Kazap Technologies
Machine learning and Big data: how important is it for a company?

Machine learning and Big data: how important is it for a company?

In the current reality, managers and entrepreneurs need access to complete and reliable information to manage their business. Without this data, the task of defining efficient strategies, and dealing with competition, becomes virtually impossible. Fortunately, this information can be ascertained by linking Machine Learning and Big Data.

Operating separately, the two technologies already have the potential to optimize companies, offering their managers a much higher level of control. When combined, however, this potential becomes even greater and makes room for a series of interesting insights to be identified.

Would you like to better understand the impacts of these technologies? Read the article and find out how they can benefit your business!

Big Data Concept

In a simpler and more summarized way, we can describe Big Data as a technology capable of capturing and classifying a series of data from different sources.

Through technology, a company can gain insights about the operation itself, identifying points in its production chain that must be improved, in addition to understanding the consumption habits of its customers, which allows it to make personalized offers.

A well-informed professional is able to avoid bad situations, or at least prepare for their impacts, and more easily identify opportunities. In this context, a large source of data, such as Big Data,is capable of revolutionizing the management of a company.

What is Machine Learning

We can say that Machine Learning is part of the concept of Artificial Intelligence. This is because technology is largely responsible for machine learning.

Technology can be described as a type of software capable of interacting with data, intelligently grouping it, and, based on it, learning and making decisions with little, if any, human intervention.

Thanks to its features, Machine Learning can perform a number of strategic tasks. Technology can, for example, analyze the performance of a group of individuals on social networks and, based on this data, indicate which products its participants are most likely to acquire.

Impacts of the union between Machine Learning and Big Data

While the data that makes up Big Data is extremely useful, its volume and complexity make it impossible for a person to be able to understand it and use their full potential. It is in this context that Machine Learning emerges as an effective solution. After all, technology is able to analyze and qualify information in a much more agile and accurate way than a human being.

Therefore, the integration between Machine Learning and Big Data makes room for a large volume of data to be properly treated and presenting the management team, in an intuitive, real-time way.

This functionality provides managers with a completely new level of control over the company’s processes. In addition, it grants management a lot of useful data for the development of intelligent business strategies.

Through this union between Machine Learning and Big Data, business controllers can more easily perform a number of tasks. Among them, we can cite the following as an example:

  • measure demand and acceptance of products or services;
  • produce more efficient marketing campaigns and target them to a more qualified audience;
  • identify productive and logistical bottlenecks;
  • market trends and find new opportunities.

Taking into account the impacts of technologies such as Big Data and Machine Learning, it’s easy to see that their use creates a real competitive advantage for businesses. Fortunately, the advancement of such technologies has made them much more accessible, so that even small and medium-sized enterprises are able to use them to their advantage.

Given its importance, however, and the level of data they need to deal with, it is important that those responsible for their implementation are reliable and empowered. Therefore, the idea is to opt for well-known developer companies in the market, such as Kazap Technology.

Now that you know how the union between Machine Learning and Big Data can benefit your company, how about sharing the article on your social networks and allowing your friends to access this knowledge?

For more articles click here.

Data monitoring: what is the importance and how to accomplish it?

Data monitoring: what is the importance and how to accomplish it?

Data monitoring can be described as the activity of monitoring a set of indicators responsible for demonstrating the situation of a factor, be it an object, a situation, or even an individual. In the corporate world, this practice allows managers to have access to the information needed to plan the direction of the company and base its decision-making process.

If we take into account the levels of competitiveness of the market, which become increasingly high, it is easy to realize that efficient data monitoring has the potential to become a real competitive advantage. Would you like to better understand this topic? Read the article and find out how data analysis can optimize your company’s results!

After all, why is data verification so important?

In a company, as efficient as processes are, there are always problems or procedures that can be improved. Through data monitoring, the management team is able to identify bottlenecks in an easier way, allowing them to solve problems more quickly.

In addition, by information, it is easier for companies to identify new opportunities for their products and services. Taking these facts into consideration, we can say data monitoring is important for companies to remain financially healthy and competitive.

How to monitor data?

While information analysis is highly beneficial for businesses, its implementation is not that simple. This is because even if every day a company generates a variety of data, capturing that information and organizing it —so that it can demonstrate patterns—takes a lot of time and effort.

In this context, it is worth mentioning that solutions in Big Data and Artificial Intelligence are very useful because they automate the process, which increases its speed and increases its accuracy, reducing the risk of errors.

What care should you take in monitoring data?

Finally, it is worth mentioning that, even using advanced technological tools, information analysis requires some care. Continue reading and understand how to perform it efficiently!

Decide what data will be monitored

First, the management team needs to decide what data will be calculated. This is because the accumulation of useless information would only make the task of identifying patterns slower and more complex. It is important that the evaluated data is actually aligned with the goal that the company wants to achieve, whether it identifies failures in its operation or increases its sales number.

Define the person responsible for the task

Once managers have decided what information will be analyzed, they need to assign a group of collaborators to carry out the task. It is important that the assigned personnel understand the subject that will be evaluated. Furthermore, they need to be able to use the technological tools available to their advantage.

Analyze the data

Once both the data to be monitored and those responsible for the activity are established, the team of employees should start studying the data at their disposal in search of standards, which must be transformed into indicators and presented to the management team — which allows them to base their decisions on solid and safe data.

As digital transformation advances,  making the market increasingly focused on the digital world, companies’ adaptability needs to increase, so that they remain aligned with the reality of the market. In this sense,  data monitoring and access to quality information are indispensable in the process.

Does your company already implement a data monitoring solution? Have you achieved results? Leave a comment and share with us your point of view on the subject!