________________________________________________________________________________ Digital transformation skills by automatically providing users with relevant insights . Augmented analytics utilizes Natural Language Query ( NLQ ) technology , which provides self-service business intelligence based on natural language search . Generating custom reports and personalized dashboards becomes as easy as searching with voice commands . This provides assembly line engineers and technicians with access to critical insights without specialized training .
Practical insights
Of course , manufacturing companies need ways to make their data insights usable . One particularly fruitful area here is applicable in predictive fault prevention on the manufacturing line . Sensors that have been placed along the production line can monitor various important metrics , for example , production speed . The sensors can combine data from multiple sources to monitor the health and performance of each machine along the manufacturing process .
Measuring temperature , voltage , power consumption , and production speed can help manufacturers track and pinpoint specific machine faults . Once the measurements and data patterns exceed certain thresholds , maintenance teams can be alerted to check machines for potential faults . This enables them to repair or replace parts that might cause unexpected downtime on the entire production line . Manufacturing organizations are increasingly looking for better ways to manage and analyze data in diverse structural formats . Traditionally , manufacturing companies would use schema-based data systems . These systems gather data that ’ s in multiple formats but the data then requires preprocessing before it is available for analytics . This requirement prevents organizations from scaling their data platforms and integrating more data sources .
Data lakes
To address data incompatibility , many manufacturing organizations are adopting data lake technologies to integrate information from multiple sources . A data lake is a central repository that allows companies to store both structured and unstructured data , and to do so at any scale . Data lakes significantly reduce the time needed to process and analyze data , allowing organizations to react more quickly to changes in the market and in their operations . Data lakes also enable manufacturing companies to scale their data platforms more effectively .
Implementing data lake technologies also allows manufacturing companies to better leverage machine learning and AI capabilities . This can lead to improvements in predictive maintenance , quality control , and demand forecasting , among others . As a result , manufacturing organizations can optimize their operations , minimize downtime , and ultimately become more competitive .
Manufacturing organizations increasingly seek better ways to manage and analyze diverse data formats to perform and benefit from advanced analytics . Data lake technologies in particular will likely play a significant role in enabling these organizations to remain agile and competitive in an ever-changing global market . ■
Bal Heroor www . mactores . com
Bal Heroor is CEO and Principal at Mactores and has led over 150 business transformations driven by analytics and cutting-edge technology . His team at Mactores are researching and building AI , AR / VR , and Quantum computing solutions for business to gain a competitive advantage .
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