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Day: February 17, 2022

Overcoming privacy challenges in supply chain planning

Posted on by Imarticus Learning

Introduction

Supply Chain Planning is a crucial step in the supply chain management process. When you plan the several factors that can affect your supply chain process, you need to consider the privacy concerns that may arise out of it. Preserving any data involved in the supply chain planning process is crucial, and you should take all the necessary actions to ensure that privacy is maintained.

If you aspire to have a career in supply chain management, you can take up a supply chain analytics course to understand how privacy can be maintained in the entire process. 

A supply chain analytics certification will help you understand the privacy concerns but will also aid in understanding the entire supply chain division with both the advanced and the basic concepts. 

Ways in which privacy challenges can be tackled 

There are several ways to overcome the privacy concerns you might face while supply chain planning. Some of these ways are:

 

  • Go Digital

 

Switching from traditional processes and technology like fax, phone, and email is slow but necessary. Your organization establishes secure data transfer within your group and external trading partners, suppliers, and customers by upgrading to contemporary technologies.

Updating your software and procedures offers you access to data security methods such as:

  • Encryption
  • Tokenization
  • Monitors and alarms for file access
  • Preventing data loss.

You can train your people on how fraud can be prevented by using a digital system and how cybersecurity risks can be reduced if the company’s focus shifts to the digital growth and digitization of the entire supply chain process.

 

  • Encryption and Identification of Data

 

The National Institute of Standards and Technology (NIST) recommends businesses build defenses on the assumption that a breach would occur. As a result, you must protect all forms of data you store or communicate. You can utilize discovery tools to locate and classify files holding confidential information, financial data, or personally identifiable information. 

With this comprehensive view of all your data, you can implement current encryption standards to safeguard your most precious assets. As firms become increasingly reliant on online transactions, enhanced controls such as digital signatures, session breaks, and multi-factor authentication can help to strengthen supply chain security.

 

  • Risk Management through third-party

 

More and more organizations in the supply chain are collaborating to store, transport, and use data. This necessitates more comprehensive risk management, including end-to-end security.

Shared risk assessment among stakeholders is the foundation of effective third-party risk management. You’ll need to break down barriers between your technical and business teams, as well as enlist the help of vendors and partners. You can protect the supply chain’s most valuable assets by banding together. After that, you can determine the extent of any potential operational damage. If data is poorly managed, compliance issues, or any data breach, interference would be required immediately.

Conclusion

We at Imarticus aim to provide the best courses that help make all the students seasoned industry experts. You can enroll yourself in the Professional Certification in Supply Chain Management and Analytics by IIT Roorkee and Imarticus learning. This course in the SCM domain will make you ready for all the challenges that you will come across in the supply chain industry. 

Also, with a certification in supply chain management, you can get into high-paying jobs where you can prove to your recruiters that you are trained to work in the industry. Handling privacy issues is vital in the supply chain industry, and a course will help you understand and manage these issues. Enroll in this course today and reap all the benefits that the course has to offer.

Here’s how to develop a NLP model in Python

Posted on by Imarticus Learning

NLP or Natural Language Processing is one of the most focused upon learning models in modern times. This is especially due to how popular chatbots, sentiment analytics, virtual assistants, and translation tools have become. NLP empowers machines with the ability to process, understand and get meaning out of textual data, speech, or human language in general.

NLP allows other applications or programs to use human language. For example, the NLP model that powers Google understands what the user is searching for and fetches the results accordingly. Python online training can definitely help when one wishes to delve into NLP.

NLP models go much further than just finding the exact type of information and can also understand the context of the search or the reason and fetch similar or related results as well. NLP-powered machines can now identify the intent and sentiment behind the human language.

Developing Learning Models in Python

Python is a great language to use for NLP models as one can take the help of the NLTK package. The Natural Language Toolkit is an NLP package for Python. Additionally, you can also install the Matplotlib and NumPy libraries in order to create visualizations.

First, you need to have Python 3.5 or any of the later versions installed. After this, you must use pip install for installing packages such as NLTK, LXML, sklearn. If you decide to work with random data, you must first preprocess the data. You can use the NLTK library for text preprocessing and then carry on with analyzing the data. 

Here are the 4 steps involved in developing a learning model using Python:

  • Loading and data preprocessing
  • Model definition
  • Model training
  • Model evaluation

How to Develop an NLP Model using Python

Let us learn how to develop an NLP Model in Python by creating a model that understands the context of a web page. Once you have installed the NLTK library, you should run this code to install the NLTK packages:

import nltk

nltk.download()

After this, you will be asked to choose the packages you wish to install, since all of them are of very small size, you can install all of them.

Then, you must find a web page that you want to process. Let us take the example of this page on computers. Now, you must use the urllib module for requesting websites:

import urllib.request

response =  urllib.request.urlopen(‘https://computer.fandom.com/wiki/Main_Page)

html = response.read()

print(html)

Now, we can use the Beautiful Soup library for pulling the data out of the XML and HTML files. Also, this will help us clean the text of HTML tags.

Once, this is done, we can go ahead with converting the text into tokens using this:

tokens = [t for t in text.split()]

print(tokens)

Once the output is returned as tokens, we can use the FreqDist() function in the NLTK library for removing unnecessary words such as (for, the, at, a, and etc.) from our text and then plot a graph for the words that occur the most number of times. After this, the model identifies the most relevant words and then the context of the web page.

Conclusion

The auto-completion suggestions that we are given, the voice searches that our devices carry out for us are all possible with the advancements we have made in NLP. The PG in Data Analytics and Machine Learning offered by Imarticus is a great Data Analytics course with placement and can definitely help you delve deeper into concepts such as Deep Learning and ANN (Artificial Neural Network).