What is the best way to bring data from huge volume source such as SAP to Data Platform (Data Lake)? Schedule base data transfer jobs are causing issues such as delayed data, partial data or zero byte transfer. How do we tackle this?

Such massive data transfers require careful planning and most importantly the right approach. Some steps to ensure that we do not encounter issues like delayed data, are:
- Understanding SAP, in particular, its structure. Gaining insights into its landscape is the starting point to have a successful data transfer.
- Define a robust data extraction strategy that aligns with your organization's requirements. Consider using SAP- specific connectors for data extraction.
- Execute a CDC machanism to extract only the modified or new records (since the last extraction). This reduces the volume of data trasnfer significantly.
- Choose appropriate tools and technologies that support parallel processing
- Errot handling mechanisms aid in capturing and managing the errors during the transfer process.
- Finally, data qualtiy checks should be included as a part of the data transfer process.

Tackling data flow challenges from mammoth sources like SAP to your Data Platform demands a strategic touch. In this age of exponential tech, it's about harmonizing innovation with practicality. I believe the following three strategies will ensure an effective approach.

1. Real-Time Integration: Seamlessly integrate data in real time. If you have a flair for data storytelling and business intelligence, it will lend itself to making swift, informed decisions.

2. Microservices Architecture: Think modular—just like the right approach to innovation. Break down complexity into manageable parts, orchestrating a symphony of data movement.

3. Continuous Vigilance: Much like maintaining a rhythm, employ continuous monitoring. This ensures transfers are smooth and timely, steering clear of disruptions.

As someone deeply immersed in IT, I hope you find these insights to be valuable. By adopting these strategies, you should be well-equipped to overcome data flow hurdles and keep insights shining.

By focusing on practical implementation and leveraging your data expertise, you can address issues of delayed, partial, or zero-byte transfers.  Keep pushing forward along your path to mastering seamless data flow and illuminating a clear way forward.