What is Big data? What is Big data for?
Big data is the process of working with huge amounts of data, this capacity exceeds that present in conventional applications to capture, process and store such information in a reasonable time.
That is why the concept of Big data brings with it infrastructures, technologies and services created explicitly for managing this large amount of information and give it relevancy in record time.
1. What is Big data for
Big data is used to make relevant decisions based on the information previously obtained and processed according to our needs. To create these databases, we can use various analytical methods to combine and isolate the information as reliably as possible. Big data can be applied to almost any field, here are some of its most common uses:
– Comparative analysis. When customer behavior is known and can be observed in real time, it is possible to compare their current behavior patterns to identify opportunities.
– Machine learning. Machine learning makes use of big data to develop automatic learning models for large amounts of data without the need for human intervention (or minimal intervention).
– Product development. Based on previous or current products, predictive models are created for new products and services through the classification of key elements.
– Scalability and error prediction. Big data can foresee problems before they happen by using data analysis (both structured data and unstructured or semi-structured data) and remedy them by focusing on the area where the conflict is foreseen.
– Customer experience. With big data, the information can be collected from multiple sources (social media, web browsing, use of mobile terminals, etc.), all of which enables personalization and more efficient decision making.
– Fraud. The capabilities of Big Data to identify suspicious or unusual data patterns allows fraud detection and prevention.
2. The 5 keywords of Big Data
For a correct management of the huge amount of data handled by Big Data, it is necessary to know the five dimensions that make up Big Data, the so-called 5 keywords. They are:
The amount of data generated is continuously increasing and as the databases grow, the applications and architecture built to support the collection and storage of data must grow/evolve.
La inmediatez prima, dado que los datos se generan a una gran velocidad y muchos de ellos quedarán obsoletos en poco tiempo, perdiendo su valor cuando se obtengan otros más recientes.Immediacy takes precedence, since data is generated at high speed and much of it will become obsolete in a short time, losing its value when more recent data is obtained.
Therefore, the speed of analysis is one of the fundamental characteristics of large-scale data management and therefore the algorithms, which are increasingly complex, must learn to process this information as fast as possible.
Given that data comes from different places and scenarios (social media, mobile, proprietary architectures, etc.) and in different formats (images, video, text and audio), collecting, storaging and managing this information is a challenging task.
Knowing the reliability of the information collected is of vital importance, as it can be incomplete or come from sources that are not entirely verified (social networks). Therefore, depending on the applications to which this information is used, effective filtering is of vital importance and provides a full-fledged competitive advantage.
The value dimension refers to the useful information that can be extracted from the data once it has been processed and analyzed, generally a large amount of data is necessary to obtain a really small amount of valuable information. Value is the foundation of knowledge and this results in taking the right action or making the right decision.
3. Benefits of Big data
After all that has been shown, it is very likely that you are asking yourself this question, but what are the benefits of big data? Well, the truth is that there are several, among which are noteworthy:
- They are a set of very agile and flexible technologies that provide solutions to the huge collection of data that are constantly collected.
- The software used is usually open source or public domain, which allows us to have a large community of developers who improve systems and processes without cost and even specific places to resolve doubts.
- Reliability, speed and adjusted costs, compared to what a traditional storage infrastructure would entail. You generally pay only for what you use.
- Big data is scalable, so if your data grows, you can add more systems to process all the data. So you will only pay more when your project grows.
- Meet your goals If well used, Big Data helps to achieve the desired objectives whenever the process has been planned efficiently in all its phases; it allows us to draw conclusions with a solid base and future predictions.