Data Analysis

Data analysis is a process of inspecting, cleansingtransforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.

If you know the enemy and know yourself, you need not fear the result of a hundred battles. If you know yourself but not the enemy, for every victory gained you will also suffer a defeat. If you know neither the enemy nor yourself, you will succumb in every battle.

Sun Tzu

If you have a company and managing your employees but you do not use an alayst for all these production to selling department. That means you do not know yourself as Sun Tzu said.

We offer you a supportive reports with additional advices in order to understand the how to improve your income.

Data analysis
Data Analysis

Data is just a stack of information, We help you in theses ways,

Cleaning the unnecessary informations,

Future Engineering

Artificial Intelligence used Models usage

-Highly effective report offer

Please click here to see our data analysis report on Heart Attack.


Machine learning (ML) is the study of computer algorithms that improve automatically through experience and by the use of data.[1] It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as “training data“, in order to make predictions or decisions without being explicitly programmed to do so.[2] Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filteringspeech recognition, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.[


Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervisedsemi-supervised or unsupervised.[1][2][3]

Deep-learning architectures such as deep neural networksdeep belief networksdeep reinforcement learningrecurrent neural networks and convolutional neural networks have been applied to fields including computer visionspeech recognitionnatural language processingmachine translationbioinformaticsdrug designmedical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance.[4][5][6][7]

Digital Pratix Data Analyst