AgensGraph Use case # 1.
POS System Solutions + Graph Database
The representative advantage of GDB(Graph Database)!
Suggesting many of the solutions using Recommendation Engine.
The IT industry is actively trending to the Fourth Industrial revolution wherein an inordinate amount of diverse data will have to be intelligently assessed. Many companies still use Relational Database (RDB) to process this diverse data.
However, If you can use Graph Database (GDB) to effectively handle this data, how will the situation change? In this blog, the use case of our Partner – Datametrex, will demonstrate the value Graph DBMS can provide.
Situation & Issue
Datametrex is a publicly traded company through the Toronto Venture Transaction (tsxv). It is an Internet of Things(IOT) company that provides datatap solutions to enable customers to access and analyze transactional data from Point of Sale (POS).
This ‘Datametrex Solution’ is a visualization tool that helps enable customers manage their stores. i.e. inventory management, balance check, increase sales, product price by region, etc. However, since RDB utilizes data in fixed tables, this provides only limited analysis to customer.
AgensGraph has the advantage of speeding up data processing by using non-fixed data without having to match the data collected from the transaction of POS Terminal to a fixed frame. Additionally, AgensGraph has the advantage of realizing relational points on specific data to calculate the combination between products, and to make new analysis based on this. It also has the advantage of looking at the relationships of data with virtually unambiguous links, which seemingly unrelated.
With AgensGraph changing the fundamental technology in the way that data is collected, stored, and processed, customers of AgensGraph use highly innovative services.
For example, by analyzing the residence time of consumers in a retail store, it is possible to efficiently manage the price and inventory of the product. And it can be applied to a variety of marketing / promotions such as bundled product development and sales by applying the results of period and region demographics.
AgensGraph also offers more value than relational databases. It can instantly collect and analyze data that specific customers and organizations have the unspecified relationships, such as search patterns, characteristics, and interests. So, it can provide real-time data on related products, services and organizations.
Thus, AgensGraph effectively integrates and manages data from disparate and disparate sources, which provides new value to customers and helps them find the best solutions.
– Enhancement recommend engine system for service or product through analyzing relationship or pattern between data
– Enhancement existed service
⇒ Sales increase (After adopting AgensGraph, the company has become able to analyze the relationship of other products purchased by customers who bought certain products)