What is big data?
The term Big Facts
has been in use since the 1990s. They are amounts of
data with many volume levels that come from different sources and do not stop
arriving. Of great complexity and that cannot be treated by
conventional software, they need a lot of counting power.
First, when talking about big data, we also talk about: macro
data,
big data, or large-scale data. It
seeks to analyze and study user behavior, collect stored data and make predictions
of observed patterns. It is a critical technology in digital
transformation and one of the most in-demand skills. Big data is used when
you have to work with large volumes of information, which require a large
storage capacity on a single machine, computer, or server. Therefore, big
data is not only technology; it is also a step beyond statistics.
Second,
it is the raw material of demography and ethnography, useful in market research
for any company. Also, for governmental and non-governmental organizations. This
requires breakneck response speeds to obtain the correct information at the
desired and precise moment. The central objective is decision-making in
each company and the need to seek experts in each area.
Benefits of big data
·
Change
management, with the search for new business opportunities through improved
segmentation and cross-selling of products. All this by applying
predictive analysis and modeling to account and customer data.
·
Analysis
of web browsing and online consumption habits. For example, analysis of
social networks.
·
Anticipation
of problems.
·
Improvement
of current processes, with simplification in execution.
·
Online
advice is offered for decision-making, running through automatic algorithms.
· The cost reduction it brings.
The big data tools
They are designed to process large and complex data sets. Includes
sales reports, web analytics, loyalty programs, customer databases. The
key is to link all the information in a program with access control to use the
work team.
Consequently, there are four dimensions of analysis that allow us
to achieve all the benefits of big data tools, such as:
·
Descriptive:
describes what happens at the moment.
·
Analysis
and diagnosis: describe or explain why something is happening.
·
Predictive:
the anticipation of probable and results.
·
Prescriptive:
specify how to make something happen.
Big data software
Next, we present a list of big data tools that offer
solutions for exploiting this software. They are open-source that cover all
processes: storage, processing, and analysis:
·
Hadoop
·
MongoDB
·
Elasticsearch
·
Apache
spark
·
Apache
storm
·
Language R
·
Phyton
Hadoop, one of the most used big data
tools
Lastly, Hadoop is a technology that is regarded as the
father of big data. His great trick is to divide an enormous task into many
small ones and then re-unify them at the start. It is the framework par excellence for the management and storage of
large volumes of data. Companies such as
Facebook and Yahoo use it to analyze and process this data.
Ultimately, the Hadoop library uses simple programming
to handle large clustered data sets. Run many processes
at the same time and create redundancies to avoid losses.
In conclusion; It is one of the considerable data tools par excellence. It is an excellent system for processing
large volumes of data. However, it is not
intended to be done in real-time, as it has high latency.
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