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\section{SED Analysis: an overview}  \label{sec:overview}  Fitting spectral energy distributions allows astronomers to estimate fundamental physical properties like stellar mass, star formation rates, dust content and overall environments of astronomical objects (e.g. \citet{1998AJ....115.1329S}, \citet{2001ApJS..137..139S}, \citet{2007ApJS..169..328R}, and many others). With deeper wide-field surveys and increasing numbers of datasets over the years, astronomers have been able to utilize multi-wavelength SEDs more frequently for their research. As such, many robust SED analysis codes have been created to help astronomers model, fit, and derive physical quantities from SEDs \citep{2011Ap&SS.331....1W,2013ARA&A..51..393C}. These widely-used codes implement a diverse set of methods, for instance: inversion (\texttt{PAHFIT} \citep{2007ApJ...656..770S}, \texttt{STARLIGHT} \cite{2004MNRAS.355..273C}), principal component analysis \citep{2009MNRAS.394.1496B}, \mathrm{\Chi}^{2}-minimization $\mathrm{\Chi}^{2}$-minimization  codes (\texttt{Le Phare} \citep{1999MNRAS.310..540A}, \texttt{hyperz} \citep{2000A&A...363..476B}), and Bayesian inference (\texttt{GalMC} \citep{2011ApJ...737...47A}; \texttt{VOSA} \citep{2008A&A...492..277B}; \texttt{BPZ} \citep{2000ApJ...536..571B}). Most distributed fitting packages are tailored for specific data sets or spectral ranges (e.g. PAHFIT, STARLIGHT), providing robust fitting methods and results. They require the data to be in a specific format with specific units in order for the tool to work properly. When fitting a broadband SED that spans over decades in the spectrum, the astronomer will typically gather data from different public archives and colleagues to add to their own dataset. More often than not, the datasets are presented in different file formats and units. The user must provide their own methods to extract the necessary data from each file, convert the units, and output a file in the single format supported by the tool.