CIO Business Intelligence

MARCH 1, 2023

Ever since we started the company back in 2011, when I was CIO, we’ve been using data to improve our operations. These are machine learning–based models that look at which trucks need to move where, what we are loading onto the trailers, and how many trailers the trucks should haul to maximize efficiency.

ROI 52

ROI Machine Learning Sales Technology 52

Cloudera

SEPTEMBER 20, 2022

The state of the art in AI systems for artistic tasks almost universally use deep-learning models, which presuppose a significant amount of compute resources both to create them, and once created to continue to use them for producing images. The content of these data sets may introduce problematic bias into a model’s results.

Deep Learning 92

Deep Learning Cost-Benefit Risk Data-driven 92

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

Smart Data Collective

APRIL 2, 2019

According to Forbes in 2011, the idea of the Data Lake was already gaining traction as companies started to consider the idea of moving their data from off-site repositories to cloud-accessible online storage , a reality that was further cemented by the cheap availability of cloud storage. The Thrust for Data Lake Creation.

Data Lake 83

Data Lake Big Data OLAP Testing 83

Occam's Razor

OCTOBER 21, 2013

In late 2011, Google announced an effort to make search behavior more secure. I've gone through the five stages in the Kubler-Ross model. Bonus: For more on next steps and attribution modeling please see: Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models. ]. want to protect user privacy.

Optimization 154

Optimization Reporting Experimentation Metrics 154

Occam's Razor

APRIL 25, 2011

The issues of course include people and jaded mental models and bureaucracy and a lack of time and the missing desire to be great and org structures, and bosses. " I'd postulated this rule in 2005, it is even more true in 2011. Doing anything on the web without a Web Analytics Measurement Model. Yet there they are.

Marketing 126

Marketing Measurement Metrics Testing 126

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Occam's Razor

JUNE 28, 2011

Web Analysts are blessed with an immense amount of data, and an amazing amount of valuable, even sexy, metrics to understand business performance. Yet our heroic efforts to report the aforementioned sexy metrics lead to little business action. Since crappy sounds bad, let's just say you are reporting super lame metrics.

Metrics 126

Metrics Measurement Key Performance Indicator Reporting 126

Peter James Thomas

AUGUST 12, 2018

Pertinence and fidelity of metrics developed from Data. Metrics are seldom reliant on just one data element, but are often rather combinations. There are often compromises to be made in defining metrics. Again see Using BI to drive improvements in data quality for further details. Some of these are based on the data available.

Metrics 49

Metrics Statistics Data Quality Measurement 49

CIO Business Intelligence

NOVEMBER 7, 2022

Since that 2011 revelation, Arooni has been doing just that: redefining IT organizations and service delivery models to embrace agile ways of working, including creating product-centric structures with persistent teams responsible for the entire lifecycle of a product. Ema Patki, vice president of software engineering, Align.

IT 116

IT Technology Modeling Software 116

datapine

APRIL 15, 2020

The term “agile” was originally conceived in 2011 as a software development methodology. Business intelligence is moving away from the traditional engineering model: analysis, design, construction, testing, and implementation. In the traditional model communication between developers and business users is not a priority.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

The Unofficial Google Data Science Blog

JULY 18, 2023

Once we’ve answered that, we will then define and use metrics to understand the quality of human-labeled data, along with a measurement framework that we call Cross-replication Reliability or xRR. We will follow the example of Janson and Olsson , and start from this generalized definition of the metric, which they call iota.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Domino Data Lab

OCTOBER 9, 2019

It divides the observations into discrete groups based on some distance metric. According to David Madigan, the former chair of Department of Statistics and current Dean of Faculty of Arts and Sciences and Professor of Statistics at Columbia University, a good metric for determining the optimal number of clusters is Hartigan’s rule (J.

Statistics 100

Statistics Machine Learning Metrics Measurement 100

Sisense

JULY 1, 2021

Marketing technology tools (also referred to as MarTech tools) have multiplied from about 150 in 2011 to around 8,000 today, a 5,233% increase that sends a clear message: Marketers are embracing digital assistance and data/analytics. In a world of rapid technological change, digital tools for marketers are having a moment.

Marketing 52

Marketing Experimentation Marketing Analytics ROI 52

Domino Data Lab

MARCH 3, 2019

What’s been the impact of using ML models on culture and organization? Who builds their models? What metrics are used to evaluate success? We also used maturity , in other words how long had an enterprise organization been deploying ML models in production?

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

datapine

AUGUST 29, 2022

And with that understanding, you’ll be able to tap into the potential of data analysis to create strategic advantages, exploit your metrics to shape them into stunning business dashboards , and identify new opportunities or at least participate in the process. Microsoft, Alibaba, Taobao, WebMD, Spotify, Yelp” according to Marz himself.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

The Unofficial Google Data Science Blog

MAY 31, 2016

This means it is possible to specify exactly in which geos an ad campaign will be served – and to observe the ad spend and the response metric at the geo level. In other words, iROAS is the slope of a curve of the response metric plotted against the underlying advertising spend. They are non-overlapping geo-targetable regions.

Advertising 42

Advertising Testing Sales Statistics 42

Occam's Razor

FEBRUARY 22, 2010

Feel better? : ) When should you start doing paid search advertising for tours to Italy for 2011? The panel methodology is based on the traditional television data capture model. Check the definitions of various metrics. Hybrid Data Bottom-line: I love customers, I love Task Completion Rate as a powerful metric, I love VOC.

Metrics 123

Metrics Advertising Reporting Software 123

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

With more features come more potential post hoc hypotheses about what is driving metrics of interest, and more opportunity for exploratory analysis. Looking at metrics of interest computed over subpopulations of large data sets, then trying to make sense of those differences, is an often recommended practice (even on this very blog).

Experimentation 61

Experimentation Testing Statistics Metrics 61

Ontotext

MARCH 24, 2021

For these reasons, publishing the data related to elections is obligatory for all EU member states under Directive 2003/98/EC on the re-use of public sector information and the Bulgarian Central Elections Committee (CEC) has released a complete export of every election database since 2011. The road ahead.

Statistics 142

Statistics Data Processing Publishing Metrics 142

O'Reilly on Data

MAY 11, 2020

Not all models are created equal, however: they operate on different principles, and impact us as individuals and communities in different ways. To understand the menagerie of models that are fundamentally altering our individual and shared realities, we need to build a typology, a classification of their effects and impacts.

Modeling 189

Modeling Advertising Recreation/Entertainment Metrics 189