Building a Data Automation System for an International Wood Wholesaler

Building a Data Automation System for an International Wood Wholesaler

JatApp developed a web-based system for automating large amounts of data. The solution allows transforming raw data into a single format for efficient data analytics and further integration with Salesforce.

  • Duration: 6 months
  • Country: USA
  • Industry: Ecommerce

Background story

Companies, big and small, collect and store large bulk of data to manage business processes and perform everyday operations. As the data is various and complex, it might be difficult to analyze it, as well as make data-driven decisions. Data automation allows companies to extract and transform raw data via automated tools, and make this data more comprehensive for a user.

Robinson Lumber Company needed a web system that automatically cleans raw data and transforms it into an appropriate format that allows to carry out thorough business analysis.

About the client

Our client is an international company that imports and exports wood products. Headquartered in New Orleans, it cooperates with clients and suppliers from over 70 countries. As Robinson Lumber is a wholesale company that operates worldwide, it has to constantly analyze the global wood market to effectively carry out strategic business planning and make the right decisions.

The company’s marketing team does research and gathers data on the competitors’ prices for lumber, their delivery time, types of best-selling wood products in a certain region, and more. It is a great number of CSV files in different languages and with duplicates that have to be manually cleaned and handled.

Since the decision quality directly depends on the cleaning and reliability of data, Robinson Lumber turned to JatApp to build a solution that would automate data processing, as well as make marketing research fast and cost-efficient.


When the Robinson Lumber Company came to us, they had two specialists that manually cleaned raw data and made it appropriate for analysis. It required much time and involved human errors that negatively influenced decision-making. To reduce time and costs, as well as improve data reliability, Robinson Lumber decided to build a data automation system that would replace manual operations.

The client also wanted the analytical data to be displayed in their Salesforce system. We cooperated with specialists from the client’s side and provided API documents to integrate the system with Salesforce.


  • Data extraction

    The software extracts unstructured and unformatted data from CSV files. As the process doesn’t involve manual operations, it saves much time and effort.
  • Data cleaning and transformation

    After data extraction, the data gets translated into one language, cleaned from duplicates and transformed into the required format. When the system receives flawed data, the software creates notifications for the company’s analysts.
  • Database aggregation

    Cleaned and reliable information is stored and categorized in the database. This way the information is summarized for analysis and decision-making.

Technologies Used

  • PHP
  • Laravel
  • MySQL
  • Python
  • Pandas


JatApp developed a solution that helps handle large data volumes – without the need for human intervention – and further analyze it for the company’s business needs.
Apart from its basic functions, like data cleaning and transformation, the software can generate data-based reports and graphs, as well as create notifications when necessary.


We developed a notification system for data analysts. In case some files can’t be handled by the system, employees get notifications and manually process this data.

Data reports and graphs

Based on the received data, the system can generate reports and build graphs. It simplifies the decision-making process for the company’s team and helps them discover new business opportunities.


  • Data cleaning
  • Data transformation
  • Notifications
  • Reports and graphs

Build a data automation system for improved decision-making

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