Paul Blogs on BI

MARCH 25, 2020

Firstly, let’s talk about the data and the metrics being used to track the pandemic. The three main metrics being tracked in this pandemic are: Confirmed Cases. As more testing becomes available this first metric will increase significantly. Total Deaths. Total recovered.

Business Intelligence 51

Business Intelligence Measurement Metrics Cost-Benefit 51

FineReport

APRIL 9, 2024

From advanced analytics to predictive modeling, the evolving landscape of business intelligence is revolutionizing how data is processed and leveraged for actionable insights. Proactive Risk Management : BI tools enable organizations to proactively identify potential risks through predictive modeling and trend analysis.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

IBM Big Data Hub

JUNE 29, 2023

First, availability measures the operational capacity of an asset over time. While reliability and availability are both measured in percentages, it’s possible—even likely—that these percentages will differ even when referring to the same piece of equipment. How does asset reliability work?

Cost-Benefit 85

Cost-Benefit Measurement Management Predictive Analytics 85

Smarten

NOVEMBER 22, 2019

Augmented analytics and tools like Smart Visualization and Self-Serve Data Preparation , as well as Assisted Predictive Modeling can provide guidance and auto-suggestions and recommendations to make users more comfortable in adopting analytics and achieving positive outcomes.

Predictive Modeling 67

Predictive Modeling Data-driven Forecasting Visualization 67

CIO Business Intelligence

MAY 26, 2022

Expectedly, advances in artificial intelligence (AI), machine learning (ML), and predictive modeling are giving enterprises – as well as small/medium-sized businesses – a never-before opportunity to automate their recruitment even as they deal with radical changes in workplace practices involving remote and hybrid work.

Advertising 128

Advertising Machine Learning Software Measurement 128

DataRobot Blog

JULY 28, 2022

Companies are emphasizing the accuracy of machine learning models while at the same time focusing on cost reduction, both of which are important. In addition to the accuracy of the models we built, we had to consider business metrics, cost, interpretability, and suitability for ongoing operations. Sensor Data Analysis Examples.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

CIO Business Intelligence

MAY 28, 2022

Expectedly, advances in artificial intelligence (AI), machine learning (ML), and predictive modeling are giving enterprises – as well as small/medium-sized businesses – a never-before opportunity to automate their recruitment even as they deal with radical changes in workplace practices involving remote and hybrid work.

Advertising 119

Advertising Machine Learning Software Measurement 119

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. Your marketing strategy is only as good as your ability to deliver measurable results. underspecified) due to omitted metrics.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. It helps you build, train, and deploy models consuming the data from repositories in the data hub.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

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

Alation

APRIL 25, 2023

Predictive models indicate that the machine learning market will grow at a compound annual growth rate (CAGR) of 38.8% But remember to set achievable and measurable goals along the way. If your infrastructure doesn’t measure up, consider upgrading or replacing it. between 2022 and 2029.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

DataKitchen

SEPTEMBER 21, 2023

Moreover, advanced metrics like Percentage Regional Sales Growth can provide nuanced insights into business performance. Data in Use pertains explicitly to how data is actively employed in business intelligence tools, predictive models, visualization platforms, and even during export or reverse ETL processes.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

Smarten

JUNE 29, 2018

For example, one might consider two groups of participants that are measured at two different “time points” or two groups that are subjected to two different “conditions” Paired T Test is used to evaluate the before and after of a situation, treatment, condition, etc. is the same in two related groups. About Smarten.

Business Analysis 40

Business Analysis Testing Statistics Advertising 40

FineReport

APRIL 9, 2024

Furthermore, maintaining data security and compliance requires continuous vigilance and proactive measures to safeguard against potential vulnerabilities. The integration of clinical data analysis tools empowers healthcare providers to leverage predictive analytics for proactive decision-making.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

Alation

APRIL 25, 2023

Predictive models indicate that the machine learning market will grow at a compound annual growth rate (CAGR) of 38.8% But remember to set achievable and measurable goals along the way. If your infrastructure doesn’t measure up, consider upgrading or replacing it. between 2022 and 2029.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

Decision Management Solutions

NOVEMBER 13, 2018

” They analyze the data available and try to see what analytic models it contains. Rather than begin with the data and try to “discover” what model is inside it, analytics teams should begin with a business problem – the decision they wish to improve – and use this to direct their work. Begin with decisions, not with data.

