DataRobot Blog

SEPTEMBER 1, 2022

This also shows how the models compare on standard performance metrics and informative visualizations like Dual Lift. With DataRobot AI Cloud, you can see predicted values and accuracy for various metrics for the Champion as well as any Challenger models.]. Model Observability with Custom Metrics.

Metrics 145

Metrics Statistics Modeling Data Science 145

datapine

JULY 17, 2019

Typically presented in the form of an interactive dashboard , this kind of report provides a visual representation of the data associated with your predetermined set of key performance indicators – or KPI data, for short. Set up a report which you can visualize with an online dashboard. Consider your data sources. 2) Select your KPIs.

KPI 223

KPI Reporting Key Performance Indicator Dashboards 223

datapine

JANUARY 6, 2022

Through the art of streamlined visual communication, data dashboards permit businesses to engage in real-time and informed decision-making and are key instruments in data interpretation. More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. agree, strongly agree, disagree, etc.).

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

DataKitchen

NOVEMBER 18, 2022

Logs and storage for problem diagnosis and visualization of historical trends. In addition to the tracking of relationships and quality metrics, DataOps Observability journeys allow users to establish baselines? DataOps Observability must also store run data over time for root cause diagnosis and statistical process control analysis.

Testing 130

Testing Statistics Measurement Metrics 130

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

AWS Big Data

JUNE 6, 2023

They have to gather detailed data statistics, such as minimums, maximums, averages, and correlations. They have to then review the data statistics to identify data quality rules, and write code to implement these checks in their data pipelines. This reduces manual data analysis and rule identification efforts from days to hours.

Data Quality 95

Data Quality Statistics Data Lake Visualization 95

datapine

NOVEMBER 5, 2019

By harnessing the insights, information, and metrics that are most valuable to key aspects of your business and understanding how to take meaningful actions from your data, you will ensure your business remains robust, resilient, and competitive. The Link Between Data And Business Performance. What Is A Performance Dashboard In Business?

Dashboards 220

Dashboards Cost-Benefit Sales Metrics 220

Occam's Razor

SEPTEMBER 24, 2012

FBe's recommendation was (paraphrasing a 35 min talk): Don't invent new metrics, use online versions of Reach and GRPs to measure success. This blog post is about the above recommendations, and their merit. Attending this presentation inspired me to write this blog post. Metrics are a problem. and AdWords ads.

Advertising 165

Advertising ROI Metrics Marketing 165

datapine

MARCH 19, 2019

According to the statistics portal Statista , there are currently around 4.78 Here, we will consider what a mobile dashboard is, the dashboard mobile design, making visualizations on mobile, and real business examples to explain the benefits this most flexible of data-driven technology can offer your business.

Dashboards 112

Dashboards Visualization Metrics KPI 112

Sisense

SEPTEMBER 3, 2020

Besides strong technical skills (for instance, use of Hadoop, programming in R and Python , math, statistics), data scientists should also be able to tackle open-ended questions and undirected research in ways that bring measurable business benefits to their organization. We live in a constantly-evolving world of data.

Statistics 97

Statistics Metrics Visualization Finance 97

datapine

APRIL 2, 2019

Tracking the success metrics based on your needs, and the time frame you select while comparing your values can be done with simple yet effective scorecards. A KPI scorecard is a term used to describe a statistical record that measures progress or achievement towards a set performance indicator. Let’s see this through a visual example.

Scorecard 226

Scorecard KPI Dashboards Reporting 226

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

Ontotext

JUNE 22, 2023

Recent statistics shed light on the realities in the world of current drug development: out of about 10,000 compounds that undergo clinical research, only 1 emerges successfully as an approved drug. The current process involves costly wet lab experiments, which are often performed multiple times to achieve statistically significant results.

Metrics 52

Metrics Statistics Visualization Metadata 52

IBM Big Data Hub

DECEMBER 19, 2023

Anomaly detection simply means defining “normal” patterns and metrics—based on business functions and goals—and identifying data points that fall outside of an operation’s normal behavior. Regression modeling is a statistical tool used to find the relationship between labeled data and variable data.

Machine Learning 64

Machine Learning Optimization Unstructured Data Sales 64

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. appeared first on IBM Blog.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Cloudera

JULY 18, 2022

In part 1 of this blog we discussed how Cloudera DataFlow for the Public Cloud (CDF-PC), the universal data distribution service powered by Apache NiFi, can make it easy to acquire data from wherever it originates and move it efficiently to make it available to other applications in a streaming fashion. Use case recap. Apache Flink.

Analytics 91

Analytics Dashboards Statistics Visualization 91

BizAcuity

MAY 16, 2022

Fast food companies like Domino’s, McDonald’s and KFC collect massive amounts of data which includes customer data and other key business metrics for their own operations. Visual Analytics employs data mining to identify patterns and trends which would have been incredibly difficult to find without it. That was in the 1900’s.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Alation

AUGUST 18, 2022

In this blog, I am drilling into something I’ve been thinking about and studying for a long time: fundamental approaches to lineage creation and maintenance. For the purposes of this blog, it means the process of understanding how and why things are related. This may be a red herring, which I’ll address in a future blog!).

Metadata 69

Metadata Visualization Statistics Data Architecture 69

Sisense

APRIL 10, 2020

R is a tool built by statisticians mainly for mathematics, statistics, research, and data analysis. It’s quite popular for its visualizations: charts, graphs, pictures, and various plots. These visualizations are useful for helping people visualize and understand trends , outliers, and patterns in data.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

DataRobot Blog

MAY 26, 2022

These methods provided the benefit of being supported by rich literature on the relevant statistical tests to confirm the model’s validity—if a validator wanted to confirm that the input predictors of a regression model were indeed relevant to the response, they need only to construct a hypothesis test to validate the input.

