por One of the most relevant factors when making decisions and when doing data analysis or working on Big Data is the type of system that is going to be used. Therefore, in this article we tell you What are the characteristics of information systems vs. operational.
Information systems vs. operational: what are they
Among the databases that companies have in systems and IT areas, there are information systems vs. operational, which are those used in Big Data.
Operational systems are those in which old information is replaced by new information that enters.. To make it more understandable, let’s give an example: imagine that you are a customer of a company, you enter your file and your email appears, but you want to change that email. To do this, you call and ask them to update it, to which they respond by deleting the old email and adding the new one. The next day, when someone enters your profile, they will only see the new email.
What happens with this situation? For us, as analysts, this information is not practical, since What we need is the history of changes that have been made; We do not require information only from a day ago, but information from months or even years ago.
This is the reason why information systems vs. operational are much more robust, because They store larger volumes of data and every change that the operational ones make, the informational ones translate it as a record. This is how information systems work vs. operational.
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Information systems vs. operational: characteristics
Below are some of the most notable characteristics of information systems vs. operational:
Data sources
Information systems store consolidated data and external files. For their part, the operational ones store data that constitutes the original data sources.
Purpose of the data
While informational systems help in the analysis, planning and decision-making process, operational systems perform a execution and control of the main management tasks.
Insertions and updates
In the case of information systems, periodic and extensive updates are made to refresh the data; In the case of operational ones, they are made short and quick inserts and updates made by end users.
Consultations
In information systems, complex queries are normally made that require aggregations, crossings and filtering of data. In operational ones, standardized and simple queries are made, with typical responses of a few records.
Processing speed
In information systems, processing depends on the amount of data stored and the complexity of the queries. Refreshing the calculation of some of them can take hours. In the operational ones, the processing speed is usually very fast.
Space needs
In information systems, normally space needs are greater, due to the storage of historical data. In the case of operational data, the space may be relatively small if historical data is archived.
Design of the topic base
In information systems the database is denormalized, with fewer tables: star, snowflake data models, etc. In operational systems, the database is highly normalized, with a large number of tables.
Backup and recovery
In information systems, backups They are carried out with some regularity. Sometimes recovery consists of reloading data from OLTP systems. In operational systems, he backup it is essentialsince data loss can lead to loss of money and legal consequences.
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