Insurance 40

Insurance Analytics Modeling Visualization 40

Smarten

DECEMBER 3, 2023

Users can replace guesswork and opinion with fact-based presentations and recommendations for more measurable analysis of trends, product pricing, financial investment, manufacturing and production and all other business factors.

Analytics 40

Analytics Cost-Benefit Data Quality Consulting 40

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

BizAcuity

MARCH 8, 2019

Workforce Analytics in simple terms can be defined as an advanced set of software and methodology tools that measures, characterizes, and organizes sophisticated employee data and these tools helps in understanding the employee performance in a logical way. Derives metrics for benchmark interpretation and trends.

Analytics 73

Analytics Prescriptive Analytics Cost-Benefit Metrics 73

AWS Big Data

NOVEMBER 14, 2023

With data streaming, you can power data lakes running on Amazon Simple Storage Service (Amazon S3), enrich customer experiences via personalization, improve operational efficiency with predictive maintenance of machinery in your factories, and achieve better insights with more accurate machine learning (ML) models.

IoT 55

IoT Data-driven Data Lake Data Strategy 55

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

Others argue that there will still be a unique role for the data scientist to deal with ambiguous objectives, messy data, and knowing the limits of any given model. 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.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Insight

FEBRUARY 19, 2020

Arthur de Vany’s Hollywood Economics and Kaggle’s recent box office prediction challenge ) and current attempts are using increasingly sophisticated techniques. Feature Selection and Engineering Most of the inputs to my model were taken either as is from the data source, or with minimal processing.

Risk 67

Risk ROI Modeling Metrics 67

Occam's Razor

JANUARY 7, 2019

Does swapping out male model posters for cute animals triple sales? Throw away your custom attribution model. From the tens of hours saved per week, figure out how to feed offline data into your data driven attribution model. There is too much goodness in modeling that you are not taking advantage of. How do you know?

Marketing Analytics 88

Marketing Analytics Marketing Analytics Strategy 88

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. This chapter will explore the numbers behind the numbers using ML and then creating an API to serve out the ML model. 05) in predicting changes in attendance. Phrasing the Problem. questions to ask. Gathering the Data.

Statistics 59

Statistics Machine Learning Testing Modeling 59

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

Smarten

MARCH 13, 2024

Augmented Analytics and Citizen Data Scientists are not meant to replace refined data modeling or the role of Data Scientists, but rather can supplement and support analytics across the enterprise. Nothing could be further from the truth. and then share and collaborate with the team to further analyze and discuss the issues.

Analytics 52

Analytics Predictive Modeling Strategy Enterprise 52

datapine

JANUARY 31, 2022

For example, in regards to marketing, traditional advertising methods of spending large amounts of money on TV, radio, and print ads without measuring ROI aren’t working like they used to. 5) Find improvement opportunities through predictions. Consumers have grown more and more immune to ads that aren’t targeted directly at them.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Smarten

JULY 31, 2019

How does one measure the effectiveness of a new Augmented Data Discovery solution? Once the business has chosen data democratization and implemented a self-serve analytics solution, it must measure ROI & TCO and establish metrics that will compare business results achieved before and after the implementation.

Predictive Modeling 40

Predictive Modeling Metrics Measurement ROI 40

datapine

NOVEMBER 27, 2019

While we work on programs to avoid such inconvenience , AI and machine learning are revolutionizing the way we interact with our analytics and data management while increment in security measures must be taken into account. Any difference between predicted data and real value is used by the moving average (MA) part.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

DECEMBER 3, 2023

It also augments the expert and citizen data scientists by automating many aspects of data science, machine learning, and AI model development, management and deployment.’ ‘You What is self-service analytics? We should probably explain before we move on.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

Alation

MAY 2, 2023

Data analytics techniques, such as machine learning (ML), artificial intelligence (AI), and predictive modeling, can help businesses extract valuable insights from this data to improve operations and customer experience. With this data, they can make informed changes to business models, operations, and offerings.

Data Analytics 52

Data Analytics Analytics ROI Data Governance 52

Alation

MAY 2, 2023

Data analytics techniques, such as machine learning (ML), artificial intelligence (AI), and predictive modeling, can help businesses extract valuable insights from this data to improve operations and customer experience. With this data, they can make informed changes to business models, operations, and offerings.

Data Analytics 40

Data Analytics Analytics ROI Data Governance 40

Jet Global

MAY 1, 2023

As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. Manage compliance through up-to-the-minute performance measures, workflow automation, and essential regulatory reports. Pricing model: The pricing scale is dependent on several factors.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52