Dataconomy
  • News
  • AI
  • Big Data
  • Machine Learning
  • Trends
    • Blockchain
    • Cybersecurity
    • FinTech
    • Gaming
    • Internet of Things
    • Startups
    • Whitepapers
  • Industry
    • Energy & Environment
    • Finance
    • Healthcare
    • Industrial Goods & Services
    • Marketing & Sales
    • Retail & Consumer
    • Technology & IT
    • Transportation & Logistics
  • Events
  • About
    • About Us
    • Contact
    • Imprint
    • Legal & Privacy
    • Newsletter
    • Partner With Us
    • Writers wanted
Subscribe
No Result
View All Result
Dataconomy
  • News
  • AI
  • Big Data
  • Machine Learning
  • Trends
    • Blockchain
    • Cybersecurity
    • FinTech
    • Gaming
    • Internet of Things
    • Startups
    • Whitepapers
  • Industry
    • Energy & Environment
    • Finance
    • Healthcare
    • Industrial Goods & Services
    • Marketing & Sales
    • Retail & Consumer
    • Technology & IT
    • Transportation & Logistics
  • Events
  • About
    • About Us
    • Contact
    • Imprint
    • Legal & Privacy
    • Newsletter
    • Partner With Us
    • Writers wanted
Subscribe
No Result
View All Result
Dataconomy
No Result
View All Result

Data acquisition in 6 easy steps

by Evgeniya Panova
May 13, 2020
in Artificial Intelligence, BI & Analytics, Big Data, Data Science, Education
Home Topics Data Science Artificial Intelligence
Share on FacebookShare on TwitterShare on LinkedInShare on WhatsAppShare on e-mail

Data scientists are constantly challenged with improving their ML models. But when a new algorithm won’t improve your AUC there’s only one place to look: DATA. This guide walks you through six easy steps for data acquisition, a complete checklist for data provider due diligence, and data provider tests to uplift your model’s accuracy. 

Editor’s note: This free guide walks you through six easy steps for data acquisition, a complete checklist for data provider due diligence, and data provider tests to uplift your model’s accuracy.

When trying to improve a model’s accuracy and performance data improvement (generating, testing, and integrating new features from various internal and/or external sources) is time-consuming, difficult, but it could be a major discovery and move the needle much more.

The process of data acquisition can be broken down into six steps:

Hypothesizing – use your domain knowledge, creativity, and familiarity with the problem to try and scope the types of data that could be relevant to your model.

Generating a list of potential data providers – create a shortlist of sources (data partners, open data websites, commercial entities) that actually provide the type of data you hypothesized would be relevant.

Data provider due diligence – an absolute must. The list of parameters below will help you disqualify irrelevant data providers before you even get into the time-consuming and labor-intensive process of checking the actual data.

Data provider tests – set up a test with each provider that will allow you to measure the data in an objective way.

Calculate ROI – once you have a quantified number for the model’s improvement, ROI can be calculated very easily.

Integration and production – The last step in acquiring a new data source for your model is to actually integrate the data provider into your production pipeline.

Get the full guide for free here.

Data acquisition in 6 easy steps
Tags: data acquisitionMachine LearningWhitepaper

Related Posts

Whispering algorithms of smart surroundings

Whispering algorithms of smart surroundings

May 30, 2023
Infrastructure challenges and opportunities for AI startups

Infrastructure challenges and opportunities for AI startups

May 31, 2023
QR codes in AI and ML: Enhancing predictive analytics for business

QR codes in AI and ML: Enhancing predictive analytics for business

May 29, 2023
See how Photoshop AI Generative Fill feature changes designers’ lives

See how Photoshop AI Generative Fill feature changes designers’ lives

May 31, 2023
Claiming to be the most humane AI chatbot, Replika AI wants to be your empathetic pal

Claiming to be the most humane AI chatbot, Replika AI wants to be your empathetic pal

May 26, 2023
Meet Inflection AI Pi chatbot that earned acclaim from Bill Gates

Meet Inflection AI Pi chatbot that earned acclaim from Bill Gates

May 25, 2023

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

LATEST ARTICLES

Zoom Settlement: Is Epiqpay legit?

SolaaS: Your gateway to streamlined success

Whispering algorithms of smart surroundings

Infrastructure challenges and opportunities for AI startups

QR codes in AI and ML: Enhancing predictive analytics for business

See how Photoshop AI Generative Fill feature changes designers’ lives

Dataconomy

COPYRIGHT © DATACONOMY MEDIA GMBH, ALL RIGHTS RESERVED.

  • About
  • Imprint
  • Contact
  • Legal & Privacy
  • Partnership
  • Writers wanted

Follow Us

  • News
  • AI
  • Big Data
  • Machine Learning
  • Trends
    • Blockchain
    • Cybersecurity
    • FinTech
    • Gaming
    • Internet of Things
    • Startups
    • Whitepapers
  • Industry
    • Energy & Environment
    • Finance
    • Healthcare
    • Industrial Goods & Services
    • Marketing & Sales
    • Retail & Consumer
    • Technology & IT
    • Transportation & Logistics
  • Events
  • About
    • About Us
    • Contact
    • Imprint
    • Legal & Privacy
    • Newsletter
    • Partner With Us
    • Writers wanted
No Result
View All Result
Subscribe

This website uses cookies. By continuing to use this website you are giving consent to cookies being used. Visit our Privacy Policy.