been around for over a decade, having linkedin database in the wake of new data streams coming from smartphones . Today, more accessible data tools are bringing data exhaust to the forefront.

Primary and secondary data have a lot to do with this. If big data is primary data that relates to the core function of your business, data exhaust is secondary data, or in other words, everything else that has been created along the way . For example, a bank would consider all data about debits and credits on its customers’ accounts to be primary. Secondary data might include information such as the percentage of customer transactions that are made at ATMs rather than a physical branch.

There are no standard definitions or schemas for data exhaust, which tends to be raw and unstructured, but in many ways is equivalent to the byproducts associated with a company's machines and core online activities . It can include streams from web browsers, plugins, 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 with on a record-by-record basis. In general, data exhaust tends to be even larger, primarily because there are few limits on what a company can collect.

To understand this better, we can say that Google is the leader here. It literally collects everything, even before you know what you are going to do with it.

That brings up another interesting feature of data exhaust related to primary and secondary data: secondary data in data exhaust can become primary data once a use is found for it .



3. It has great potential
Data exhaust can be hugely useful . In the banking example, knowing where consumers conduct most of their transactions can lead the bank to do a better job.

It is not core to the transaction but can be important to elevate customer service to a better level. It provides a level of understanding and contextualization to this primary transaction or service that customers increasingly desire .

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