Excel: Automated Ledger or Analytics IDE?

• URL: http://arxiv.org/abs/2409.12976v1
• Date: Tue, 3 Sep 2024 01:12:52 GMT
• Title: Excel: Automated Ledger or Analytics IDE?
• Authors: Andrew Kumiega,
• Abstract summary: Spreadsheets have undergone a gradual transformation, evolving from simple ledger automation tools to the current state of Excel. Excel includes a fully functional database, an OLAP Engine, multiple statistical programming languages, multiple third-party software libraries, dynamic charts, and real time data connectors. The importance of establishing a comprehensive risk framework for managing this distinctive development environment becomes clear.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Since the inception of VisiCalc over four decades ago, spreadsheets have undergone a gradual transformation, evolving from simple ledger automation tools to the current state of Excel, which can be described as an Integrated Development Environment (IDE) for analytics. The slow evolution of Excel from an automation tool for ledgers to an IDE for analytics explains why many people have not noticed that Excel includes a fully functional database, an OLAP Engine, multiple statistical programming languages, multiple third-party software libraries, dynamic charts, and real time data connectors. The simplicity of accessing these multiple tools is a low-code framework controlled from the Excel tool that is effectively an IDE. Once we acknowledge Excel's shift from a desk top application to an IDE for analytics, the importance of establishing a comprehensive risk framework for managing this distinctive development environment becomes clear. In this paper we will explain how the current risk framework for spreadsheets needs to be expanded to manage the growing risks of using Excel as an IDE for analytics.

Related papers

• Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows? [73.81908518992161]
  We introduce Spider2-V, the first multimodal agent benchmark focusing on professional data science and engineering. Spider2-V features real-world tasks in authentic computer environments and incorporating 20 enterprise-level professional applications. These tasks evaluate the ability of a multimodal agent to perform data-related tasks by writing code and managing the GUI in enterprise data software systems.
  arXiv  Detail & Related papers  (2024-07-15T17:54:37Z)
• SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation [34.8332394229927]
  SpreadsheetBench is designed to immerse current large language models (LLMs) in the actual workflow of spreadsheet users. Unlike existing benchmarks that rely on synthesized queries and simplified spreadsheet files, SpreadsheetBench is built from 912 real questions gathered from online Excel forums. Our comprehensive evaluation of various LLMs under both single-round and multi-round inference settings reveals a substantial gap between the state-of-the-art (SOTA) models and human performance.
  arXiv  Detail & Related papers  (2024-06-21T09:06:45Z)
• Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representations [36.2969566996675]
  We develop an Auto-Formula system that can accurately predict formulas that users want to author in a target spreadsheet cell. We use contrastive-learning techniques inspired by "similar-face recognition" from compute vision.
  arXiv  Detail & Related papers  (2024-04-19T03:28:18Z)
• AgentStudio: A Toolkit for Building General Virtual Agents [57.02375267926862]
  General virtual agents need to handle multimodal observations, master complex action spaces, and self-improve in dynamic, open-domain environments. AgentStudio provides a lightweight, interactive environment with highly generic observation and action spaces. It integrates tools for creating online benchmark tasks, annotating GUI elements, and labeling actions in videos. Based on our environment and tools, we curate an online task suite that benchmarks both GUI interactions and function calling with efficient auto-evaluation.
  arXiv  Detail & Related papers  (2024-03-26T17:54:15Z)
• OS-Copilot: Towards Generalist Computer Agents with Self-Improvement [48.29860831901484]
  We introduce OS-Copilot, a framework to build generalist agents capable of interfacing with comprehensive elements in an operating system (OS) We use OS-Copilot to create FRIDAY, a self-improving embodied agent for automating general computer tasks. On GAIA, a general AI assistants benchmark, FRIDAY outperforms previous methods by 35%, showcasing strong generalization to unseen applications via accumulated skills from previous tasks.
  arXiv  Detail & Related papers  (2024-02-12T07:29:22Z)
• EASYTOOL: Enhancing LLM-based Agents with Concise Tool Instruction [56.02100384015907]
  EasyTool is a framework transforming diverse and lengthy tool documentation into a unified and concise tool instruction. It can significantly reduce token consumption and improve the performance of tool utilization in real-world scenarios.
  arXiv  Detail & Related papers  (2024-01-11T15:45:11Z)
• InstructExcel: A Benchmark for Natural Language Instruction in Excel [72.018640505825]
  This work investigates whether Large Language Models can generate code that solves Excel specific tasks provided via natural language user instructions. Our benchmark includes over 10k samples covering 170+ Excel operations across 2,000 publicly available Excel spreadsheets. We observe that (1) using GPT-4 over GPT-3.5, (2) providing more in-context examples, and (3) dynamic prompting can help improve performance on this benchmark.
  arXiv  Detail & Related papers  (2023-10-23T02:00:55Z)
• Excel as a Turing-complete Functional Programming Environment [0.0]
  The Excel calculation engine was the subject of a major upgrade to accommodate Dynamic Arrays in 2018. This paper will show the ad-hoc end user practices of traditional spreadsheets can be replaced by radically different approaches. It is too early to guess the extent to which the new functionality will be adopted by the business and engineering communities.
  arXiv  Detail & Related papers  (2023-08-31T20:11:36Z)
• SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models [60.171444066848856]
  We propose a SheetCopilot agent that takes natural language task and control spreadsheet to fulfill the requirements. We curate a representative dataset containing 221 spreadsheet control tasks and establish a fully automated evaluation pipeline. Our SheetCopilot correctly completes 44.3% of tasks for a single generation, outperforming the strong code generation baseline by a wide margin.
  arXiv  Detail & Related papers  (2023-05-30T17:59:30Z)
• Will Dynamic Arrays finally change the way Models are built? [0.0]
  Spreadsheets offer a supremely successful and intuitive means of processing and exchanging numerical content. Their ad-hoc nature makes it hugely popular for use in diverse areas including business and engineering. Many would question whether it is suitable for serious analysis or modelling tasks.
  arXiv  Detail & Related papers  (2020-06-25T21:18:41Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.