CIO Business Intelligence

DECEMBER 10, 2024

For example, our employees can use this platform to: Chat with AI models Generate texts Create images Train their own AI agents with specific skills To fully exploit the potential of AI, InnoGames also relies on an open and experimental approach. billion data records in real-time every day, based on player interactions with its games.

Data-driven 98

Data-driven Metadata Interactive KPI 98

Smart Data Collective

JULY 9, 2023

This article is going to provide some great insights on developing strategies for unlocking additional value from an online business, which can do a lot to boost revenue and catapult the enterprise to new heights. Experimentation is the key to finding the highest-yielding version of your website elements.

Optimization 97

Optimization Data Analytics Analytics Data-driven 97

CIO Business Intelligence

SEPTEMBER 12, 2024

I read an article once titled, “AI Won’t Replace Humans – But Humans with AI Will Replace Humans without AI.” A culture of experimentation, learning from failures, and ample resources is essential along with a culture that fosters the space and ability to fail fast, learn, and move on.”

Management 115

Management IT Experimentation Technology 115

datapine

JANUARY 31, 2022

They’re about having the mindset of an experimenter and being willing to let data guide a company’s decision-making process. Renowned author Bernard Marr wrote an insightful article about Shell’s journey to become a fully data-driven company. What Are The Benefits of Business Intelligence? Let’s look at our first use case.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Smart Data Collective

JUNE 21, 2023

Last summer, we wrote an article about the ways that artificial intelligence is changing video editing software. This frees up time for experimentation and achieving superior results. The software not only transforms a simple photo booth into a highly interactive platform but also significantly enriches the overall guest experience.

Software 104

Software Technology Experimentation Data-driven 104

FineReport

DECEMBER 19, 2019

In addition, Jupyter Notebook is also an excellent interactive tool for data analysis and provides a convenient experimental platform for beginners. If you want a more comprehensive getting started guide for data analysis, you can refer to the following articles: Data Analysis Practice Guide: How to Begin? From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Data mining Reporting 98

Data Science and Beyond

JULY 22, 2018

This article is a short summary of my understanding of the definition of data science in 2018. Numerous articles have been published on the meaning of data science in the past six years. In a recent article , Hernán et al. No one is born an expert – expertise is gained by learning from and interacting with the world.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. Yet, this challenge is not insurmountable. for what is and isn’t possible) to address these challenges.

Management 110

Management Machine Learning Experimentation Metrics 110

The Unofficial Google Data Science Blog

JANUARY 16, 2018

by SANGHO YOON In this article, we discuss an approach to the design of experiments in a network. Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. This simulation is based on the actual user network of GCP.

Testing 59

Testing Experimentation Measurement Modeling 59

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. ” BTW, that Knuth article from 1983 was probably the first time that I ever saw the word “Web” used as a computer-related meaning. Introduction. BTW, videos for Rev2 are up: [link]. Software writes Software?

Metadata 105

Metadata Data Science Machine Learning Data-driven 105

Domino Data Lab

AUGUST 5, 2019

The article focuses on 1) proposed frameworks for defining and designing for ethics and for understanding the forces that encourage industry to operationalize ethics, as well as 2) proposed ethical principles for data scientists to consider when developing data-empowered products. data munging, building models, etc.).

Data Science 93

Data Science Data-driven Modeling Machine Learning 93

IBM Big Data Hub

MARCH 4, 2024

It’s also crucial to modernize existing applications that interact with AI. This culture encourages experimentation and expertise growth. Innovate and modernize applications Innovating with new AI-based applications to deliver outstanding experiences is essential.

Enterprise 96

Enterprise ROI Risk Strategy 96

Perceptual Edge

AUGUST 26, 2019

New conceptions of data are now encoded into the actual application experiences that improve the user’s interaction with their data. (p. These novel interactions, which are possible only in spatial computing, unlock new insights because of being able to view and manipulate data in 3D pace unlike previous design paradigms. (p.

Visualization 52

Visualization Cost-Benefit Interactive Experimentation 52

IBM Big Data Hub

APRIL 18, 2024

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. It analyzes historical data and news articles, confirming a possible market correction.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

Sisense

JUNE 30, 2019

A data strategy deals with all aspects of your data: where it comes from, where it’s stored, how you interact with it, who gets to see what, and who is ultimately in charge of it. Encouraging a culture of experimentation is key to finding new ways to use data to drive revenue and keep your company competitive. Is that my job?”

Data Strategy 71

Data Strategy Strategy Consulting Experimentation 71

Insight

APRIL 28, 2020

In this article, we share some data-driven advice on how to get started on the right foot with an effective and appropriate screening process. How will they interact with product, engineering, sales, or marketing? Article by Adam Azzam. Originally posted on Open Data Science (ODSC). Will they be a strategic thought partner?

