HelloData

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HelloData - Full Product Demo (6-3-2024)
Power your multifamily rent surveys with real-time data on over 25M units nationwide, sourced entirely from property websites and public data sources.
Data Pipeline Design Patterns - #1. Data flow patterns
Data pipelines built (and added on to) without a solid foundation will suffer from poor efficiency, slow development speed, long times to triage production issues, and hard testability. What if your data pipelines are elegant and enable you to deliver features quickly? An easy-to-maintain and extendable data pipeline significantly increase developer morale, stakeholder trust, and the business bottom line! Using the correct design pattern will increase feature delivery speed and developer value (allowing devs to do more in less time), decrease toil during pipeline failures, and build trust with stakeholders. This post goes over the most commonly used data flow design patterns, what they do, when to use them, and, more importantly, when not to use them. By the end of this post, you will have an overview of the typical data flow patterns and be able to choose the right one for your use case.
Apartment Market Surveys & Product Feedback: Real-World Notes from a 2x PropTech Entrepreneur | HelloData.ai
Over the past month, we finished a few pilots where the primary feedback was that our product was “too detailed” for on-site management teams. Here's how we found out why, and fixed the problem in 7 days.
HelloData’s API Documentation 👋 | API Documentation | HelloData
Make real-time data your competitive advantage!
Nuitka the Python Compiler — Nuitka the Python Compiler
With the Python compiler Nuitka, you create protected binaries from your Python source code.
Catalog of Patterns of Distributed Systems
A catalog of patterns to better understand, communicate, and teach the design of distributed systems
Logging - Engineering Fundamentals Playbook
ISE Engineering Fundamentals Engineering Playbook
Logs vs Metrics vs Traces - Engineering Fundamentals Playbook
ISE Engineering Fundamentals Engineering Playbook
REST API Design Guidance - Engineering Fundamentals Playbook
ISE Engineering Fundamentals Engineering Playbook
Non-Functional Requirements Capture - Engineering Fundamentals Playbook
ISE Engineering Fundamentals Engineering Playbook
Data Transfer Object
An object that carries data between processes in order to
reduce the number of method calls.
How to Split Address in Excel: A Step-by-Step Guide
If you want to split address in Excel, this comprehensive guide is your ticket to mastering it as You’ll explore through different functions.
Advanced Business Law and the Legal Environment - Table of Contents
Function factories to improve Database read and write – Olivier Leroy
Advanced Tidyverse
Use piped workflows for efficient data cleaning and visualization.
Design Patterns in Functional Programming: A Closer Look
Explore the intricacies of design patterns in functional programming, gaining insights into their implementation and benefits.
Technical Guidelines for R
Best practices with R around select topics.
Summarizing and Querying Data from Excel Spreadsheets Using eparse and a Large Language Model
Editor's Note: This post was written by Chris Pappalardo, a Senior Director at Alvarez & Marsal, a leading global professional services firm. The standard processes for building with LLM work well for documents that contain mostly text, but do not work as well for documents that contain tabular data (like spreadsheets). We wrote about our latest thinking on Q&A over csvs on the blog a couple weeks ago, and we loved reading Chris's exploration of working with csvs and LangChain using agents, chai
Overview - Cellm
Use LLMs in Excel formulas
Generating Structured Output with LLMs (Part 1)
LLMs are great at generating text, but how do you get them to generate structured output?
Paper page - SpreadsheetLLM: Encoding Spreadsheets for Large Language Models
Join the discussion on this paper page
Agentic AI for Data Management and Warehousing
Explore how Agentic AI for data management enhances automation, governance, and decision-making by leveraging intelligent workflows, real-time insights
BillPetti/baseballr: A package written for R focused on baseball analysis. Currently in development.
A package written for R focused on baseball analysis. Currently in development. - BillPetti/baseballr
Sports and Fantasy Data from Fantasypros
The goal of the fantasypros R package is to provide easy and reproducable access to data
provided on the fantasypros website. The intital focus is on
NFL and fantasy football data, but other sports are planned to be added
Ploomber AI Editor
Create custom Streamlit and Shiny R apps effortlessly with AI assistance. Design, code, and deploy data apps in minutes.
Add Authentication and SSO to Your Shiny App
Learn how to implement strong authentication and SSO in Shiny apps with Descope. This guide integrates both OIDC and SAML with Posit Connect for seamless login.
Powerful Classes for HTTP Requests and Responses
In order to facilitate parsing of http requests and creating appropriate responses this package provides two classes to handle a lot of the housekeeping involved in working with http exchanges. The infrastructure builds upon the rook specification and is thus well suited to be combined with httpuv based web servers.
Send Error Reports to the Google Error Reporting Service API
Send error reports to the Google Error Reporting service and view errors and assign error status in the Google Error Reporting user interface.
tapLock/R/google.R at main · ixpantia/tapLock
Seamless SSO for R applications