Revolutionizing Data Processing: The Power of Zero Copy Data Access

Faster and more efficient data processing techniques are needed as the volume of data processed grows. “Zero copy data access” (ZCDA) may revolutionise how data is processed, and is already making waves in the customer data platform (CDP) space. ZCDA eliminates the need to copy data between memory locations, significantly improving the performance of applications, including marketing technology applications. It can also be used to improve the performance of in-memory databases, and is used in a variety of applications, such as Apache Arrow, an open-source software project that provides a cross-language development platform for in-memory data. Google and Salesforce recently partnered on a ZCDA initiative, allowing data to be stored in Google’s Big Query dataware house and accessed by Salesforce. In addition, the partnership gives zero copy access to Google’s Vertex AI to train AI models on Salesforce data. This eliminates the need to copy data into Vertex to train the models, and then copy it back into Salesforce. This has been implemented by CDPs such as Simon Data and ActionIQ, which also offer the option of allowing the CDP to ‘drill down’ into an organisations existing data lake, utilising the data without importing it into the CDP. Future applications of ZCDA include improving the performance of AI and machine learning, as well as making accessing data stored in blockchain applications more efficient.

As the volume of data processed grows, so do the demands for faster and more efficient data processing techniques. Zero copy data access (ZCDA) is one such technique that has the potential to revolutionise how data is processed. It eliminates the need to copy data between memory locations, enabling applications to access the memory location where the data is stored directly. This can significantly improve the performance of applications, including marketing technology applications. ZCDA is already being used in a variety of applications, such as Apache Arrow, an open-source software project that provides a cross-language development platform for in-memory data, and in-memory databases. It can also be used to improve the performance of AI and machine learning technologies. Google and Salesforce recently partnered on a ZCDA initiative, allowing data to be stored in Google’s Big Query dataware house and accessed by Salesforce, as well as using zero copy access to Google’s Vertex AI to train AI models on Salesforce data. This has been implemented by CDPs such as Simon Data and ActionIQ, which offer the option of allowing the CDP to ‘drill down’ into an organisations existing data lake utilising the data without importing it into the CDP.

Zero copy data access is an extremely powerful and efficient technique that has the potential to significantly improve the performance of data-intensive applications, particularly in the customer data platform space. It can reduce the amount of time it takes to move data between different parts of the system, as well as reducing the need to copy data between memory locations. It is already being used in a variety of applications and is being implemented by CDPs such as Simon Data and ActionIQ. In addition, Google and Salesforce have recently partnered on a ZCDA initiative, and its potential future applications include improving the performance of emerging technologies such as AI and machine learning, as well as making accessing data stored in blockchain applications more efficient.

Originally reported by Martech: https://martech.org/zero-copy-data-access-the-future-of-data-management/
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