Textile Trade Intelligence

In today's era of consumerism, running a textile and apparel business is a lot more than finding the right vendors, suppliers, and consumers. In the digital era, all-size business needs to understand their marketing potential on various parameters such as ? needs, demands, supply, value, and quality

Project Title

Textile Trade Intelligence

Project Area of Specialization

Artificial Intelligence

Project Summary

In today's era of consumerism, running a textile and apparel business is a lot more than finding the right vendors, suppliers, and consumers. In the digital era, all-size business needs to understand their marketing potential on various parameters such as – needs, demands, supply, value, and quality. New global markets and increasingly demanding consumer expectations are forcing companies in each corner of this sector to make the most of every resource at their disposal. Manufacturing and supply chain solutions need to be cost-effective and drive efficiencies that provide management with the ability to maximize productivity. Our goal is to create a framework which features Business Intelligence which encompasses data mining, process analysis, performance benchmarking, and descriptive analytics. It has empowered textile and apparel businesses with marketing insights. It provides insights into various markets based on hard-core research and market analysis. It will provide in-depth reports for various products showing how they are performing in markets across the globe and also analyzes brands and retailers' performance to generate their performance report. Based on that, any business can analyze the performance of other companies in the global market. We will use data from around the globe, analyze it's behavior and find trends and hidden patterns which would help buyers and sellers to make better decisions.

Project Objectives

The objective is to create a framework that provides insight through data by determining market potential on various parameters such as needs, demands, supply, value and quality and makes use of historical data to get knowledge of the present and the past in order to show future trends on how the market shall behave, thus, increasing the revenue generated by vendors and sellers.

Project Implementation Method

Data Analysis Data analysis is the process of collecting, modeling, and analyzing data to extract insights that support decision-making. There are several methods and techniques to perform analysis depending on the industry and the aim of the analysis.

Predictive Analytics Predictive data analytics refers to using historical data, machine learning, and artificial intelligence to predict what will happen in the future. This historical data is fed into a mathematical model that considers key trends and patterns in the data. The model is then applied to current data to predict what will happen next. Train the system to learn from your data and can predict outcomes. When building model, we have to start by training the system to learn from data. Our predictive analytics model will eventually be able to identify patterns and/or trends about different market across the globe. We will be using following model.

LSTM Model: Sequence prediction problems have been around for a long time. They are considered as one of the hardest problems to solve in the data science industry. These include a wide range of problems; from predicting sales to finding patterns in stock markets’ data, from understanding movie plots to recognizing your way of speech, from language translations to predicting your next word on your iPhone’s keyboard. With the recent breakthroughs that have been happening in data science, it is found that for almost all of these sequence prediction problems, Long short Term Memory networks LSTMs have been observed as the most effective solution.

Data Visualization Using Business Intelligence Business intelligence is the process by which enterprises use strategies and technologies for analyzing current and historical data, with the objective of improving strategic decision-making and providing a competitive advantage. We make use of business intelligence and data visualization software’s, both of which are optimized for decision-makers and business users. These options generate easy-to-understand reports, dashboards, scorecards, and charts. Machine learning used alongside business intelligence enables BI tools to adopt more business-friendly interfaces; after all, when algorithms perform the heavy data lifting, the user won’t need the same technical expertise to find what they need. Power BI is a collection of software services, apps, and connectors that work together to turn unrelated sources of data into coherent, visually immersive, and interactive insights. W

Benefits of the Project

The textile and apparel industry currently lacks transparency in each stage of the product’s lifecycle. Creating transparency between vendors and sellers about the product traceability with regards to every component used by the community of textile in the global marketplace. Thus, using the past and present data for the textile industry's market trends, business intelligence available in a framework will aid businesses/ vendors and customers in making important business decisions such as when they can acquire a component/ product at the least price or at what time of the year they can gain a huge profits by selling a particular raw material/ component. This information will directly benefit business owners and the government. The lack of technology forces the industry to export raw materials at a relatively slow rate which have low reliability in general and lack diversity. Exporting and importing from different countries requires certain knowledge about the products, and a lot of authentication to seller and buyer too. In a traditional textile industry, whether its raw material suppliers searching for buyers, or apparel manufacturers looking for retailers, delivery processes take a much longer time. Retailers often end up out of stock, delayed or overstocked, since market trends are changing far faster than their procurement time. Proper flow of information among textile supply chain members is crucial. As such, the flow of information can influence the performance of overall supply chain operations. This information includes data about customers and their demand, inventory status, production and promotion plan, shipment schedules, and payment details. As textile businesses go global, opportunity increases, however, fierce competition also arises. With an increasing number of competitors fighting for a greater share of global market, it is vital to maintain a good online presence. The more easily your business can be found online, the more business opportunities you will have.

Technical Details of Final Deliverable

Our final deliverable will be a platform for Textile Industry which will display Future stock prices for different textile raw materials and latest news regarding global textile industry , Reports using power BI and prices in the form of graphs. We will use Python,Django,HTML,CSS, javascript ,Bootstrap and Power BI.

Final Deliverable of the Project

Software System

Core Industry

Manufacturing

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Big Data

Sustainable Development Goals

Decent Work and Economic Growth, Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com