Sisense

DECEMBER 3, 2019

Data is the New Oil” was coined by The Economist in May 2017 and became a mantra for organizations to drive new wealth from data. But in reality, data by itself has no value. The rapid growth of data volumes has effectively outstripped our ability to process and analyze it. Unleash the power of advanced analytics.

Analytics 90

Analytics Data Warehouse Digital Transformation Forecasting 90

Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Peter James Thomas

APRIL 9, 2019

As in 2017 , I have failed miserably in my original objective of posting this early in January. This increase was driven in part by the launch of my new Maths & Science section , articles from which claimed no fewer than 6 slots in the 2018 top 10 articles, when measured by hits [1]. These are as follows: General Data Articles.

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Cloudera

SEPTEMBER 10, 2021

The IRS has spent more than a decade working to combat high-cost hazards, including launching a collaborative Identity Theft Tax Refund Fraud Information Sharing and Analysis Center (ISAC) pilot for the 2017 tax-filing season, advancing authentication tools and taking proactive steps in fighting business identity theft.

Machine Learning 69

Machine Learning Statistics Data-driven Big Data 69

Smarten

MAY 11, 2017

Self-Serve Data Preparation provides seamless data access and allows users to discover, transform, mash-up and integrate data for clear analytics. Plug n’ Play Predictive Analysis enables business users to explore power of predictive analytics without indepth understanding of statistics and data science.

Experimentation 49

Experimentation Visualization Predictive Analytics Business Intelligence 49

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. Introduction Time series data appear in a surprising number of applications, ranging from business, to the physical and social sciences, to health, medicine, and engineering.

Forecasting 66

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The Unofficial Google Data Science Blog

JULY 22, 2020

For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. One reason to do ramp-up is to mitigate the risk of never before seen arms.

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. On the one hand, basic statistical models (e.g. GAMs are popular among data science and machine learning applications for their simplicity and interpretability.

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

Peter James Thomas

JUNE 20, 2019

Of course it can be argued that you can use statistics (and Google Trends in particular) to prove anything [1] , but I found the above figures striking. © Scott Adams (2017) – dilbert.com. In 2017, a survey estimated that 68 percent of American offices had low or no separation between workers.

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Domino Data Lab

JANUARY 6, 2019

In Paco Nathan ‘s latest column, he explores the theme of “learning data science” by diving into education programs, learning materials, educational approaches, as well as perceptions about education. He is also the Co-Chair of the upcoming Data Science Leaders Summit, Rev. Learning Data Science.

Data Science 56

Data Science Machine Learning Visualization Reporting 56

Smarten

JANUARY 3, 2019

By enabling data integration and ease of analysis through the organization, the business can cascade knowledge and skill and make it easier for every business user to complete tasks, make accurate decisions and perform with agility in a fast-paced business environment. ’ Clearly, Citizen Analysts are here to stay!

Business Intelligence 40

Business Intelligence Statistics Interactive Data Science 40

Domino Data Lab

OCTOBER 23, 2019

As a result, there has been a recent explosion in individual statistics that try to measure a player’s impact. Eighty percent of this problem is collecting the data and then transforming the data. The other 20 percent is ML- and data science–related tasks like finding the right model, doing EDA, and feature engineering.

Statistics 59

Statistics Machine Learning Testing Modeling 59

The Unofficial Google Data Science Blog

APRIL 17, 2017

An obvious requisite property of reconciliation is arithmetic coherence across the hierarchy (which is implicit in the sum-up-from-the-bottom possibility in the previous paragraph), but more sophisticated reconciliation may induce statistical stability of the constituent forecasts and improve forecast accuracy across the hierarchy.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Peter James Thomas

AUGUST 12, 2018

I explore some similar themes in a section of Data Visualisation – A Scientific Treatment. Integrity of statistical estimates based on Data. Having spent 18 years working in various parts of the Insurance industry, statistical estimates being part of the standard set of metrics is pretty familiar to me [7].

Statistics 49

Statistics Metrics Data Quality Measurement 49

The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. e-handbook of statistical methods: Summary tables of useful fractional factorial designs , 2018 [3] Ulrike Groemping. Hedayat, N.J.A.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

The Unofficial Google Data Science Blog

MARCH 13, 2017

By MUKUND SUNDARARAJAN, ANKUR TALY, QIQI YAN Editor's note: Causal inference is central to answering questions in science, engineering and business and hence the topic has received particular attention on this blog. Not just a black box: Learning important features through propagating activation differences. CoRR, 2016. [3] Le, Andrew M.

IT 70

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Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

CIO Business Intelligence

JULY 20, 2022

The 2022 State of the CIO research confirmed talent acquisition and retention strategies are a key issue for CIOs, cited by 38% of respondents, with cybersecurity skills, data science/analytics, and artificial intelligence (AI) and machine learning (ML) in top demand.

IT 136

IT Software Cost-Benefit Strategy 136

Jen Stirrup

JUNE 20, 2020

My analysis is based on the Financial statements put forward by PASS using some basic metrics; until you do that piece, you can’t move forward to compare and contrast it with other data since you have not done your ‘descriptive statistical analysis’ first to ensure that the comparison is valid. Current Ratio.

Metrics 104

Metrics Business Analytics Data-driven Statistics 104

The Unofficial Google Data Science Blog

JULY 18, 2023

Editor's note : The relationship between reliability and validity are somewhat analogous to that between the notions of statistical uncertainty and representational uncertainty introduced in an earlier post. In what follows, assume we have a large number of items and people, so that the measures have little statistical uncertainty.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

O'Reilly on Data

JANUARY 25, 2021

Our data shows that Chef and Puppet peaked in 2017, when Kubernetes started an almost exponential growth spurt, as Figure 4 shows. AI, Machine Learning, and Data. Healthy growth in artificial intelligence has continued: machine learning is up 14%, while AI is up 64%; data science is up 16%, and statistics is up 47%.

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Machine Learning Software Testing Technology 364

Data Science and Beyond

JANUARY 8, 2017

As of early 2017, fewer than half. Indeed, several people have commented on the flaws in Kissmetrics’ approach, which is reminiscent of the Dilbert strip where the pointy-haired boss asks Dilbert to average and multiply wrong data. You google the term, and end up on a page with ten results (and probably some ads). Why is that?

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