Listen free for 30 days

Listen with offer

Preview

  • Data Lake Architecture

  • Designing the Data Lake and Avoiding the Garbage Dump
  • By: Bill Inmon
  • Narrated by: Mark Shumka
  • Length: 2 hrs and 33 mins
  • 3.5 out of 5 stars (4 ratings)

£0.00 for first 30 days

Try for £0.00
Pick 1 audiobook a month from our unmatched collection - including bestsellers and new releases.
Listen all you want to thousands of included audiobooks, Originals, celeb exclusives, and podcasts.
Access exclusive sales and deals.
£7.99/month after 30 days. Renews automatically. See here for eligibility.

Data Lake Architecture

By: Bill Inmon
Narrated by: Mark Shumka
Try for £0.00

£7.99/month after 30 days. Renews automatically. See here for eligibility.

Buy Now for £6.99

Buy Now for £6.99

Pay using card ending in
Switch payment method
By completing your purchase, you agree to Audible's Conditions of Use and authorise Audible to charge your designated card or any other card on file. Please see our Privacy Notice, Cookies Notice and Interest-based Ads Notice.

Summary

Organizations invest incredible amounts of time and money in obtaining and then storing big data in stores called data lakes. But how many of these organizations can actually get the data back out in a useable form? Very few can turn a data lake into an information gold mine. Most wind up with garbage dumps.

Data Lake Architecture will explain how to build a useful data lake where data scientists and data analysts can solve business challenges and identify new business opportunities. Learn how to structure data lakes as well as analog, application, and text-based data ponds to provide maximum business value. Understand the role of the raw data pond and when to use an archival data pond. Leverage the four key ingredients for data lake success: metadata, integration mapping, context, and metaprocess.

Bill Inmon opened our eyes to the architecture and benefits of a data warehouse, and now he takes us to the next level of data lake architecture.

©2016 Bill Inmon (P)2016 Technics Publications, LLC
Data Science Machine Theory & Artificial Intelligence Software
Show More Show Less
activate_Holiday_promo_in_buybox_DT_T2

Listeners also enjoyed...

 Data Analytics for Beginners: Your Ultimate Guide to Learn and Master Data Analysis cover art
Designing Data-Intensive Applications cover art
Data Mesh cover art
Software Wasteland: How the Application-Centric Mindset Is Hobbling Our Enterprises cover art
Data and Reality cover art
Blockchain for Beginners: Understand the Blockchain Basics and the Foundation of Bitcoin and Cryptocurrencies cover art
Markov Models: Supervised and Unsupervised Machine Learning cover art
Machine Learning for Beginners cover art
Your Starter Guide for Data Management, Model Training, Neural Networks, Machine Learning Algorithms cover art
SQL cover art
Data Mining: The Data Mining Guide for Beginners cover art
Data Science for Business cover art
Machine Learning cover art
Machine Learning and Artificial Intelligence, Two-Book Bundle cover art
Reactive Design Patterns cover art
Unit Testing Principles, Practices, and Patterns cover art

What listeners say about Data Lake Architecture

Average customer ratings
Overall
  • 3.5 out of 5 stars
  • 5 Stars
    1
  • 4 Stars
    1
  • 3 Stars
    1
  • 2 Stars
    1
  • 1 Stars
    0
Performance
  • 2.5 out of 5 stars
  • 5 Stars
    0
  • 4 Stars
    0
  • 3 Stars
    1
  • 2 Stars
    1
  • 1 Stars
    0
Story
  • 2.5 out of 5 stars
  • 5 Stars
    0
  • 4 Stars
    0
  • 3 Stars
    1
  • 2 Stars
    1
  • 1 Stars
    0

Reviews - Please select the tabs below to change the source of reviews.

Audible.co.uk reviews

Amazon reviews
Sort by:
Filter by:
  • Overall
    2 out of 5 stars
  • Performance
    3 out of 5 stars
  • Story
    2 out of 5 stars
Profile Image for Stef

General generalities not worth the listen

There's about an article worth of information here. It's not bad as such, just too general, and nothing you couldn't find out with a very short read of some basic summary articles. I was hoping for more detail, more insights and more actionable content. Disappointing.

Report this

Something went wrong. Please try again in a few minutes.

You voted on this review!

You reported this review!