O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. As model building become easier, the problem of high-quality data becomes more evident than ever.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

Sisense

AUGUST 12, 2021

Using beer sales statistics to understand the consumer. Using beer sales statistics to understand the consumer. RetailZoom analyzed beer sales statistics gathered from 95% of the supermarkets in its native Cyprus. Beer culture has risen in the US and worldwide, with over a half-trillion USD in sales annually ?—

Sales 98

Sales Statistics Manufacturing Dashboards 98

IBM Big Data Hub

MAY 1, 2023

Continued advancement in AI development has resulted today in a definition of AI which has several categories and characteristics. The four categories of predictive modelling, robotics, speech and image recognition are collectively known as algorithm-based AI or Discriminative AI. It has taken the world by storm.

Insurance 80

Insurance Predictive Modeling Cost-Benefit Statistics 80

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature. Among these, only statistical uncertainty has formal recognition. Vignette: Data Science at fluff.ai

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Rocket-Powered Data Science

MARCH 10, 2020

In 2019, I was asked to write the Foreword for the book “ Graph Algorithms: Practical Examples in Apache Spark and Neo4j “ , by Mark Needham and Amy E. I wrote an extensive piece on the power of graph databases, linked data, graph algorithms, and various significant graph analytics applications. Graph Algorithms book.

Metadata 250

Metadata Machine Learning ROI Prescriptive Analytics 250

Sisense

SEPTEMBER 3, 2020

The good news is that if you are passionate about data and have the skills to back it up, you can probably find a challenging, rewarding role. We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! Data Scientist.

Statistics 97

Statistics Metrics Visualization Finance 97

The Unofficial Google Data Science Blog

SEPTEMBER 30, 2016

The statistics app for Google Sheets hopes to change that. Editor's note: We've mostly portrayed data science as statistical methods and analysis approaches based on big data. Introduction Statistics for Google Sheets is an add-on for Google Sheets that brings elementary statistical analysis tools to spreadsheet users.

Statistics 53

Statistics Big Data Data Science Marketing 53

Peter James Thomas

OCTOBER 1, 2019

Categories and values (see below) are plotted on axes. Throughout I use the word “category” to refer to something discrete that is plotted on an axis, for example France, Germany, Italy and The UK, or 2016, 2017, 2018 and 2019. With a few exceptions, the Charts described below plot values against categories.

Sales 61

Sales Measurement Statistics Data Architecture 61

Smarten

DECEMBER 3, 2023

The augmented analytics search engine allows users to factor in several variables, e.g., a list of sales team members, a time period or range, a category of products or items etc. What is Augmented Analytics and How Has it Evolved? Maybe you just want to understand the analytics solution market better.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

Sisense

JUNE 26, 2020

You’re probably tired of hearing that information is proliferating at a rate that humans can barely comprehend, let alone keep up with. As datasets become bigger and more complex, only AI, materialized views, and more sophisticated coding languages will be able to glean insights from them. The good news is, you don’t have to!

Visualization 97

Visualization Unstructured Data Measurement Data-driven 97

datapine

SEPTEMBER 4, 2023

A visual is processed 60,000 times faster than any text, and studies show that 65% of the population comprises visual learners. Moreover, 90% of the information transferred to the brain is visual. This very notion is the core of visualization.

Interactive 264

Interactive Visualization Cost-Benefit Dashboards 264

Sisense

SEPTEMBER 25, 2020

A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. Statistics and programming go hand in hand. Importance of statistical techniques.

Statistics 98

Statistics Modeling Predictive Modeling Machine Learning 98

The Unofficial Google Data Science Blog

JULY 18, 2023

by MICHAEL QUINN, JEREMY MILES, KA WONG As data scientists, we often encounter situations in which human judgment provides the ground truth. But humans often disagree, and groups of humans may disagree with each other systematically (say, experts versus laypeople). This isn’t a new approach either.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Insight

AUGUST 5, 2020

Humans show a myriad of explicit and implicit emotional signals in our behaviors. Our facial expression, posture, and even the music we listen to are types of expressions that tell the overarching story of how we feel. For this reason, signals that could help us understand ourselves and our emotions go unnoticed. you get a daunting enigma.

