The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

IBM Big Data Hub

DECEMBER 5, 2023

Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time. The impact of these investments will become evident in the coming years.

Unstructured Data 95

Unstructured Data Cost-Benefit Experimentation Machine Learning 95

CIO Business Intelligence

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

O'Reilly on Data

MARCH 19, 2020

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. The chatbot was one of the first applications of AI in experimental and production usage.

Deep Learning 276

Deep Learning Machine Learning Data-driven Modeling 276

Cloudera

SEPTEMBER 17, 2020

Today’s data tool challenges. By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. .

Experimentation 80

Experimentation Data Warehouse Dashboards Visualization 80

CIO Business Intelligence

MAY 16, 2023

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. The inherent capabilities of AI–to process vast amounts of data and use learned intelligence to make decisions with extraordinary speed–enable opportunities uncovered through digital listening.

Advertising 94

Advertising Recreation/Entertainment Experimentation Enterprise 94

DataRobot Blog

OCTOBER 18, 2022

Organizations are looking for AI platforms that drive efficiency, scalability, and best practices, trends that were very clear at Big Data & AI Toronto. DataRobot Booth at Big Data & AI Toronto 2022. Monitoring and Managing AI Projects with Model Observability. Accelerating Value-Realization with Industry Specific Use Cases.

Big Data 96

Big Data Forecasting Experimentation Metrics 96

Sisense

MARCH 26, 2021

Companies surveyed by Harvard Business Review Analytic Services (HBR) report that two of the most important strategic benefits of using data analytics are (1) identifying new revenue and business models and (2) becoming more innovative. 39% of companies want to identify new revenue and business opportunities with data analytics.

Analytics 98

Analytics Data-driven Dashboards Experimentation 98

Smart Data Collective

JUNE 21, 2023

We also talked about some of the best AI-driven video editing applications. 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 77

Software Technology Experimentation Data-driven 77

Cloudera

AUGUST 20, 2020

Businesses had to literally switch operations, and enable better collaboration and access to data in an instant — while streamlining processes to accommodate a whole new way of doing things. This year, we hope to see even more stories of ML and AI driven innovation among the finalists. That’s really important.

Enterprise 120

Enterprise Experimentation Uncertainty Deep Learning 120

Cloudera

APRIL 9, 2021

This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

Ontotext

JULY 6, 2023

In today’s fast changing environment, enterprises that have transitioned from being focused on applications to becoming data-driven gain a significant competitive edge. There are four groups of data that are naturally siloed: Structured data (e.g., Transaction and pricing data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

CIO Business Intelligence

JULY 31, 2023

To allow or not According to various news reports, some big-name companies initially blocked generative AI tools such as ChatGPT for various reasons, including concerns about protecting proprietary data. 1 question now is to allow or not allow,” says Mir Kashifuddin, data risk and privacy leader with the professional services firm PwC US.

Strategy 98

Strategy Risk Enterprise Risk Management 98

CIO Business Intelligence

OCTOBER 4, 2022

Customers gravitate to personalized interactions and show a preference for companies that anticipate and cater to their unmet needs. Data has become the currency of so many organizations in understanding and delivering value for their customers,” says McLemore, who before joining AWS served as corporate CIO at Coca-Cola Co.

Data-driven 106

Data-driven Machine Learning Interactive Predictive Analytics 106

DataRobot

APRIL 19, 2021

Data Scientists Are AI Experts. But for more complex business decisions, including those that use less structured data, we have artificial intelligence systems. Data scientists train the algorithms using datasets that contain curated learning examples. They need data assembly, data science, integration, and visualization skills.

Machine Learning 52

Machine Learning Visualization Data-driven Data Science 52

Domino Data Lab

AUGUST 5, 2019

This Domino Data Science Field Note covers Chris Wiggins ‘s recent data ethics seminar at Berkeley. Data Scientists, Tradeoffs, and Data Ethics. As more companies become model-driven , data scientists are uniquely positioned to drive innovation and to help their companies remain economically strong.

Data Science 93

Data Science Data-driven Modeling Machine Learning 93

Ontotext

APRIL 3, 2024

Joseph Hilger : People are starting to understand that knowledge graphs are not just a tool for storing data and information. I need something that defines what those entities are and can align them with the data.” The other use case where graphs are exploding is what Gartner calls a data fabric. What are your thoughts about it?

Technology 59

Technology Risk Digital Transformation Measurement 59

Alation

SEPTEMBER 28, 2022

The term has been used a lot more of late, especially in the data analytics industry, as we’ve seen it expand over the past few years to keep pace with new regulations, like the GDPR and CCPA. In essence, DataOps is a practice that helps organizations manage and govern data more effectively. What exactly is DataOps ?

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

Sisense

JUNE 30, 2019

It doesn’t matter what you think your company does, it’s going to have to turn into a data company soon, if it hasn’t started already, in addition to continuing to provide your core product or service. Data Strategies for the Uninitiated. First off, “So, what even is a data strategy anyway?” Is that my job?”

