Netsmartz Builds a Data Engine for a Mexican eCommerce Firm

merama tech

MexicoLocation

2Team Size

eCommerceIndustry

Netsmartz’s engagement with Merama was primarily to work on data transformation from an existing portal to a new format, which they could then use to carry out high-level data analysis to suggest business notions for a strategic edge to their clients.

About The Company

Merama is based in Mexico. The firm partners with e-commerce players across Latin America in several categories to accelerate growth and profit by investing millions of dollars in working capital alongside a line of experts who aid in strategic and functional knowledge and proprietary technology to take eCommerce businesses to the next level.

About Company

The Tech Stack

python tech

Python

Team Composition

The two developers allocated by Netsmartz were Python developers with machine-learning capabilities. To facilitate a seamless engagement, Netsmartz also assigned a project coordinator.

The Problem Statement

The client wanted a software development partner to work on data.

That included all sorts of data analysis services (which entailed the ML Python skillset).

One of the primary reasons that they wanted to get Netsmartz onboard was the fact that they had a lot of portals to source data from. Thus, they required the additional pair of hands and seasoned engineers who could manage the data analytics front.

Furthermore, the client wanted us to write the algorithms necessary to sift through the data, gather meaningful insights, and deliver a report for analytical purposes.

The Challenge

Since the skill requirement was high, the client was looking for developers who could look for and suggest data-structural changes that could make the analytics and reporting more seamless.

There was also a big challenge in analyzing and identifying the endpoints where the data could be gathered.

Furthermore, there was an incumbent analysis for all these portals since they were constructed in different manners. That meant that the developers had to assess, and study the data sets (different in all), thus there was a need to find how each of these portals was making the dataset available before the transformation could be applied to it.

The client was funded and required a definitive RoI post their engagement with Netsmartz.

The Solution

Netsmartz started with two developers supported by a data analyst, who doubled up as the project coordinator.

The project coordinator started to review the various portals that were required to be included in the data transformation process.

The team then analyzed each of the portals and their constituent datasets, as well as endpoint APIs, and started creating documentation on how data can be fetched from each of these portals.

The team then proceeded towards creating a central data transformation framework that could cater to the different datasets provided by the individual API endpoints.

Each individual API endpoint was programmed so that the overall data transformation engine could be completed.

Our Process

Netsmartz followed the following process to fulfill the requirements of the client:

Mapping & Vetting Developers

The preliminary task was to identify senior resources to dedicatedly work on the project. Since the project was intensive in its skill requirements, Netsmartz allocated a project coordinator to ensure seamless collaboration.

Client Interviews

After the resource selection, the developer candidates were introduced to the client for further vetting, and interviews. This process also included getting the developers acquainted with the client, their requirements, their processes, and their methodologies.

Team Engagement

Post the team selection, we started with assessing the client’s requirements and understanding their tech stack and engineering requirements.

Scaling Project

After the initial discovery and assessment, the Senior resources worked on the data transformation project to encapsulate multiple datasets and data sources.

The Result

The primary achievements of this project were:

  • Setting up the senior resources to take over the ownership of the project end-to-end, from assessment to building a data transformation engine.
  • Enabling quicker allocation of resources development – thus significantly boosting the time-to-market.
  • The data transformation was further used for further projects and data sets – thus making the Engine crafted by Netsmartz resources, the Centralized engine used by everyone in the client’s organization.
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