The chapter delves into the theoretical and practical aspects of signal transformation from analog to digital and vice versa, employing techniques such as Laplace transform, Fourier transform, and Z-transform. It comprehensively explains the process of sampling continuous signals to form discrete ones, emphasizing the role of the Z-transform in spectral analysis and the conversion of analog signal spectra into discrete spectra, particularly addressing issues like aliasing and spectrum overlap. The chapter introduces the Discrete Fourier Transform (DFT) and its inverse for computing the spectral density of discrete signals, showcasing practical applications using mathematical derivations and examples. Additionally, the study explores analog-to-digital conversion (ADC), detailing the quantization process, quantization noise, and error impacts on signal quality. Different ADC types including dual-slope, sigma-delta, and successive-approximation ADCs are discussed, alongside parameters influencing their performance. The chapter further outlines the design and accuracy considerations for various digital-to-analog converters (DACs), discussing error characteristics, implementation challenges, and solutions for precision and stability. Finally, the chapter emphasizes the importance of digital interfaces for ADC connectivity with processors, the development of single-chip data acquisition systems, and the role of structural diagrams and mathematical formulas in elucidating key concepts. This comprehensive analysis offers valuable insights for researchers and engineers focused on digital signal processing and the design of efficient measurement systems.