Risk 52

Risk Modeling Metrics Business Objectives 52

AWS Big Data

MAY 16, 2023

This blog post is co-written with Steve Alexander at PG&E. Amazon Athena runs queries using a variety of SQL statements on data stored in Amazon S3, and QuickSight is used for business intelligence and data visualization. Smart Sensor Status By Location – This pane shows the geographical distributions of all the smart sensors.

Dashboards 78

Dashboards Statistics Data Collection Business Intelligence 78

DataRobot

APRIL 20, 2021

This is the first in a series of three blog posts that shares our perspective on AI you can trust. This includes the basics: Computing summary statistics on each feature Measuring associations between features Observing feature distributions and their correlation with the predictive target Identifying outliers.

Measurement 52

Measurement Visualization Advertising Metrics 52

datapine

MAY 14, 2019

We gave you a curated list of our top 15 data analytics books , top 18 data visualization books , top 16 SQL books – and, as promised, we’re going to tell you all about the world’s best books on data science. 8) “Storytelling With Data: A Data Visualization Guide for Business Professionals” by Cole Nussbaumer Knaflic.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

datapine

NOVEMBER 15, 2022

1) What Are Product Metrics? 2) Types Of Product Metrics. 3) Product Metrics Examples You Can Use. 4) Product Metrics Framework. The right product performance metrics will give you invaluable insights into its health, strength and weaknesses, potential issues or bottlenecks, and let you improve it greatly.

Metrics 141

Metrics KPI Measurement Dashboards 141

Occam's Razor

AUGUST 22, 2011

Here you'll find all my blog posts categorized into a structure that will hopefully make it easy for you to discover new content, find answers to your questions, or simply wallow in some excellent analytics narratives. " ~ Web Metrics: "What is a KPI? " + Standard Metrics Revisited Series. How to focus?"

KPI 124

KPI Metrics Measurement ROI 124

Cloudera

JUNE 28, 2022

In a previous blog of this series, Turning Streams Into Data Products , we talked about the increased need for reducing the latency between data generation/ingestion and producing analytical results and insights from this data. This blog will be published in two parts. This is what we call the first-mile problem.

Dashboards 85

Dashboards Machine Learning Statistics KPI 85

Cloudera

FEBRUARY 25, 2021

They need strong data exploration and visualization skills, as well as sufficient data engineering chops to fix the gaps they find in their initial study. The project launches an interactive visualization for exploring the quality of representations extracted using multiple model architectures. Deep Learning for Image Analysis.

Deep Learning 84

Deep Learning Machine Learning Forecasting Visualization 84

datapine

FEBRUARY 9, 2024

4) How to Select Your KPIs 5) Avoid These KPI Mistakes 6) How To Choose A KPI Management Solution 7) KPI Management Examples Fact: 100% of statistics strategically placed at the top of blog posts are a direct result of people studying the dynamics of Key Performance Indicators, or KPIs. What happens next?

KPI 221

KPI Management Key Performance Indicator Measurement 221

The Unofficial Google Data Science Blog

OCTOBER 31, 2016

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. I'd like to share the contents of that document in this blog post. By PATRICK RILEY For a number of years, I led the data science team for Google Search logs.

Metrics 107

Metrics Measurement Statistics Data Collection 107

IBM Big Data Hub

AUGUST 7, 2023

AI algorithms have the potential to surpass traditional statistical approaches for analyzing comprehensive recruitment data and accurately forecasting enrollment rates. It can be integrated into real-time dashboards, visualizations, and reports that provide stakeholders with a comprehensive and up-to-date insight into site performance.

Optimization 55

Optimization Forecasting Data-driven Strategy 55

Occam's Razor

JULY 24, 2018

work (collection, processing, reporting, analysis), processes, org structure, governance models, last-mile gaps , metrics ladders of awesomeness , and… so… much… more. Remember, tools, work, processes, org structure, governance models, last-mile gaps, metrics ladders of awesomeness, and… so… much… more. The Implications of Complexity.

Analytics 93

Analytics Metrics Strategy Measurement 93

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. For your business to thrive, you need to know what’s working, what’s not, and how to improve. That much is obvious.

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

Jen Stirrup

JUNE 20, 2020

My analysis is based on the Financial statements put forward by PASS using some basic metrics; until you do that piece, you can’t move forward to compare and contrast it with other data since you have not done your ‘descriptive statistical analysis’ first to ensure that the comparison is valid. What does that say about the #SQLFamily?

Metrics 104

Metrics Business Analytics Data-driven Statistics 104

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. Data science is an interdisciplinary field within STEM that combines math and statistics, computer science, and business acumen to find patterns in complex datasets that can be used to improve decision making.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

datapine

SEPTEMBER 16, 2022

But often that’s how we present statistics: we just show the notes, we don’t play the music.” – Hans Rosling, Swedish statistician. Data visualization, or ‘data viz’ as it’s commonly known, is the graphic presentation of data. That’s a colossal number of books on visualization. Data visualization: What You Need To Know.

Visualization 304

Visualization Dashboards Data-driven Statistics 304

Sisense

SEPTEMBER 25, 2020

A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. No matter your skill, career level, or title, the ability to analyze, organize, and visualize data are vital skills in our world of quickly growing and ever-changing data. Statistics and programming go hand in hand.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98

datapine

MARCH 25, 2019

Data analysis method focuses on strategic approaches to taking raw data, mining for insights that are relevant to the business’s primary goals, and drilling down into this information to transform metrics, facts, and figures into initiatives that benefit improvement. Conduct statistical analysis. Visualize your data.

Key Performance Indicator 217

Key Performance Indicator Statistics Visualization Big Data 217