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

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. What Is Business Intelligence And Analytics?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Smarten

JULY 26, 2022

The Smarten mobile application provides intuitive dashboards and reports, stunning visualizations, dynamic charts and graphs and key performance indicators (KPIs). “Users can analyze and interact with data with full visibility of dashboards, reports and other BI objects.”

Key Performance Indicator 74

Key Performance Indicator Analytics Business Intelligence Dashboards 74

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

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2) Data Discovery/Visualization. Data exploded and became big.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

APRIL 12, 2023

Smarten CEO, Kartik Patel says, ‘Smarten SnapShot supports the evolving role of Citizen Data Scientists with interactive tools that allow a business user to gather information, establish metrics and key performance indicators.’

Snapshot 52

Snapshot Key Performance Indicator KPI Business Intelligence 52

CIO Business Intelligence

APRIL 25, 2022

The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. On-site courses are available in Munich. Remote courses are also available. Switchup rating: 5.0 (out

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

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

FineReport

MAY 29, 2020

It is a part of BI features that allow you to extract and dynamically display data in the form of different types of visualizations such as charts and tables, so users can transform data into useful information and discover insights. . BI Reports can vary in their interactivity. The ‘data’ part is the statistics and data display. .

Reporting 94

Reporting OLAP Visualization Software 94

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Smarten

DECEMBER 3, 2023

As Springboard notes, ‘Augmented Analytics is an example of human machine interaction in the data science field.’ So, you can ask, ‘Who sold the most bakery items in the Southwest region from September through November of 2022,’ and you will receive your results and can visualize your data in a way that makes sense to you and to your team.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

The Data Visualisation Catalogue

APRIL 4, 2019

I’ve implemented DataView in my own work and find it an excellent way to organize investment information, do data discovery and create predictive models. Application #2: Creating and visualizing multi-variable relationships, which is particularly useful in creating predictive models.

Dashboards 73

Dashboards Predictive Modeling Visualization Modeling 73

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

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. We covered the importance of Exploratory Analytics including observing the frequency of missing data and computing interactions of all features. Pandas Profiler.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

Jet Global

MAY 9, 2024

For example, streaming data from sensors to an analytics platform where it is processed and visualized immediately. Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Cloudera

NOVEMBER 2, 2020

It is very hard to maintain interactive performance, over large amounts of data that is arriving very fast, some of which might need updates, with a large number of queries of varying patterns. Fast ingest of streaming data, interactive queries, very high scale. Tool for visualizing, dashboarding, and report building.

Data Warehouse 94

Data Warehouse Optimization Dashboards Interactive 94

Birst BI

OCTOBER 30, 2018

The foundation of predictive analytics is based on probabilities. To generate accurate probabilities of future behavior, predictive analytics combine historical data from any number of applications with statistical algorithms. A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Jet Global

MAY 1, 2023

Plus, there is an expectation that tools be visually appealing to boot. In the past, data visualizations were a powerful way to differentiate a software application. Their dashboards were visually stunning. Today, free visualizations seem to be everywhere. Users’ varied needs require a shift in traditional BI thinking.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Darkhorse

JULY 6, 2017

Let’s further pretend you’re starting out with the aim of doing a big predictive modeling thing using machine learning. Proceed visually. Summary statistics are not your friend – they may in fact lead you astray. This is level seven – when you interact with your stakeholders using data. So what is data wrangling?

Data Lake 74

Data Lake Sales Machine Learning Visualization 74

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. The describe function on a Pandas DataFrame provides descriptive statistics, including the number of columns, in this case 27, and median (this is the 50 percent row), for each column. 05) in predicting changes in attendance.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

AUGUST 20, 2019

There are three major strategies: manual techniques based on our knowledge of the problem and the data, random sampling techniques that use coin flipping to keep or discard data, and model-based techniques that attempt to keep features that interact well with our learning model. Visually, the shape has relatively flat sides.

Testing 68

Testing Modeling Interactive Measurement 68

The Unofficial Google Data Science Blog

MARCH 31, 2016

Finally, through a case study of a real-world prediction problem, we also argue that Random Effect models should be considered alongside penalized GLM's even for pure prediction problems. Random effects models are a useful tool for both exploratory analyses and prediction problems. hi-fly-airlines 123.com

Modeling 40

Modeling Statistics Advertising Testing 40

Domino Data Lab

JULY 9, 2019

Diving into examples of building and deploying ML models at The New York Times including the descriptive topic modeling-oriented Readerscope (audience insights engine), a prediction model regarding who was likely to subscribe/cancel their subscription, as well as prescriptive example via recommendations of highly curated editorial content.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

IBM Big Data Hub

DECEMBER 20, 2023

Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences. In other words, ML leverages input data to predict outputs, continuously updating outputs as new data becomes available.

Machine Learning 77

Machine Learning Modeling Deep Learning Predictive Modeling 77

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] GloVe and word2vec differ in their underlying methodology: word2vec uses predictive models, while GloVe is count based. Human brains are not well suited to visualizing anything in greater than three dimensions. Example 11.6 Example 11.9

Deep Learning 111

Deep Learning Modeling Metrics Testing 111