Data Analysis: Why Does It Make Better Decisions?

You wonder what is data analytics and how could it benefit your company? We could understand data analysis as the practice of an Olympic sport; requires clarity of objective, discipline in the preparation and confidence in execution. Data analysis is the permanent exercise of transforming facts into data, accumulating them in an orderly fashion and observing collective behaviors through specific, replicable and well-founded methods. It is not by chance that today we see the rise of disciplines such as Data Science or Data Analytics.

How can a business benefit from analyzing its information correctly?

The digital age is now, both for the amount of services available online and also for the number of interconnected users. It is estimated that in Mexico there are almost 81 million inhabitants using smartphones, that is, they generate digital information through their online interactions and this trend will increase. Suffice it to observe that the 86% from European citizens connect and use their smartphones for personal purposes. In other words, overwhelming amounts of data and potential information. Correctly analyzed data becomes assets, but not just any data is valuable nor will any analysis add value, this will begin to occur as a data culture Inside the company. This data culture must align with objectives of the company as the first foundation. Second is due permeate collaborators in the search to update their skills and diversify the available sources of data, and as a third party generate relationships relevant between the different data sources, the objectives, targets and indicators to visualize said data. This will allow trends and behaviors to be explored, allowing reflection and deepening on them thanks to the accumulated experience of the company, which will be the main asset in the transition and maturation process in the implementation of this type of strategy. If these foundations can be established, companies will know identify where bottlenecks are occurring in the purchase or contracting of their services. Will be able to model scenarios based on past events and thus better prepare for the contingency, as well as, automate processes freeing up the workforce to reorient it in areas of greater relevance such as personalizing customer service.

Different areas of data analytics that exist

There are many associated concepts when defining what data analysis is and many times they circulate as if they were the same, but they are not.
  • Data Analytics: Systematization and use of both structured and unstructured data on a reduced scale and whose objectives are to improve statistical analysis, visualize possible relationships and / or conclude past events.
  • Data science: Science that supports the use, structuring and exploitation of data. She addresses greater volumes of information, structures analyzes more rigorously and develops predictive models with a view to a possible future.
  • Big data: High volume, variety of sources and speed in data processing. One way to differentiate it from the previous two is that the data repositories cannot be hosted on a single computer or server, but are obtained at high speed from different sources.
  • Machine Learning: Modeling and creation of algorithms that will allow computers to consume data and use it to learn and interact automatically. It is part of what we understand by Artificial Intelligence.
The internal development of the necessary skills can take time, for that reason it is that while that happens it must count on support of professionals in the area and even venture to receive advice. In said field Codster it can make the difference between a smart spend and an investment with which to take the right steps in corporate data culture.
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