Facing the challenge of data scatter and subsequent operational errors may seem common to many multi-industry corporations, and here we give you an example of how Kaprikorni successfully copes with this.

Customer

The Customer is a multibillion-dollar corporation that manages over 30 different businesses and does business with over 300 well-known international brands. The business engages in operations in a variety of sectors, including engineering, logistics & inventory, financial consulting for the automobile industry (for banks, investment organizations, etc.), retail, food & beverage, advertising, and more.

Challenge

The enterprises owned separate IT infrastructures. As a result, operational data was separated across various CRM, ERP, POS, e-commerce, supply chain, and other corporate platforms. The following problems were experienced by the Customer as a result of the disintegrating data:

  • Data reliability was hampered by errors that resulted from manual data transfer. Furthermore, because manual inputs were dependent on employee schedules, the data wasn’t readily accessible.
  • The workers were unable to swiftly gather an accurate picture of every consumer interaction with the company.
  • An advanced conglomerate-wide loyalty program could not be implemented.
  • It was not practicable to automate reporting in all business directions.

Solution

The consulting team at Kaprikorni began by carefully examining the Customer’s applications before determining the needs and issues that were currently present. Our specialists identified current business processes, information flows, technical details of communication protocols, data formats in use, and the necessary data refresh rates during numerous Q&A sessions with the senior management of each company.

Creating an architecture for application integration

IT specialists from Kaprikorni proposed to implement a layered architecture. Four levels made up the suggested architecture scheme, each of which performed a specific duty and purpose

The enterprise service bus (ESB) and/or extract, transform, and load (ETL) services were the foundation for the suggested integration, allowing for two methods of efficient data interchange. The rapid and comparatively light actions (messaging) between a data source and another data source or the underlying layer should be the responsibility of the ESB. Routing messages, keeping track of message exchanges, storing messages, and validating message formats were done by ESB.

The task of loading enormous amounts of data should primarily fall under the purview of ETL (extract, transform, and load) tools. ETL was responsible for data cleaning (by using sophisticated validation criteria), master data management, and loading transformed data into the data warehouse. It also dealt with the translation of structured and unstructured data into forms that could be used.

Assessing and contrasting available technologies

Kaprikorni described, evaluated, and contrasted four potential tech stacks as part of the IT consulting service. The Customer’s relationships with IT service providers and the prevalence of technology in the current IT architecture gave rise to the 4 main possibilities.

Results

Four fully detailed and evaluated integration possibilities and tech stacks were provided to the Customer for the speedy and efficient consolidation of the conglomerate’s data. All four action plans made it possible to transport secure data between systems while keeping it clean, accurate, and consistent.

The suggested integration option enabled for the seamless introduction of new components at little additional cost, supporting the company’s development and scalability.