How to use Hadoop for Predictive Analysis

How to use Hadoop for Predictive Analysis
How to use Hadoop for Predictive Analysis

The world of data science has been growing to new heights, and the community has worked closely in developing technology that can serve as framework and infrastructure, as well as a common resource for developers across the globe. Hadoop is one of these triumphs, becoming a cornerstone in the building of data science-driven enterprises, and how they begin to incorporate revised business processes and innovations into the business. As such, institutions have taken to providing in-depth educational programs for professionals and students to capitalize upon due to their relevance in the industry and the credibility it can create in a data science professional. Aside from being an expertise-driven platform, it allows professionals to be able to implement data systems across multiple industries and it is in huge demand for this exact reason, responsible for revolutionizing the way business treat and operate with data. The rise in applications for Hadoop data scientist certifications can be attributed to this. The largest aspect of its application in businesses rest upon its capabilities for predictive analysis, and it benefits businesses in primarily two ways.

  1. Classification Model- This is used for logistical functionalities and administrative responsibilities. The classification model uses a determinative system for predicting class membership or workplace retention. Existing to solve logic based problems, they are represented by 0 and 1 and it is usually one of those values which are attached to a particular outcome or result.
  2. Regression Model- This primarily relies on a predictive analysis that aims to measure the extent of the relationship between two variables. Factors like assessing and comparing business profits and even to predict future behaviours and events.

When it comes to predictive analysis, there are important factors to keep in mind when enterprises must deal with their consumer’s data for the sake of business strategy and growth. The process of predictive analysis entails interaction of in-house employees as well as external vendors who provide the platform to execute functions, and it is the responsibility of the enterprise to ensure user data integrity from mismanagement and security threats.  Another factor to keep in mind is the fast changing pace of international markets which must be accounted for when dealing with analytical processes as these markets affect a great number of variables. To receive accurate and actionable insight, those maintaining the values of variables and parameters must work tirelessly to ensure the systems remain up-to-speed with market trends and developments for accuracy and effectiveness.

Dealing with these factors are integral to understanding the capabilities of Hadoop in a professional environment, seeking to define the way businesses are able to collaborate with one another. The Apache framework for Hadoop is open-source and this has greatly enabled the growth of the industry in its desired directions, and even popularizing the act of obtaining Hadoop certifications. While we use predictive analytics to identify meaningful patterns behind big data, working on Hadoop allows professionals to tap into the vast community for resources and community support.

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