Development for e-commerce *

Learning Shopify has been on my bucket list for a few years now. Plenty of people in my circle — friends, colleagues, and fellow devs — are all somehow involved with Shopify in one way or the other. Earlier this year, I finally had some breathing room between projects, so I figured it was the perfect time to give Shopify a proper look.

I started exploring the platform by setting up a dev store, poking around the admin, and skimming through the API manual. While this was a quick and easy start, it didn’t give me a deeper understanding of the platform. Plus, clicking my way through the UI felt repetitive and tedious.

That got me thinking: is there a more efficient, developer-centric way to manage a store? Something that I could run in a terminal, plug into a CI/CD pipeline, or script my way out of those mundane tasks.

Clean Go

Hey guys, I recently dove into 'Clean Code' by Robert C. Martin and found some valuable insights. The book is originally in Java, but I decided to reinterpret the principles in Go. Here's my take on the clean code concepts and how they can improve our coding practices.

1. Clean Code

The gist: Clean code is more than just working code; it's code that other developers can easily read, understand, and modify.

This is a translated and adopted article I wrote for the Aha'22 (30 May 2022) conference. It describes an approach to a marketplace prices optimisation. Here I've outlined some important definitions and tried to define the scopes and roles of ML, algorithms, and humans in optimal pricing. Although the article covers rather basic things, still, you can find out some new formulas and ideas, because these basics are somewhat "well-known only in a very closed clubs", and besides, the real gem found here is the detailed recipe for ML engineers how to build optimal pricing systems.

Effective data management is a critical aspect in retail. You have to manage information about customers, products, services, staff, materials, and so on. You should have a source that you will trust. And you need to store, process, moderate, and administer data in this system. 

Until recently, retailers only knew MDM - Master Data Management. A traditional MDM system is a system that knows about different data sources. It contains the “golden standard” of data. 

Imagine that your stores have one customer information, your online store has another, and your marketing services have third data. MDM system collects all these types of information in a single source. The system can find the same clients, spelled differently, and eliminate errors in the data based on different algorithms.

The evolution of MDM systems has led to the emergence of highly specialized master systems. Modern business does not need to implement a heavy MDM to manage only product data. There are PIM systems for this task.

When a company decides to build a marketplace, one of the most critical issues to solve is building interaction between all operational processes.

You need a system where you can manage and exchange customer, partner, and order data. Often the back-office of a marketplace consists of a complex of systems. However, we have been working with marketplaces for many years and have come to the conclusion that the integration between back-office systems should be seamless. At least between 6 fundamental parts. Thus, we have created the Scallium platform, where the business manages the processes of the marketplace.

Did you know!

An eCommerce platform empowers startups, SMEs, and large enterprises to manage multiple online business processes such as website, marketing, sales, and operations.

The top eCommerce platforms handle online business tasks efficiently, and this finally helps enterprises in expanding their productivity.

E-commerce today has become so frequent that it has become almost a standard chain of stores, where most people make purchases. But even online stores are trying to save money by becoming drop shippers and more working on additional implementations, rather than on the maintenance and payment of huge storage spaces.

• Handling multi-language data
• Multiple geographic locations
• Modification of product information within a product catalog
• Managing product information to be scattered throughout business processes

• Overall number of customer reviews on such reputable platforms as Clutch, Upwork, GoodFirms, App Futura, Extract.co, IT Firms.
• Overall score of those reviews.
• Presence of Fortune 500 clients in the public domain.
• Presence of industry awards in the public domain (e.g. Global Sourcing Award, Top B2B Global Leaders, Best of the Global Outsourcing 100).
• Team size (bigger companies come first).
• Year of fundation (mature companies have more trust).
• Number of offices (more is better).
• Number of brand mentions over the web (only companies with 1,500+ mentions are listed).

• Inter-bank transfer systems (see a research paper by Narula et al.)
• Privacy-focused management of digital assets (see a proof of concept by J.P. Morgan and zCash)
• KYC (see a proof of concept by ING)
• Self-sovereign identity (see an attribute-based credentials EU project)
• Voting (see a proxy voting prototype by Russian National Security Depository)