Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. That depends on who you serve, where you operate, and what types of data you’re trying to manage.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. That depends on who you serve, where you operate, and what types of data you’re trying to manage.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

O'Reilly on Data

JULY 25, 2023

If you’re reading this, chances are you’ve played around with using AI tools like ChatGPT or GitHub Copilot to write code for you. Or even if you haven’t yet, then you’ve at least heard about these tools in your newsfeed over the past year. or “ha look how incompetent it is … it couldn’t even get my simple question right!”

Consulting 246

Consulting Interactive Software IT 246

O'Reilly on Data

NOVEMBER 28, 2023

Generative AI has been the biggest technology story of 2023. And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. Many AI adopters are still in the early stages. What’s the reality?

Enterprise 269

Enterprise Modeling Testing Reporting 269

Domino Data Lab

JULY 22, 2019

why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”. Paco Nathan: Thank you, Jon [Rooney]. You’ve seen Jon up here, too, doing fantastic MC-ing.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

O'Reilly on Data

OCTOBER 11, 2022

There seems to be broad agreement that hyperautomation is the combination of Robotic Process Automation with AI. Natural language generation and natural language understanding are frequently mentioned, too, but they’re subsumed under AI. Using AI to discover tasks that can be automated also comes up frequently.

Data Integration 289

Data Integration Insurance Dashboards Modeling 289

CIO Business Intelligence

DECEMBER 13, 2023

Most recently, in June, it spent $650 million to buy Casetext, a 104-employee company that offers an AI assistant for legal professionals powered by OpenAI’s GPT-4, the same large language model (LLM) behind ChatGPT. But that’s not the only big bet the company is making on generative AI. How do you apply strategic problem-solving?”

Enterprise 135

Enterprise Consulting Risk Marketing 135

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch presented “ Product Management for AI ” at Rev. Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. How many people are designers?

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

APRIL 15, 2022

In 2017, The Economist declared that data, rather than oil, had become the world’s most valuable resource. Understanding your data and what it’s telling you is important, but it’s also important to understand your tools, know your data, and keep your organization’s values firmly in mind. The refrain has been repeated ever since.

Analytics 145

Analytics Machine Learning Insurance Testing 145

datapine

DECEMBER 11, 2019

With a new year on the horizon, in this article, we’ll explore 10 essential SaaS trends that will stand out in 2020. SaaS is taking over the cloud computing market. Gartner predicts that the service-based cloud application industry will be worth $143.7 billion by 2022—a level of growth that will shape SaaS trends in 2020.

Software 314

Software Cost-Benefit Data Processing Data-driven 314

Domino Data Lab

FEBRUARY 4, 2019

This month, let’s explore two themes in detail: take an in-depth look at Rev 2 and exploring how curiosity plays a vital, and perhaps non-intuitive, role in data science work. We’ll unpack curiosity as a core attribute of effective data science, look at how that informs process for data science (in contrast to Agile, etc.),

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Insight

MARCH 25, 2020

Build a scalable, online recommender with Keras, Docker, GCP, and GKE TL;DR Online retailers such as Wayfair and Amazon offer endless arrays of products, chosen by smart AI product recommender systems. Unfortunately, it only took a few Google searches to feel overwhelmed, with more furniture choices than I cared to look through.

Deep Learning 53

Deep Learning Metrics Data Processing Interactive 53

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. Our goal is to demonstrate the foundational role of the data catalog, and how it influences the higher corresponding layers that form an effective data fabric.

Metadata 52

Metadata IT Metrics Data-driven 52

Smart Data Collective

JUNE 30, 2023

[Alt Text: Eric Blue, CEO of Nevly, provides access to resources so that others can avoid getting trapped in debt and other common mistakes early on in their financial journey. This is a major topic of discussion, since the value of the AI in fintech market is estimated to be worth $39 billion.

Insurance 81

Insurance Finance Cost-Benefit Strategy 81

O'Reilly on Data

JANUARY 25, 2021

Those reports are valuable, but their value isn’t in knowing what languages are popular in any given month. Sometimes they’re only apparent if you look carefully at the data; sometimes it’s just a matter of keeping your ear to the ground. In our industry, cloud computing might be a good example. Methodology.

Machine Learning 363

Machine Learning Software Testing Technology 363