The manufacturing industry is currently in the middle of a data-driven revolution, which requires the ability to manage large amounts of data. Bosch Sensortec, a leading global supplier of MEMS sensors for consumer electronics, exploits big data technologies to store massive amounts of data from the whole manufacturing process. Despite the employed cutting-edge technologies, the process of storing, retrieving, preprocessing and analyzing the manufacturing data can be challenging and time consuming. The solutions for the data analysis are often commercial and require extensive trainings and/or programming language knowledge. This thesis aims at increasing the overall efficiency of the manufacturing data analysis using two approaches: developing an internal tool for data analysis and investigating the relevance of the manufacturing data stored in the big data cluster.