Nuclear magnetic resonance spectroscopy, or NMR, is a widely used analytical technique that gives unique insight into molecular structure and dynamics. Its strengths are in finding specific information regarding chemical connectivity by probing the local environment of nuclear spins. This is balanced by a relatively weak signal that often takes either large amounts of sample or more scans (and therefore more time) to acquire useful spectra. Due to the cost constraints of instrument time, many methods have been developed around every aspect of NMR to gain the most useful information in the shortest amount of time possible. Here, we focus on efforts in the realm of data processing and pulse sequence design to address several separate problems. The four separate projects, which comprise the remaining chapters, each address a problem of gaining useful data in a faster or more efficient way, whether it be through experimental design or through new ways of processing the data. The first chapter will give a background of basic one- and two-dimensional Fourier transform (FT) NMR as well as some general information useful in later chapters. The second chapter deals with an alternative data acquisition and processing technique referred to as projection reconstruction (PR) NMR. Directly following is a chapter on the hybrid filter diagonalization method (HFDM) and how to use the information from both the FT and FDM in the same spectrum. The fourth chapter focuses on developing and testing a new pulse sequence for the elucidation of oligosaccharide structure. This entails the derivatization with ¹³C labeled acetyl groups and making use of selective heteronuclear Hartmann-Hahn (HEHAHA) transfer experiments. The final chapter discusses the use and development of a blind source separation (BSS) method to isolate independently varying NMR signals that are mixed. Applications to overlapped multiplets and chemical mixtures are described.