Predictive Modeling 98

Predictive Modeling Statistics Modeling Measurement 98

Peter James Thomas

APRIL 9, 2019

Given the advent of the Maths & Science section, there are now seven categories into which I have split articles. Statistics & Data Science. In each category, I will pick out one or two pieces which I feel are both representative of my overall content and worth a read. Statistics & Data Science. The number ?

Data-driven 49

Data-driven Statistics Big Data Data Science 49

The Unofficial Google Data Science Blog

AUGUST 27, 2019

We want to estimate the prevalence of violation of each individual policy category (we call them policy verticals ) by sampling the videos and manually reviewing those sampled videos. We also cover many practical challenges encountered in implementation when the requirement is to produce fresh and regular estimates of prevalence.

Metrics 98

Metrics Statistics Uncertainty Optimization 98

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Depict Data Studio

MARCH 27, 2023

Sure, she probably has public-facing talks on YouTube. This was the perfect length: a half-day of dataviz principles and quick drawing exercises, followed by a half-day focused on a bigger project. Participants were mostly based in the U.S. and Europe , with most people using data for part/all of their job. and some basic art supplies (e.g.,

Visualization 52

Visualization Consulting Experimentation Dashboards 52

datapine

MAY 2, 2019

The fundamental categories that differentiate these questions are based on: Relationship. Modern dashboard software makes it simpler than ever to merge and visualize data in a way that’s as inspiring as it is accessible. But while doing so is easy, a great dashboard still requires a certain amount of strategic planning and design thinking.

Visualization 173

Visualization Dashboards Sales KPI 173

Depict Data Studio

APRIL 10, 2023

and implications of findings) than in statistical significance. Visualizing data in charts, graphs, dashboards, and infographics is one of the most powerful strategies for getting your numbers out of your spreadsheets and into real-world conversations. But it can be overwhelming to get started with data visualization.

Visualization 105

Visualization Dashboards Testing Reporting 105

Darkhorse

JULY 6, 2017

Maybe they converted from an AS/400 at some point and everything thereafter has more decimals or more values. Once you’ve documented and understood your sources, you have reached the second stage: data sloughs (note, you have more than one). Now comes the fun part: cleaning up your data. After cleaning, it’s on to organizing your data. That’s fine.

Data Lake 74

Data Lake Sales Machine Learning Visualization 74

datapine

SEPTEMBER 29, 2022

With a shocking 2.5 quintillion bytes of data being produced on a daily basis and the wide range of online data analysis tools in the market, the use of data and analytics has never been more accessible. However, with all good things comes many challenges and businesses often struggle with managing their information in the correct way.

Data Quality 241

Data Quality Metrics Data-driven Management 241

CIO Business Intelligence

OCTOBER 14, 2022

Product managers aren’t a new job category by any means, but this shift means that they’re newly prominent and important to many companies’ strategies. These new building blocks of business include both tech and business pros, and they’re generally led by a product manager , who acts as the point person throughout the product’s lifecycle.

Management 101

Management IT Consulting Marketing 101

Depict Data Studio

JULY 28, 2020

Our organizations collect all this data—through surveys, assessments, interviews, and so on— and then what? The default: The data just sits there inside a Dusty Shelf Report. But what if your data could actually inform real-life decisions? metro area. The topic was school reopening plans for the 2020-2021 academic year. Watch the Conversation Below.

Visualization 102

Visualization Reporting Modeling Statistics 102

datapine

MAY 16, 2019

A sobering statistic if ever we saw one. The restaurant industry is one of the most competitive sectors on the planet. Not only do we as a species need to eat and drink to survive; communal dining is an experience that people have cherished for centuries. But shockingly, 50,000 restaurant locations close their doors each year.

