AWS Big Data

JANUARY 15, 2025

In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications. This approach supports both the immediate needs of visualization tools such as Tableau and the long-term demands of digital twin and IoT data analytics.

IoT 101

IoT Machine Learning Metadata Data-driven 101

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Darkhorse

NOVEMBER 8, 2016

There is a near infinite variety of visualization methods within our field. FlowingData has given us 9 ways to visualize proportions and 11 ways for changes over time. Jittered strip plots in all their glory: Orchard visualizes loan principal amounts Andy Cotgreave’s Chart of Biology Aware looks at personal productivity Bee Swarm Plot.

Visualization 71

Visualization Experimentation Measurement Statistics 71

datapine

JANUARY 31, 2022

BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. They’re about having the mindset of an experimenter and being willing to let data guide a company’s decision-making process. What Are The Benefits of Business Intelligence?

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

DataRobot Blog

JANUARY 10, 2023

Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. This flexibility allows you to import your local code into the DataRobot platform and continue further experimentation using the combination of DataRobot Notebooks with: Deep integrations with DataRobot comprehensive APIs.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

FineReport

APRIL 24, 2024

Learn Data Visualization Understanding the Importance of Visualizing Data Data visualization is a powerful tool for conveying complex information in a clear and impactful manner. Whether it’s through charts, graphs, maps, or other visual formats, mastering data visualization is crucial for anyone working with data.

Visualization 52

Visualization Dashboards Interactive Data-driven 52

Smart Data Collective

JULY 9, 2023

Understanding E-commerce Conversion Rates There are a number of metrics that data-driven e-commerce companies need to focus on. It is a crucial metric that provides priceless information about your website’s ability to transform visitors into paying customers. Some of the most important is conversion rates.

Optimization 97

Optimization Data Analytics Analytics Data-driven 97

AWS Big Data

AUGUST 21, 2023

It similarly codes the query as a vector and then uses a distance metric to find nearby vectors in the multi-dimensional space. We’ll compare searching for visual similarity (on the left) and textual similarity (on the right). The algorithm for finding nearby vectors is called kNN (k Nearest Neighbors).

Data Processing 96

Data Processing Visualization Experimentation Metrics 96

Occam's Razor

AUGUST 12, 2013

Combine that with the excellent multi-channel conversion visualize (in the Overview section) and you have yourself a view of your marketing that will freak you out. You can visualize the impact of applying three models at one time. Then Experimentation. There is a free tool inside Google Analytics called Model Comparison Tool.

Modeling 162

Modeling Optimization Marketing Interactive 162

DataKitchen

JANUARY 17, 2022

The business analysts creating analytics use the process hub to calculate metrics, segment/filter lists, perform predictive modeling, “what if” analysis and other experimentation. Visualizations updated per week increased from 50 to 1500. Requirements continually change. Data is not static.

Experimentation 130

Experimentation Data Lake Predictive Modeling Marketing 130

Occam's Razor

JANUARY 7, 2014

7: 25% of all analytical effort is dedicated to data visualization/enhancing data's communicative power. #6: They are generic mash-ups that tailor to almost no one's needs, and more often than not contain awful things like nine not-really-thought out metrics for one dimension in a report. " Kisses. Angels singing!

Data-driven 142

Data-driven Consulting Reporting Marketing 142

DataRobot Blog

OCTOBER 18, 2022

Model Observability – the ability to track key health and service metrics for models in production – remains a top priority for AI-enabled organizations. We dug into interactive visualizations such as the DataRobot drift drill down plot , where users can investigate the exact feature and time period affected by data drift in a model.

Big Data 96

Big Data Forecasting Experimentation Machine Learning 96

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. Another pattern that I’ve seen in good PMs is that they’re very metric-driven.

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

MARCH 5, 2024

Many other platforms, such as Coveo’s Relative Generative Answering , Quickbase AI , and LaunchDarkly’s Product Experimentation , have embedded virtual assistant capabilities but don’t brand them copilots. As copilot technology capabilities are changing rapidly, leaders should frequently identify metrics and evaluate strategies.

Advertising 124

Advertising Cost-Benefit Experimentation Reporting 124

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 95

Analytics Metrics Strategy Measurement 95

CIO Business Intelligence

NOVEMBER 21, 2023

Develop citizen data science and self-service capabilities CIOs have embraced citizen data science because data visualization tools and other self-service business intelligence platforms are easy for business people to use and reduce the reporting and querying work IT departments used to support.

IT 137

IT Risk Cost-Benefit Data Science 137

DataKitchen

OCTOBER 5, 2021

DataOps enables: Rapid experimentation and innovation for the fastest delivery of new insights to customers. The data analyst’s products are charts, graphs and visualizations. The bottom line metrics that DataOps impacts are deployment latency and errors (figure 6). What is DataOps. Low error rates. Their product is the data.

