Arvato is a leading service provider in Turkey, offering call center and tech solutions for top global brands and Turkish institutions. With over 4,000 agents across cities and remote FlexAgents, they serve in 12 languages, including Turkish, German, and Russian. Beyond customer service, Arvato specializes in areas like Robotic Process Automation and Customer Experience, emphasizing innovations in artificial intelligence and data analysis. Their clientele encompasses major e-commerce platforms, telecom brands, and Turkey’s prominent banks and insurers.
The Challenge
Arvato Turkey confronted a multifaceted set of challenges in their data management processes. Firstly, the sheer diversity of their data sources, which spanned daily sales reports in Excel, inventory records in CSV, and customer information scattered across various databases, introduced complexities in integration and consistency. This diversity, when combined with the high volume of data processed daily, made manual data management not only cumbersome but also highly susceptible to errors.
The importance of data quality was paramount for Arvato Turkey. Accurate and consistent data was the backbone of their decision-making process. This necessitated a rigorous system where data underwent thorough validation, cleansing, and enrichment during the ETL stages.
Lastly, looking ahead, Arvato Turkey recognized the evolving nature of their data needs. They anticipated the addition of new data sources and a surge in data volumes as the business grew. This foresight brought forth the challenge of scalability, emphasizing the need for a robust system capable of accommodating future growth without requiring extensive modifications or overhauls.
What did
Deka Technology do
Deka Technology and Arvato Turkey jointly embarked on an ambitious project to address data integration challenges with a robust ETL solution based on the Knime ETL tool. Leveraging Knime’s extensive connectors, Deka Technology efficiently extracted data from a myriad of sources, including Excel, CSV, and various databases. Using Knime’s visual workflow interface, they executed complex data transformations, encompassing data cleansing, data type conversion, and merging data from different origins.
Furthermore, Deka Technology placed a significant emphasis on data quality. They implemented specific data validation rules and utilized both built-in nodes and custom scripting functions of Knime to enrich the data with external sources, ensuring its accuracy. Error-handling mechanisms were introduced to ensure any discrepancies or issues during the ETL process were promptly identified and addressed. After transformation, the data was loaded into an SQL Server database, with a particular focus on optimizing performance. Finally, Knime’s automation features ensured that the ETL processes were conducted regularly and efficiently, enabling Arvato Turkey to always have up-to-date data for their business decisions.
The Results
- Standardized and clean data
- Improved data accuracy
- Scalable data integration capabilities
- Efficient and reduced manual data handling
- Enhanced decision-making for Arvato Turkey
