Juice Analytics

MARCH 11, 2021

3) That’s where our data visualization and user experience capabilities helped them turn this data into a web-based analytical tool that focused users on the metrics and peer groups they cared about. There are many paths to consider: Visual representations that reveal patterns in the data and make it more human readable.

Predictive Modeling 128

Predictive Modeling Visualization Reporting Interactive 128

FineReport

APRIL 9, 2024

Through the utilization of predictive models, clinicians can forecast patient outcomes and resource needs, enabling early intervention and personalized care delivery. Maximizing the impact on patient care involves harnessing healthcare data visualization tools to present these personalized insights in a comprehensible manner.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

Birst BI

JANUARY 16, 2018

But to build that dashboard, someone has to assemble all the components, the key performance indicators (KPIs), the data visualizations, and all of the dashboard’s data feeds. The BI system can discover business-critical relationships in the data and automatically build visualizations and dashboards.

Data-driven 70

Data-driven Analytics Dashboards Machine Learning 70

Birst BI

OCTOBER 30, 2018

Descriptive analytics techniques are often used to summarize important business metrics such as account balance growth, average claim amount and year-over-year trade volumes. The credit scores generated by the predictive model are then used to approve or deny credit cards or loans to customers. Accounts in use.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

AWS Big Data

MARCH 7, 2023

It enables you to create interactive dashboards, visualizations, and advanced analytics with ML insights. It helps you build, train, and deploy models consuming the data from repositories in the data hub. You can collect metrics and events and analyze them for operational efficiency.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

Domino Data Lab

JULY 28, 2021

In its current form , data science is limitless in terms of industry and application; the only requirement is data, compute power, data scientists, and a desire to become model-driven. These advances have had huge ramifications across industries ranging from finance and banking to healthcare and insurance. The Data Science Toolkit.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

datapine

OCTOBER 21, 2020

Now that we live longer, treatment models have changed and many of these changes are namely driven by data. By utilizing key performance indicators in healthcare and healthcare data analytics, prevention is better than cure, and managing to draw a comprehensive picture of a patient will let insurance provide a tailored package.

Big Data 364

Big Data Data Analytics Analytics Cost-Benefit 364

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. Doing anything on the web without a Web Analytics Measurement Model. Making lame metrics the measures of success: Impressions, Click-throughs, Page Views. " 22.

Marketing 126

Marketing Measurement Metrics Testing 126

DataRobot Blog

JULY 21, 2022

Data scientists need to understand the business problem and the project scope to assess feasibility, set expectations, define metrics, and design project blueprints. If there is no forward-looking predictive component to the use case, it can probably be addressed with analytics and visualizations applied to historical data.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

CIO Business Intelligence

AUGUST 15, 2023

Shamim Mohammad, CIO, CarMax CarMax That volume created a Sisyphean task for the company’s content writers, as they struggled to provide up-to-date information by make, model, and year for each vehicle in the company’s constantly changing inventory. And it yields multiple business metric improvements, such as limiting surplus inventory.

IT 98

IT Manufacturing IoT Cost-Benefit 98

Domino Data Lab

JULY 22, 2019

how “the business executives who are seeing the value of data science and being model-informed, they are the ones who are doubling down on their bets now, and they’re investing a lot more money.” He also really informed a lot of the early thinking about data visualization. Key highlights from the session include. Transcript.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

IBM Big Data Hub

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

Domino Data Lab

JUNE 2, 2019

We had data science leaders presenting about lessons learned while leading data science teams, covering key aspects including scalability, being model-driven, being model-informed, and how to shape the company culture effectively. Data science leadership: importance of being model-driven and model-informed.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110

Occam's Razor

JULY 15, 2014

It also handy explanations of the metrics, with key context where necessary. Allow me to visualize the problem above, and leverage that visualization to present the solution. As you might have guessed, you are at the very right of the above visual, with most access to data, the ability to analyze it ( inshallah! )

Dashboards 159

Dashboards Key Performance Indicator Snapshot Slice and Dice 159

Domino Data Lab

FEBRUARY 4, 2019

Lately there’s been lots of dialog about bias in machine learning models, though considering the noise part of the equation is an important corollary. I double-dare you not to visualize that cohort! Problems with training ML models efficiently. We’d love to hear your insights and perspectives about running data teams.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade. See Ribeiro et al.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Sisense

DECEMBER 11, 2019

He outlined how critical measurable results are to help VCs make major investment decisions — metrics such as revenue, net vs gross earnings, sales , costs and projections, and more. And he demonstrated how the Periscope Data platform overcomes the challenges of huge data volumes that can’t be easily modeled by traditional BI.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

Alation

AUGUST 26, 2021

These future-oriented models are used to make predictions. BI leverages and synthesizes data from analytics, data mining, and visualization tools to deliver quick snapshots of business health to key stakeholders, and empower those people to make better choices. Business Intelligence (BI) is explanatory and backward-looking.

Metadata 64

Metadata Data Governance Dashboards Software 64

Andrew White

JANUARY 11, 2021

As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. Try some gamification?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

APRIL 5, 2021

Enterprises actively use financial modeling to guide their financial planning and strategic decision-making. Financial models offer data-driven, quantitative analysis that tells you where your company stands and where it’s heading. That being said, one model can’t do it all. What Is Financial Modeling?

Modeling 98

Modeling Forecasting Metrics Finance 98

Domino Data Lab

SEPTEMBER 9, 2019

Typically, there are contracts (sales contracts, work agreements, partnerships), there are invoices, there are insurance policies, there are regulations and other laws, and so on. We have configured the default Compute Environment in Domino to include all of the packages, libraries, models, and data you’ll need for this tutorial.

Deep Learning 110

Deep Learning Machine Learning Visualization Data Science 110