CIO Business Intelligence

JULY 24, 2023

Insights gleaned from Mediacoach are intended for technical staff—coaches and doctors, for example—but LaLiga has also created Beyond Stats, a portal powered by Mediacoach that packages and presents data for media and fans via a range of accessible dashboards. “We

Broadcasting 80

Broadcasting Recreation/Entertainment Testing Machine Learning 80

O'Reilly on Data

JUNE 18, 2019

The good news is that researchers from academia recently managed to leverage that large body of work and combine it with the power of scalable statistical inference for data cleaning. HoloClean adopts the well-known “noisy channel” model to explain how data was generated and how it was “polluted.” Market validation.

Machine Learning 264

Machine Learning Data Quality Statistics Modeling 264

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

O'Reilly on Data

MAY 18, 2020

And last is the probabilistic nature of statistics and machine learning (ML). Most AI models decay overtime: This phenomenon, known more widely as model decay , refers to the declining quality of AI system results over time, as patterns in new data drift away from patterns learned in training data.

Risk 361

Risk Modeling Data Processing Software 361

Data Science 101

JUNE 10, 2019

They can clean large amounts of data, explore data sets to find trends, build predictive models, and create a story around their findings. The power of data science comes from a deep understanding of statistics,algorithms, programming, and communication skills. A data scientist can run a project from end-to-end. Data Analysts.

Data Science 96

Data Science Statistics Predictive Modeling Machine Learning 96

The Data Visualisation Catalogue

APRIL 4, 2019

Then in around 2016, I first started using VR hardware and from there I had two thoughts: first, that VR is going to be the most revolutionary technology of my lifetime; and second, that VR can make the process of data analysis and presentation much easier (especially in my job as an investment analyst). Give Presentations Anywhere.

Dashboards 72

Dashboards Predictive Modeling Visualization Modeling 72

DataRobot Blog

JULY 28, 2022

This article presents a case study of how DataRobot was able to achieve high accuracy and low cost by actually using techniques learned through Data Science Competitions in the process of solving a DataRobot customer’s problem. I thought of the solutions of the top team in a Data Science Competition for LANL Earthquake Prediction.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

Sisense

AUGUST 11, 2019

Typically, this involves using statistical analysis and predictive modeling to establish trends, figuring out why things are happening, and making an educated guess about how things will pan out in the future. So, BI deals with historical data leading right up to the present, and what you do with that information is up to you.

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

Smarten

JUNE 27, 2018

This article presents a brief explanation of Outliers, and how this type of analysis is used. All of these tools are designed for business users with average skills and require no special skills or knowledge of statistical analysis or support from IT or data scientists. What is Outlier Analysis?

IT 40

IT Business Intelligence Predictive Modeling Testing 40

Insight

AUGUST 5, 2020

You have to wrangle all these implicit emotion-conveying signals to predict one final output: how is this person feeling right now? Given the breadth of information required, estimating mood from audio recordings presents an interesting challenge. Summary statistics (i.e. up to 20% for prediction of ‘happy’ in females?—?in

Predictive Modeling 98

Predictive Modeling Statistics Modeling Measurement 98

datapine

MARCH 25, 2022

There is not a clear line between business intelligence and analytics, but they are extremely connected and interlaced in their approach towards resolving business issues, providing insights on past and present data, and defining future decisions. What Is Business Intelligence And Analytics?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

O'Reilly on Data

MARCH 23, 2021

On top of this, pre-existing societal biases are being reinforced and promulgated at previously unheard of scales as we increasingly integrate machine learning models into our daily lives. For print presented an image of repeatable precision that inspired totally new forms of extending social energies.

Internet Publishing and Broadcasting 319

Internet Publishing and Broadcasting Broadcasting Data-driven Interactive 319

Smarten

APRIL 19, 2024

Assisted Predictive Modeling and Auto Insights to create predictive models using self-guiding UI wizard and auto-recommendations The Future of AI in Analytics The C=suite executive survey revealed that 93% felt that data strategy is critical to getting value from generative AI, but a full 57% had made no changes to their data.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

O'Reilly on Data

MARCH 20, 2019

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. If an attacker can receive many predictions from your model API or other endpoint (website, app, etc.),

Modeling 227

Modeling Machine Learning Predictive Modeling Consulting 227

Domino Data Lab

NOVEMBER 17, 2020

Classical statistics, developed in the 20 th century for small datasets, do not work for data where the number of variables is much larger than the number of samples (Large P Small N, Curse of Dimensionality, or P >> N data). Predictive models fit to noise approach 100% accuracy. Antimicrobial. Autoimmunity. IL-4, IL-13.

