INDIA
His journey from integrating legacy systems to pioneering advanced data solutions illustrates his versatility and commitment to driving innovation
In the dynamic field of data and analytics, adapting to change is key. Devidas Kanchetti, with over 14 years of experience, exemplifies this adaptability, having worked across multiple industries, including insurance, oil and gas, energy, and finance. His journey from integrating legacy systems to pioneering advanced data solutions illustrates his versatility and commitment to driving innovation. In this interview, Kanchetti reflects on his earlier career milestones, the challenges of transitioning to advanced technologies, and the strategies that have defined his success.
Q: Can you tell us about your experience with legacy system integration and how it shaped your approach to data analytics?
A: One of my most formative experiences was at Larsen & Toubro InfoTech, where I worked on integrating data from legacy systems with SAP ERP systems for Chevron Oil. This project was challenging due to the complexities of aligning old data structures with modern data warehousing needs. We developed a comprehensive implementation roadmap that included scope estimation and gap analysis between the current architecture and the future analytics requirements. This experience taught me the importance of a strategic approach to data integration, laying the groundwork for my later work in more advanced environments.
Q: How did you approach the ETL tool migration at McKesson, and what were the key challenges?
A: At McKesson, I was involved in migrating ETL processes from DataStage to SAP BODS. This was a critical project because it involved understanding the intricacies of the existing ETL feeds and ensuring a seamless transition to the new tool. The key challenges included maintaining data integrity and performance during the migration. We conducted thorough testing and performance tuning, which not only ensured a smooth migration but also improved the efficiency of the ETL processes. This project highlighted the importance of meticulous planning and testing in large-scale data migrations.
Q: Could you elaborate on your role in SAP HANA modeling and how it enhanced business operations?
A: During my tenure at McKesson, I was heavily involved in SAP HANA modeling, where I created various models such as Attribute Views, Analytic Views, and Calculation Views. These models played a crucial role in supporting real-time analytics and reporting, which were essential for our business operations. By integrating SAP HANA with other data sources using SAP BODS, we enabled the company to access rapid insights from large datasets, which significantly improved decision-making processes. This work underscored the value of robust data models in driving business efficiency.
Q: What were some of the key innovations you introduced at Larsen & Toubro InfoTech in your earlier career?
A: At Larsen & Toubro InfoTech, I introduced a modular ETL framework using SAP Data Services (BODS) that standardized our ETL processes across various projects. This framework improved not only the efficiency but also the maintainability of our data pipelines. We also implemented pushdown optimization techniques to handle large datasets more effectively and developed automated testing scripts that streamlined the testing phase, ensuring data quality and consistency. These innovations set a new standard for our data integration efforts and were instrumental in several successful projects.
Q: How did you tackle performance optimization and data quality in your earlier roles?
A: Performance optimization and data quality have always been at the forefront of my work. At Steria, I worked on optimizing complex BODS jobs through performance tuning and implementing pushdown optimization techniques. We also set up a robust data quality framework that included data profiling, validation, and automated error detection. These measures were crucial in ensuring that our data solutions met the highest standards of performance and reliability, which is essential when dealing with large and complex datasets.
Q: What was your approach to handling ETL challenges in high-pressure environments like the oil and gas industry?
A: In the oil and gas industry, especially during my time at Chevron Oil, data integration challenges were often compounded by the need for high accuracy and real-time processing. My approach was to first conduct a thorough assessment of the current architecture and business KPIs. From there, I developed a detailed implementation roadmap, focusing on scalable solutions that could adapt to the evolving needs of the business. This involved close collaboration with stakeholders to ensure that the data architecture aligned with business goals, which was critical in such a high-pressure environment.
Q: Can you share a memorable success from your early career that significantly impacted the business?
A: A memorable success from my early career was my work on the RNA Pharma Gx HANA Implementation at McKesson. This project involved using SAP BODS for data provisioning and integrating various data sources into SAP HANA. The success of this project was evident in the improved data accessibility and analytics capabilities it provided, which directly contributed to better business outcomes. The ability to deliver such impactful solutions early in my career reinforced the value of strong technical skills combined with strategic thinking.
Q: What advice would you give to young professionals entering the field of data analytics?
A: For young professionals entering the field, I would emphasize the importance of mastering the fundamentals of data management and analytics. Start by gaining a strong understanding of ETL processes, data modeling, and cloud technologies. Stay curious and continuously learn new tools and techniques as the field evolves. It's also crucial to develop strong problem-solving skills and the ability to communicate complex data insights to non-technical stakeholders. Lastly, always focus on data quality and consistency, as these are the pillars of any successful analytics project.
Through his early career experiences, Devidas Kanchetti has demonstrated an unwavering commitment to advancing data analytics across diverse industries. His work on integrating legacy systems, optimizing ETL processes, and pioneering SAP HANA implementations reflects his strategic vision and technical expertise. As Devidas continues to push the boundaries of data analytics, his journey offers valuable insights and inspiration for professionals looking to make their mark in this ever-evolving field.
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