In order for us to carry out a good Big Data administration, it is essential that the team of experts carry out a data creation procedure whose main characteristics are scalability., intelligence and flexibility. In this context, Attention must be paid that for the correct administration of the big data architecture we must look at several essential pillars who will be the ones to mark this administration in the future. What pillars are we talking about?
The integration
To properly integrate the Big data in our company, a series of actions that condition the correct administration of all data what are we managing. It stands out the use of all the tools that we must have available so that the access that we have to this data is as fast as possible. in addition, such data must be universally connected, which will allow us to have full access to all of them, even though they may come from different sources.
Yes indeed, It is also essential to take advantage of all the structures that we have available in the hardware and we must centralize the administration and governance of that data. We cannot forget to comment that within this procedure another of the fundamental actions is to give priority to the data that we have available according to the use that we are going to give them.. To obtain this objective we will have to divide all this information into functional departments known as Staging Areas..
Quality
After the integration of Big Data, it is necessary to pay attention to the quality of the data we manage, since this must be automated so that governance can be improved of the data, always bearing in mind that this information will be found within the context in which the business in question operates. Quality is another of the fundamental pillars of Big Data, enabling us to better manage data relationships and make master data relevant.
Security
To achieve the best security within Big Data we can do different very useful actions. Experts opt for security measures to enter this data such as authentication, encryption or masking of information. At the moment, one of the most widespread measures is tokenization, that it is about replacing the most sensitive data with less important ones and thus keeping the first 100% insurance.
How is the Big Data architecture?
This is created from three layers keeping in mind the technological requirements that each of them must meet. We find a first layer that focuses on the analysis and visualization of the data, getting great importance. The second layer is that of Big Data management and the third is used for storage. Regularly, entities focus on the first and third layer, even though it must be said that the second is also very important and that much more must be taken into account. What can we find in each layer?
First layer
It is the Big Data analysis that is done through multiple actions. This way The data will be displayed first and the tools will be used. as predictive analytics, more advanced statistics and machine learning technology.
back cover
There are three pillars in management: data integration, governance and security. It is necessary to incorporate the data that have a higher performance, processing them in an optimized way, making sure they are scalable and of course, that are implemented with the greatest flexibility. For his part, data governance will focus on the preparation of all the information that we manage, making sure it is of the highest quality. These data will be given a lineage and all the relationships between them will have to be detected. Finally, security is used to analyze risks, keep sensitive data under control and protect it as much as possible with a maximum protection policy.
Third layer
Relates to data processing and storage, not using SQL system, sino Hadoop o MPP, the massive parallel processing system. The correct use of the three layers and the application of this knowledge in the day-to-day of the company will depend on whether companies can successfully manage Big Data.