Statistics 131

Statistics Measurement Testing Predictive Modeling 131

Domino Data Lab

JANUARY 21, 2021

Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. Results become the basis for understanding the solution space (or, ‘the realm of the possible’) for a given modeling task. Each dataset has properties that warrant producing specific statistics or charts.

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

Domino Data Lab

AUGUST 12, 2021

In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase. Excellent, let us look at the descriptive statistics for our dataset. If we were to use this column in a model, we are now aware that we have an unbalanced dataset.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

DataRobot Blog

DECEMBER 1, 2022

Artificial intelligence (AI) can help improve the response rate on your coupon offers by letting you consider the unique characteristics and wide array of data collected online and offline of each customer and presenting them with the most attractive offers. Training and Testing Different AI Models.

Machine Learning 52

Machine Learning Marketing Modeling Statistics 52

FineReport

APRIL 24, 2024

What is Data Visualization Understanding the Concept Data visualization, in simple terms, refers to the presentation of data in a visual format. It enables organizations to effectively convey their findings and insights, fostering collaboration and driving impactful decisions based on the presented information.

Visualization 52

Visualization Dashboards Interactive Key Performance Indicator 52

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

Nor can we learn prediction intervals across a large set of parallel time series, since we are trying to generate intervals for a single global time series. With those stakes and the long forecast horizon, we do not rely on a single statistical model based on historical trends.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Rocket-Powered Data Science

OCTOBER 6, 2023

What is the point of those obvious statistical inferences? The point is that the 100% association between the event and the preceding condition has no special predictive or prescriptive power. The probability of the condition X occurring, P(X), is irrelevant since the existence of the precondition X is implicitly present by default.

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

Occam's Razor

NOVEMBER 17, 2008

So you don't have to worry about integrations with analytics tools, you don't have to worry about rushing to get a PhD in Statistics to interpret results and what not. Now it did present a fundamental challenge, no one like to give revenue up. Rather than create prediction models (with faulty assumptions!)

Testing 112

Testing Experimentation Risk Optimization 112

Smarten

JUNE 25, 2018

This article provides a brief explanation of the definition and uses of the Descriptive Statistics algorithms. What is a Descriptive Statistics? Descriptive statistics helps users to describe and understand the features of a specific dataset, by providing short summaries and a graphic depiction of the measured data.

Statistics 40

Statistics Enterprise Measurement Business Intelligence 40

Domino Data Lab

JULY 9, 2019

Chris Wiggins , Chief Data Scientist at The New York Times, presented “Data Science at the New York Times” at Rev. One of the ways I frame that is, “Are you looking to build a predictive model? or a prescriptive model? or a descriptive model?” We have a very good data governance group.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

datapine

NOVEMBER 27, 2019

The trends we presented last year will continue to play out through 2020. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. Time gain is also present in the form of AI assistants. Suddenly advanced analytics wasn’t just for the analysts.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

JULY 3, 2017

By the time the user receives the report, the data may be outdated or it may be presented in a way that makes it difficult to interpret and use. Tools like plug n’ play predictive analysis and smart data visualization ensure data democratization and drastically reduce the time and cost of analysis and experimentation.

Visualization 40

Visualization Predictive Modeling Business Intelligence Experimentation 40

Domino Data Lab

AUGUST 22, 2019

In the present chapter [excerpt], we cover code that will enable you to create your own word vectors as well as to provide them as an input into a deep learning model. Although it’s not perfect, [Note: These are statistical approximations, of course!] Compiling the model (Example 11.20). Example 11.6 Note: Cho, K.,

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

datapine

DECEMBER 4, 2019

Without a doubt, it’s a big technological advancement, and one of the big statistics buzzwords, but the extent to which it is believed to be already applied is vastly exaggerated. The commercial use of predictive analytics is a relatively new thing. The accuracy of the predictions depends on the data used to create the model.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Data Science and Beyond

JANUARY 8, 2017

Popularity is a function of inbound links (weighted by site credibility), and of user interaction with the presented results (e.g., My main problem with the Kissmetrics infographic is that it helps feed an illusion of understanding that is prevalent among those with no statistical training.

Statistics 100

Statistics Modeling Predictive Modeling Marketing 100

Jet Global

MAY 1, 2023

Discuss, don’t present. Present your business case. To support your case, present findings from the State of Embedded Analytics study. Information Delivery The main reason software providers take on an embedded analytics project is to improve how data is presented. It is now most definitely a need-to-have.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MAY 9, 2024

Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment. This allows them to make informed decisions about the next steps in their analysis or modeling process.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52