CIO Business Intelligence

APRIL 10, 2024

Higher-level languages, automation, low-code and no-code development platforms, and better programming environments have been gradually reducing the need for IT staff to perform low-level, routine tasks for years so they can take on more innovative challenges. That might continue to work for a few rarified geniuses, he adds.

Consulting 135

Consulting Technology Management Software 135

O'Reilly on Data

NOVEMBER 28, 2023

And of course, companies that don’t use AI don’t need an AI use policy. The higher percentage of users that are experimenting may reflect OpenAI’s addition of Advanced Data Analysis (formerly Code Interpreter) to ChatGPT’s repertoire of beta features. It’s also well suited to writing a quick email.

Enterprise 271

Enterprise Modeling Testing Reporting 271

DataKitchen

MAY 10, 2021

Remember your first data science courses? As such, applying manufacturing methods, such as lean manufacturing, to data analytics produces tremendous quality and efficiency improvements. Testing proves that analytics code is ready to be promoted to production. Writing Tests in Your Tool of Choice.

Testing 214

Testing Manufacturing Data Quality Statistics 214

Domino Data Lab

JULY 22, 2019

By looking through this lens, industry is able to ingest and iterate on some current “hot buttons” and infer potential implications on decisions, outcomes, and insights that may surface during the course of their work. If you have a smartphone, use the QR code, you can load it up on your phone. Key highlights from the session include.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

FEBRUARY 12, 2020

Dean Wampler provides a distilled overview of Ray, an open source system for scaling Python systems from single machines to large clusters. If you’re wondering if Ray should be part of your technical strategy for Python-based applications, especially ML and AI, this post is for you. Ray: Scaling Python Applications.

Experimentation 137

Experimentation Modeling Data Science Management 137

Cloudera

AUGUST 4, 2022

Once data is in Z-order it is possible to efficiently search against more columns. But the version of page index filtering that we described could only search efficiently against a limited number of columns. This ordering enables us to efficiently search against more columns. Which are those columns? More on that later.

IoT 102

IoT Measurement Statistics Cost-Benefit 102

Occam's Razor

FEBRUARY 11, 2008

9: "Micro Efficiencies" # 8: A company that truly cares. # 9: "Micro Efficiencies" Google has all these "micro efficiencies" that are very clever and well thought out. Micro efficiencies that result in significant macro efficiency. # I of course insisted he keep it.

Consulting 139

Consulting Visualization Recreation/Entertainment IT 139

Alation

JANUARY 17, 2023

A modern data stack is typically more scalable, flexible, and efficient than a legacy data stack. Enhanced Efficiency. A modern data stack can also be more efficient than a legacy data stack. Smaller companies that want to improve their scalability, flexibility, and efficiency are also embracing the modern data stack.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

Domino Data Lab

AUGUST 22, 2019

In the present chapter [excerpt], we cover code that will enable you to create your own word vectors as well as to provide them as an input into a deep learning model. Most of these dependencies are from nltk (the Natural Language Toolkit) and gensim (another natural language library for Python). matplotlib inline. Tokenization.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Andrew White

JANUARY 11, 2021

You can of course listen and watch the webinar from this link. Does this promote efficiency? GI-GO of course we all know. Coding skills – SQL, Python or application familiarity – ETL & visualization? We cannot of course forget metadata management tools, of which there are many different.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Edwin Chen

MAY 29, 2017

I could have caught a hundred Pidgeys in the time it took me to write this post, so here's a cartoon. Learning to Code. For example: Imagine a code autocompleter smart enough to allow you to program on your phone. While the code certainly isn't perfect, it's better than a lot of data scientists I know. Neural Networks.

Modeling 94

Modeling IT Deep Learning Testing 94