Manufacturers need to leverage a data mesh for innovation and competitiveness
By Vinay Samuel, Founder and CEO, Zetaris The success of any manufacturing business depends on closely managing every element of the process. That starts with accessing raw materials, monitoring the actual process of manufacturing, the dispatch of finished goods and ensuring they are shipped to the customer. The key to understanding all those steps is data. That data is often spread across multiple systems and managing a manufacturing supply chain requires access to real-time information. Traditional approaches manufacturers leveraged to perform data analytics focused on looking back at what happened in the past. The old extract, transform and load (ELT) process relied on being able to extract data from various systems in order to load them into a centralised data warehouse or data lake for analysis and insights. This approach was piecemeal as the ETL process was limited to data sources the manufacturer could access easily. This put external systems and data sources, such as those operated by logistics companies and raw material suppliers, out of reach. The cost, time and complexity required to connect to those external systems, extract the required data in a timely way and then integrate it into the data warehouse was prohibitive and when it was done, already vastly out-of-date. As a result, manufacturers only had a limited view of what was happening across their entire manufacturing process and supply chain and little ability to detect and address changing customer preferences in real-time. A data fabric takes a very different approach. Rather than relying on the ETL process, data fabric technology leverages the data mesh principles to enable manufacturers to access information from internal and external locations across disparate sources without the need to extract it. Data from multiple systems can easily be integrated into a metadata-driven virtual data warehouse that can be accessed by […]