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Introduction to Business Intelligence and Big Data

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Introduction to Business Intelligence and Big Data

One of the most fashionable terms in the digital and business world is business intelligence, a term that goes hand in hand with Big Data. Both concepts are part of the movement of digital transformation companies. In this article I will make a small introduction about Business Intelligence and Big Data , so that you can get an idea of ​​the importance of applying it in your company.
What is Business Intelligence?

When we talk about BI we refer to the ability to transform the data we have into information , and later into useful knowledge for the company. It is the Israel Mobile Database best way to optimize the decision-making process.

From a more pragmatic point of view, we talk about the set of methodologies, technologies and applications that allow us to transform all existing data , whether from internal sources or external sources, into structured information for its exploitation, analysis or knowledge.

Business Intelligence provides a great competitive advantage for the company, since it will obtain privileged information to take the correct steps in business.
Relevant Business Intelligence Terms Israel Mobile Database

A continuación, muestro una serie de términos muy habituales en el mundo del BI y del Big Data. Términos que es necesario conocer para poder entender un poco más este complicado mundo:

Datamart: it is a departmental database. That is, in that database we will only find information about a specific department of the company, be it finance, marketing or logistics. It is characterized because its data structure is optimized to study the specific data of that department .

Datawarehouse: this is the corporate database. It integrates and refines the information from the sources, so that it can later be analyzed . The creation of a data warehouse is the first step to implement an optimal strategy for the company. Its main advantage is the way in which the information is stored, the most famous being the star or snowflake tables. The information in this case is homogeneous and reliable, thus allowing a hierarchical treatment of it.

ETL (Extract, Transform & Load): extraction, transformation and loading of information. It is the process to get the data to become valuable information, the ETL process. It is obtained the information , both internal and external, subsequently, from the various sources is done one filtering , cleaning and grouping information and finally, data is organized in a database.

Datamart OLAP: they are based on OLAP cubes, which are built by adding the necessary indicators of each relational cube.

Datamart OLTP: the most common thing in this case is to optimize performance, through filters for example, and thus take advantage of the particularity of each department. business intelligence y big data
What is the big data?

When we talk about Big Data, we refer to the large volume of data , both structured and unstructured, that exists. Although the important thing about Big Data is not the data itself, but what can be done with that information . Big Data is usually more related to the external databases of the company, and as I will explain in the next point, the high speed of data generated in a short time is the main problem. You have to know how to differentiate good data from those that are not, because, after all, if we use poor quality data, the decisions will not be correct .
What are the 5 V’s of Big Data?

Big Data is composed of 5 dimensions that characterize it, below I define the 5 V’s of Big Data:

Volume: the volume to be analyzed is massive. Terabytes of information are produced every day, and the capacity of the databases is doubling every two months. To give you an idea, all the data produced in 2 days represents more information than all that generated up to 2003. This makes managing this data a challenge .
Speed: the flow of data is not only massive, it is constant . The great speed of data generation causes them to become out of date quickly. So companies must be skillful, and they have to collect , store and process that information at great speed .
Variety: the origin of the data is very Brother Cell Phone List heterogeneous. From different sources, internal and external, and can come they structured or unstructured, being e l 80% of the data of the unstructured Big Data .
Truthfulness: many data are incomplete or of poor quality, and if we use the wrong data, we will make the wrong decisions in the company . The uncertainty about the veracity of the data raises doubts about the quality of the data in the future. That is why it is important to ensure that the data collected is valid.
Value: once the data is transformed into information, we must know what value they provide us. The more value the data has, the more performance we will get out of it.

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