Data-driven 53

Data-driven Data Science Experimentation Measurement 53

Cloudera

NOVEMBER 25, 2020

Scale to provide 1,000s of researchers frictionless interaction with data. How can users drill down, in non-technical ways, to quickly interact with data that explains what correlations seem to matter? It would enable faster experimentation with easy, protected, and governed access to a variety of data.

Data Warehouse 59

Data Warehouse Unstructured Data Analytics Visualization 59

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. Experimentation with different technical analysis services becomes possible. Knowledge organization (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

Business Over Broadway

MAY 22, 2019

Below is a list of topics, answers and articles in support of a recent Tweet Chat in which I was the guest. I have included the topics of discussion, some of my answers and a list of articles in support of the week’s topic. Also, here is an article about 1 0 digital transformation influencers that will change your world.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

Alation

SEPTEMBER 28, 2022

However, there is a lot more to know about DataOps, as it has its own definition, principles, benefits, and applications in real-life companies today – which we will cover in this article! Daily Interactions. Technical environments and IDEs must be disposable so that experimental costs can be kept to a minimum. Simplicity.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

O'Reilly on Data

JULY 28, 2020

In this article, we turn our attention to the process itself: how do you bring a product to market? Without clarity in metrics, it’s impossible to do meaningful experimentation. Experimentation should show you how your customers use your site, and whether a recommendation engine would help the business. Identifying the problem.

Marketing 364

Marketing Experimentation Metrics Testing 364

Domino Data Lab

AUGUST 22, 2019

Note These three particular words are called articles , or determiners. Instead, we recommend using the bokeh library to create a highly interactive—and actionable—plot, as with the code provided in Example 11.11. Interactive bokeh plot of two-dimensional word-vector data. produces the interactive scatterplot in Figure 11.9

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

only in enough detail to motivate the types of uncertainty that are central to this article. For fluff.ai, the product is changing, how users interact with the product is changing, the needs of the organization are changing, new users are being added, tastes are changing (RIP Grumpy Cat ). leaves out. For instance, if fluff.ai

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

CIO Business Intelligence

APRIL 9, 2025

These conversational systems of interaction with data provide the context to answer questions based not only on what is being asked but by whom. Organizations are now moving past early GenAI experimentation toward operationalizing AI at scale for business impact. Modern BI dashboards wont be about correlated data sets.

Enterprise 102

Enterprise Analytics Experimentation Statistics 102

O'Reilly on Data

MARCH 19, 2020

The chatbot was one of the first applications of AI in experimental and production usage. This likely doesn’t portend the end of interactions with occasionally helpful—and still sometimes horrifying —customer service chatbots. For example, the chatbots topic continues to decline, first by 17% in 2018 and by 34% in 2019.

Deep Learning 354

Deep Learning Machine Learning Data-driven Modeling 354

O'Reilly on Data

JULY 25, 2023

This article summarizes what I learned from that experience. The inspiration (and title) for it comes from Mike Loukides’ Radar article on Real World Programming with ChatGPT , which shares a similar spirit of digging into the potential and limits of AI tools for more realistic end-to-end programming tasks.

Consulting 246

Consulting Interactive Software Metadata 246

Domino Data Lab

FEBRUARY 4, 2019

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. At this point I’m resisting an urge to quote and analyze nearly all of that HBR article. Articulating process for data science.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66

Sisense

MARCH 26, 2021

Some of those hurdles are overcome via dashboards, but they sit in a system several layers removed from anything that many people normally interact with. To achieve this, he says, companies should find ways to lower the cost of experimentation, decrease the time to value, and scale successful experimentation into products quickly.

Analytics 98

Analytics Data-driven Dashboards Experimentation 98

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Introduction. Welcome back to our monthly burst of themes and conferences.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

AUGUST 26, 2019

This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. Let’s use an example where we have four major processing steps: Standardize the data, Create interaction terms between the features, Discretize these features to big-small, and. Introduction.

Testing 79

Testing Modeling Machine Learning Metrics 79

Insight

MARCH 12, 2020

In this article, I will discuss the construction of the AIgent, from data collection to model assembly. After some experimentation, I landed on a strategy I’ll call ‘warm encoding’: if greater than 1% of tags were in a particular class, I encoded the book as belonging to that class, non-exclusively. In other words, if 0.1%

Modeling 59

Modeling Metadata Publishing Sales 59

CIO Business Intelligence

NOVEMBER 12, 2024

In a recent article on five IT risks CIOs should be paranoid about , I highlighted several IT team culture issues, including team burnout, mounting technical debt, and continuous crisis management cycles. Worse, issues that undermine IT culture may not appear in these KPIs or employee satisfaction surveys for months.

IT 140

IT Digital Transformation Management Experimentation 140