Skip to main content

BECOMING A DOCTOR TO DATA


The world of forensics is so fun and thrilling that almost every one of us at one point of time wished to be involved in the field of forensics. Seeing our favorite actors and actresses on screen do intriguing and enthralling stuff using some really mind-boggling techniques and technology always used to attract a lot of us in doing something similar right! Well, let us explore one such field of forensics and try to give you a little insight and a possible jumpstart to do something that a part of you always wished to.

IMPORTANCE OF DATA
Talking of doing riveting stuff with the best technology at your disposal, the best field to do so would certainly be in the world of data. There is no doubt and questions in regards to the fact that the field of data and its related studies have made a serious breakthrough in revolutionizing each and every industry on unprecedented levels. The power and potential of data has been identified by each and every business and organization in the world. From gaining simple insights on something to taking the biggest of decisions, the driving force behind each and every action taken by businesses is the set of data that they have: the security and maintenance of which has become a major part of concern as well as expenditure for them.

WHAT IS DATA FORENSICS?
With streams of data flowing in and around from unknown perimeters in the modern world, it has become very difficult to predict and analyze the legitimacy of its source. The advent of the internet has also made cases and events of cyber crime a common thing. Fraudulent and malicious links disguised as perfect and legitimate sources duping people of their money, information, or anything critical is something we see and hear every day. This is exactly where the field of data forensics comes into play. It involves the study and investigation of the chain of events in order to track down the lost piece of information to its source. This involves a high amount of identifying and analyzing the attributes of the digital data that was created, and then pinpointing its blueprint/mark to an exact source where whatever was lost is being kept.
The analysis of the data can either be done in a cross-drive manner: where information retrieved from various hard drives is linked together to create a web-like structure that ultimately points to its center, or using live analysis: where evidence is gathered in real time by analyzing the series tasks that the operating system of the host computer performed in order to identify something fishy and peculiar and which could be a possible source of the cybercrime.


RESOURCE BOX
The field of data science and its applications pack a huge potential in regards to a career in the modern world. Being involved in it is something that will really pay off in the times to come. Get a certification in data science in bangalore today from ExcelR one of the best institutes for data science there is.


Source : https://excelrdatascience.blogspot.com/2019/04/learn-data-science-from-experts.html

Comments

  1. Hey, thanks for this great article I really like this post and I love your blog and also Check marking analytics manager in hyderabad at 360DIGITMG.
    360Digitmg marketing analytics manager in hyderabad

    ReplyDelete
  2. This is exactly the information I'm looking for, I couldn't have asked for a simpler read with great tips like this... Thanks! ExcelR Data Scientist Course In Pune With Placement

    ReplyDelete

Post a Comment

Popular posts from this blog

Understanding Logistic Regression using R

  1. What is Logistic Regression? Logistic Regression is one of the machine learning algorithms used for solving classification problems. It is used to estimate probability whether an instance belongs to a class or not. If the estimated probability is greater than threshold, then the model predicts that the instance belongs to that class, or else it predicts that it does not belong to the class as shown in fig 1. This makes it a binary classifier. Logistic regression is used where the value of the dependent variable is 0/1, true/false or yes/no. Example 1 Suppose we are interested to know whether a candidate will pass the entrance exam. The result of the candidate depends upon his attendance in the class, teacher-student ratio, knowledge of the teacher and interest of the student in the subject are all independent variables and result is dependent variable. The value of the result will be yes or no. So, it is a binary classification problem. Practical Implementation of Logistic Re...

785 Enterprise Analytics Jobs In Mumbai, Maharashtra, India (38 New)

Choosing the proper and greatest digital advertising courses in Delhi & NCR is an ideal determination to make for better career and to work in smart method on larger salaries or ensure a better supply of earnings. Boston Institute of Analytics is an international organization that imparts coaching in predictive analytics, machine learning and synthetic intelligence to school college students and dealing professionals by means of classroom coaching carried out by business experts. In this teacher-led, stay training (onsite or distant), contributors will learn how to use SSAS to analyze giant volumes of data in databases and knowledge warehouses. BBA business analytics & knowledge science is India's first specialised Undergraduate program specializing in the data science and enterprise analytics business. Dr Abhijit Dasgupta, Director - Large Information & Visual Analytics, was a source of fixed assist and motivation together with every different faculty member we stu...

The Concept of KNN Algorithm Using R

Understanding the Concept of KNN Algorithm Using R   The huge amount of data that we’re generating every day, has led to an increase of the need for advanced Machine Learning Algorithms. One such well-performed algorithm is the K Nearest Neighbour algorithm. In this blog on KNN Algorithm In R, we will understand what is KNN algorithm in Machine Learning and its unique features including the pros and cons, how the KNN algorithm works, an essay example of it, and finally moving to its implementation of KNN using the  R Language. It is quite essential to know Machine Learning basics. Here’s a brief introductory section on what is Machine Learning and its types. Machine learning  is a subset of Artificial Intelligence that provides machines the power to find out automatically and improve from their gained experience without being explicitly programmed. There are mainly three types of Machine Learning discussed briefly below: Supervised Learning: It is that part of M...