Analytics 163

Analytics Predictive Analytics Advertising Dashboards 163

O'Reilly on Data

APRIL 19, 2021

That clearly doesn’t reflect reality; China is a leader in AI and probably has more AI developers than any other nation, including the US. First, we wanted to understand how the use of AI grew in the past year. The most striking result is the sheer number of respondents. While it’s still an issue, culture has dropped to fourth place.

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

Smarten

JUNE 29, 2018

The KNN (K Nearest Neighbors) algorithm analyzes all available data points and classifies this data, then classifies new cases based on these established categories. It is useful for recognizing patterns and for estimating. We would first determine K = number of nearest neighbors (in terms of distance) to check for class assignment.

Enterprise 40

Enterprise Business Intelligence Predictive Modeling Statistics 40

Depict Data Studio

MARCH 23, 2021

You might participate in a program evaluation where the evaluator helps you brainstorm what your questions are and how to collect data to answer those questions. Collect the data. Design and administer surveys. Organize focus groups. Review public data sources (e.g., Census data). Analyze the data. But it doesn’t have to be a headache, either.

Analytics 52

Analytics Visualization Testing Measurement 52

Domino Data Lab

AUGUST 20, 2019

Feature coding involves choosing a set of symbolic values to represent different categories. Many thanks to AWP Pearson for the permission to excerpt “Manual Feature Engineering: Manipulating Data for Fun and Profit” from the book, Machine Learning with Python for Everyone by Mark E. Introduction.

Testing 68

Testing Modeling Interactive Measurement 68

Grooper

AUGUST 19, 2019

You can probably imagine that the top roadblock was culture challenges to accept change. You can probably imagine that the top roadblock was culture challenges to accept change. Successfully navigating the 20,000+ analytics and business intelligence solutions on the market requires a special approach. A Modern Approach is Needed.

Analytics 54

Analytics Machine Learning Data-driven Data Science 54

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Introduction. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Depict Data Studio

APRIL 16, 2019

Long ago, I had majored in psychology so I could take as many research methods and statistics courses as possible. A couple weeks ago, I led a series of half-day workshops for faculty members and graduate students at the University of South Carolina in Columbia, South Carolina. I had initially planned to become a psychology professor.

Visualization 56

Visualization Reporting Statistics Dashboards 56

The Unofficial Google Data Science Blog

OCTOBER 31, 2016

It’s fine to exclude them from your data or to lump them together into an “Unusual” category, but you should make sure you know why data ended up in that category. We were often asked to make sense of confusing results, measure new phenomena from logged behavior, validate analyses done by others, and interpret metrics of user behavior.

Metrics 107

Metrics Measurement Statistics Data Collection 107

The Unofficial Google Data Science Blog

MARCH 22, 2018

Background At Google, experimentation is an invaluable tool for making decisions and inference about new products and features. An experimenter, once their candidate product change is ready for testing, often needs only to write a few lines of configuration code to begin an experiment. they get with the new version.

Experimentation 62

Experimentation Measurement Modeling Statistics 62

Domino Data Lab

JANUARY 6, 2019

I’ve been teaching data science since 2008 privately for employers – exec staff, investors, IT teams, and the data teams I’ve led – and since 2013, for industry professionals in general. However, right now is an interesting point in time to consider: “What needs to be taught? What are the foundational parts of our field?”. Learning Data Science.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

O'Reilly on Data

MAY 27, 2020

My exact score is lost to history, but one of the doctors in the room tells me it was probably a six or less out of ten. And yet a number or category label that describes a human life is not only machine-readable data. You get two points for waving your arms and legs, for instance.) Numbers like that typically mean a baby needs help.

Risk 354

Risk Testing Measurement Reporting 354

O'Reilly on Data

NOVEMBER 28, 2023

Almost everybody’s played with ChatGPT, Stable Diffusion, GitHub Copilot, or Midjourney. A few have even tried out Bard or Claude, or run LLaMA 1 on their laptop. 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.

Enterprise 269

Enterprise Modeling Testing Reporting 269