Big Data Management: 5 Things You Should to Know

It is increasingly common for companies to use big data platforms in order to manage all the information they need. And they store it in a safe but accessible place. When working with this technology you will also need specific Big Data Management tools and techniques with which to manage all processes in the most correct way.

In the following sections, we will explain five essential things you must know to properly manage Big Data. And preserve consistency in the results we obtained after carrying out the analyzes:

• Knowledge of the processes

• I work with modern technology

• The importance of quality

• Understand architecture

• Squeeze the streaming

• The need to know the processes

If there is something to highlight Big Data. It allows us to access a large number of data, which is why it is so important for companies. Currently, commercial users can access all the data and manage it by themselves from its original format. What is needed is that they know the process perfectly and leave aside the classic chains of warehouses such as Data Warehouses or Data Marts. Entrepreneurs must have an idea fixed in mind and that is that they want to scan the data sources and then develop their own reports or analysis always based on the business needs they have. This is what ensures them to squeeze the Big Data. What we want to say with all this is that Big Data can also be a self-service tool. A practice that is becoming increasingly established among entrepreneurs. But for this, you have to know the processes and have the right information.

Work with modern technology

Big Data is not the data model of yesteryear. This means that in the past, to store the data and prepare the subsequent analyses and reports. The process was carried out starting from a predefined structure where we could include all the information that we needed. However, when we talk about Big Data we have to take this idea away from the head since the expectation is very different. In this sense, it is necessary to comment that with the Big Data both the structured data and the ones that are not, can be stored in their original formats, without having to manipulate this information. This eliminates completely the predefined model to which we have already referred. The advantage over old models is that with the Big Data any user can access the information and then manage it and adapt it according to their own needs.

The importance of quality

Because the Big Data intends to present the data in its original format since there is no standardization or cleanliness in them. The quality of the information can be greater and it is much easier to adapt it to each user and transform it according to the needs that present. The absence of a predefined model offers greater freedom for users to use the data according to what they need at any given time. However, this freedom also becomes a responsibility, since they are responsible for transforming information. Thus, it must be borne in mind that, as a general rule, transformations and data management are simple processes. Although one must always make sure that these transformations are not opposed and that they do not come into conflict.

Understanding of architecture

In order to achieve greater performance, we must understand the architecture on which Big Data is based. It must be taken into account that Big Data platforms use a distributed storage system. These supports present data processing and also storage nodes to work in what is known as parallel computing. Although Big Data is very beneficial for users. It is advisable to familiarize yourself with the system in advance and avoid surprises that may be negative.

Squeeze streaming data

Times have changed and the data is no longer only gathered within a company for its file and correct analysis. At this time, data originates from all directions and in different ways. The streaming of data is constant and does not rest at any time, highlighting above all the variety of ways in which this information originates. The data is created and managed in different ways as part of this same streaming. There is data that comes from the hand of machines and sensors, devices and measurement systems that are connected to the Internet. Other of these data are generated by people and overturned in social networks, emails, blogs, and other media. There is also content and data that is created in an automated way through pre-configured systems. All this information is crucial and can make a difference if analyzed in a relevant way.