Developing a Modular Visual Data Manipulation Framework for Data Exploration in the Consumer Packaged Goods Industry

The rapidly increasing reliance on data analytics to drive strategic decision-making in today’s digital economy means that efficient and user-friendly data analysis tools are becoming increasingly important. Even as understanding and manipulating data becomes more critical, the technical complexity...

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Bibliographic Details
Main Author: Huang, Allen
Other Authors: Eng, Tony
Format: Thesis
Published: Massachusetts Institute of Technology 2023
Online Access:https://hdl.handle.net/1721.1/152637
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author Huang, Allen
author2 Eng, Tony
author_facet Eng, Tony
Huang, Allen
author_sort Huang, Allen
collection MIT
description The rapidly increasing reliance on data analytics to drive strategic decision-making in today’s digital economy means that efficient and user-friendly data analysis tools are becoming increasingly important. Even as understanding and manipulating data becomes more critical, the technical complexity of traditional query languages like SQL often poses a substantial barrier to non-technical users. In this thesis, we present a fully visual analytics framework that can be arbitrarily integrated with relational data stored in an analytics platform. We describe the design and implementation of a frontend client by which nontechnical users can construct rich queries involving relational operations such as aggregations and filters on promotional data and view their outputs in tabular or graphical form. We also describe a protocol for uniquely and unambiguously describing these queries and the design and implementation of an engine by which these queries are efficiently executed.
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spelling mit-1721.1/1526372023-11-03T03:01:56Z Developing a Modular Visual Data Manipulation Framework for Data Exploration in the Consumer Packaged Goods Industry Huang, Allen Eng, Tony Wey, Scott Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science The rapidly increasing reliance on data analytics to drive strategic decision-making in today’s digital economy means that efficient and user-friendly data analysis tools are becoming increasingly important. Even as understanding and manipulating data becomes more critical, the technical complexity of traditional query languages like SQL often poses a substantial barrier to non-technical users. In this thesis, we present a fully visual analytics framework that can be arbitrarily integrated with relational data stored in an analytics platform. We describe the design and implementation of a frontend client by which nontechnical users can construct rich queries involving relational operations such as aggregations and filters on promotional data and view their outputs in tabular or graphical form. We also describe a protocol for uniquely and unambiguously describing these queries and the design and implementation of an engine by which these queries are efficiently executed. M.Eng. 2023-11-02T20:04:43Z 2023-11-02T20:04:43Z 2023-09 2023-10-03T18:21:29.094Z Thesis https://hdl.handle.net/1721.1/152637 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology
spellingShingle Huang, Allen
Developing a Modular Visual Data Manipulation Framework for Data Exploration in the Consumer Packaged Goods Industry
title Developing a Modular Visual Data Manipulation Framework for Data Exploration in the Consumer Packaged Goods Industry
title_full Developing a Modular Visual Data Manipulation Framework for Data Exploration in the Consumer Packaged Goods Industry
title_fullStr Developing a Modular Visual Data Manipulation Framework for Data Exploration in the Consumer Packaged Goods Industry
title_full_unstemmed Developing a Modular Visual Data Manipulation Framework for Data Exploration in the Consumer Packaged Goods Industry
title_short Developing a Modular Visual Data Manipulation Framework for Data Exploration in the Consumer Packaged Goods Industry
title_sort developing a modular visual data manipulation framework for data exploration in the consumer packaged goods industry
url https://hdl.handle.net/1721.1/152637
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