Data Strategy 71

Data Strategy Strategy Consulting Experimentation 71

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. It helps you to amplify what’s proven to work, throw away what isn’t, and tweak the goal-posts when data indicates that they may be in the wrong place.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

datapine

MAY 20, 2020

A CRM dashboard is a centralized hub of information that presents customer relationship management data in a way that is dynamic, interactive, and offers access to a wealth of insights that can improve your consumer-facing strategies and communications. Let’s look at this in more detail. What Is A CRM Report? Sales Activity.

Dashboards 265

Dashboards Reporting KPI Visualization 265

FineReport

APRIL 24, 2024

Learn Data Visualization Understanding the Importance of Visualizing Data Data visualization is a powerful tool for conveying complex information in a clear and impactful manner. Whether it’s through charts, graphs, maps, or other visual formats, mastering data visualization is crucial for anyone working with data.

Visualization 52

Visualization Dashboards Interactive Data-driven 52

datapine

FEBRUARY 4, 2020

Today’s digital data has given the power to an average Internet user a massive amount of information that helps him or her to choose between brands, products or offers, making the market a highly competitive arena for the best ones to survive. First things first – organizing and prioritizing your marketing data.

Reporting 280

Reporting Marketing Advertising Metrics 280

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. The last 10+ years or so have seen Insurance become as data-driven as any vertical industry.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Domino Data Lab

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science. Introduction.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

DataRobot

SEPTEMBER 14, 2021

Becoming AI-driven is no longer really optional. And for those that do make it past the experimental stage, it typically takes over 18 months for the value to be realized. At the same time, business and data analysts want to access intuitive, point-and-click tools that use automated best practices.

Machine Learning 94

Machine Learning Modeling Experimentation Visualization 94

AWS Big Data

NOVEMBER 14, 2023

Data is a key strategic asset for every organization, and every company is a data business at its core. However, in many organizations, data is typically spread across a number of different systems such as software as a service (SaaS) applications, operational databases, and data warehouses.

IoT 55

IoT Data-driven Data Lake Data Strategy 55

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. Without large amounts of labeled training data solving most AI problems is not possible.

Management 110

Management Machine Learning Experimentation Metrics 110

AWS Big Data

MARCH 20, 2023

We discuss how to create such a solution using Amazon Kinesis Data Streams , Amazon Managed Streaming for Kafka (Amazon MSK), Amazon Kinesis Data Analytics for Apache Flink ; the design decisions that went into the architecture; and the observed business benefits by Poshmark.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

Occam's Razor

JUNE 6, 2007

Bonus: Interactive CD: Contains six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. Experimentation & Testing (A/B, Multivariate, you name it). Bonus: Interactive CD. Immediately actionable web analytics (your biggest worries covered). Clicks and outcomes.

Analytics 60

Analytics Metrics Marketing Dashboards 60

Occam's Razor

AUGUST 12, 2013

There are few things more complicated in analytics (all analytics, big data and huge data!) There is lots of missing data. And as if that were not enough, there is lots of unknowable data. Last Interaction/Last Click Attribution model. First Interaction/First Click Attribution Model. " low.

Modeling 161

Modeling Optimization Marketing Interactive 161

AWS Big Data

JUNE 20, 2023

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (Amazon S3) and data sources residing in AWS, on-premises, or other cloud systems using SQL or Python. Solution overview Data scientists are generally accustomed to working with large datasets.

Data Lake 70

Data Lake Data Science Recreation/Entertainment Experimentation 70

Domino Data Lab

JUNE 10, 2020

Today, we announced the latest release of Domino’s data science platform which represents a big step forward for enterprise data science teams. You can identify data drift, missing information, and other issues, and take corrective action before bigger problems occur.

Data Science 82

Data Science Enterprise Experimentation Modeling 82

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Cloudera

NOVEMBER 25, 2020

The challenges Matthew and his team are facing are mainly about access to a multitude of data sets, of various types and sources, with ease and ad-hoc, and their ability to deliver data-driven and confident outcomes. . Most of their research data is unstructured and has a lot of variety. Challenges Ahead.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

Domino Data Lab

JULY 28, 2021

The data science lifecycle (DLSC) has been defined as an iterative process that leads from problem formulation to exploration, algorithmic analysis and data cleaning to obtaining a verifiable solution that can be used for decision making. The data science process in a business environment begins with the Manage stage.

Data Science 59

Data Science Enterprise Modeling Experimentation 59

Occam's Razor

DECEMBER 12, 2016

There is, almost literally, an unlimited number of things you could focus on to create a high impact data-influenced organization. I was asked a few weeks back: " What companies should we proactively help with analytics, for free, so that they can make smarter data-influenced decisions ?" Data quality plays a role into this.

Analytics 141

Analytics Data-driven Strategy Consulting 141