Testing 152

Testing Dashboards Measurement Experimentation 152

AWS Big Data

JANUARY 9, 2024

Now users seek methods that allow them to get even more relevant results through semantic understanding or even search through image visual similarities instead of textual search of metadata. It similarly codes the query as a vector and then uses a distance metric to find nearby vectors in the multi-dimensional space to find matches.

Visualization 107

Visualization Cost-Benefit Modeling Machine Learning 107

CIO Business Intelligence

AUGUST 21, 2024

Our goal is to analyze logs and metrics, connecting them with the source code to gain insights into code fixes, vulnerabilities, performance issues, and security concerns,” he says. But multiagent AI systems are still in the experimental stages, or used in very limited ways.

Risk 136

Risk Insurance Cost-Benefit Software 136

Cloudera

APRIL 9, 2021

The third video in the series highlighted Reporting and Data Visualization. To effectively leverage their predictive capabilities and maximize time-to-value these companies need an ML infrastructure that allows them to quickly move models from data pipelines, to experimentation and into the business. Schedule ML Jobs.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

DataRobot

JUNE 10, 2021

Traditionally, experimentation and observation was the only way to understand the physical-chemical properties of the molecule. DataRobot also provides per-label metrics so that metrics per class can be compared. Below are the per-label metrics provided by DataRobot for model evaluation purposes.

Metrics 52

Metrics Machine Learning Visualization Experimentation 52

Domino Data Lab

JUNE 10, 2020

Domino connects with technologies spanning the end-to-end data science management lifecycle, from data prep and cleansing through model visualization and utilization, for a holistic, best-in-class solution to data science. In Domino 4.2

Data Science 82

Data Science Enterprise Experimentation Modeling 82

Sisense

MAY 18, 2021

When you discover data that means something, you need to be agile enough to make experimental changes.”. Mistake #2: Choosing the wrong data visualization to present your data. Data visualizations are graphic representations of data. We must first know the data to find the visualization that fits.”.

Marketing 52

Marketing Data Analytics Analytics Metrics 52

The Unofficial Google Data Science Blog

JANUARY 16, 2018

Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. However, the downside of using a larger unit of randomization is that we lose experimental power. Figure 4 is a visual representation of these steps. Assume we have $K$ users.

Testing 59

Testing Experimentation Measurement Modeling 59

DataRobot Blog

SEPTEMBER 30, 2022

By tracking service, drift, prediction data, training data, and custom metrics, you can keep your models and predictions relevant in a fast-changing world. Adoption of AI/ML is maturing from experimentation to deployment. Visualize Data Drift Over Time to Maintain Model Integrity. Model Observability can help. Drift Over Time.

Slice and Dice 52

Slice and Dice Modeling Metrics Experimentation 52

Domino Data Lab

DECEMBER 4, 2020

Having calculated AUC/AUMC, we can further derive a number of useful metrics like: Total clearance of the drug from plasma. Domino Lab supports both interactive and batch experimentation with all popular IDEs and notebooks (Jupyter, RStudio, SAS, Zeppelin, etc.). The area under the first moment curve would respectively be.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

Domino Data Lab

AUGUST 22, 2019

Human brains are not well suited to visualizing anything in greater than three dimensions. Visualizing data using t-SNE. We like the ROC AUC for two reasons: It blends together two useful metrics—true positive rate and false positive rate—into a single summary value. we do not need to consider all of the dimensions. Example 11.9

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

DataRobot

JUNE 23, 2021

After adding the preferred code, teams can take advantage of the existing DataRobot capabilities, such as metrics, explainability, visualizations, deployment, monitoring, collaboration, and governance. In data science , the best results come through experimentation. So let’s dig in!

Machine Learning 52

Machine Learning Visualization Experimentation Modeling 52

The Unofficial Google Data Science Blog

MARCH 22, 2018

But what if users don't immediately uptake the new experimental version? Background At Google, experimentation is an invaluable tool for making decisions and inference about new products and features. by DANIEL PERCIVAL Randomized experiments are invaluable in making product decisions, including on mobile apps.

Experimentation 62

Experimentation Measurement Modeling Statistics 62

Octopai

OCTOBER 26, 2022

When DataOps principles are implemented within an organization, you see an increase in collaboration, experimentation, deployment speed and data quality. Continuous DataOps metrics testing checks data’s validity, completeness and integrity at input and output. What DataOps best practices put you on track to achieving this ideal?

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

AWS Big Data

NOVEMBER 14, 2023

With a combination of low-latency data streaming and analytics, they are able to understand and personalize the user experience via a seamlessly integrated, self-reliant system for experimentation and automated feedback. Canva is an online design and visual communication platform.

IoT 59

IoT Data-driven Data Lake Data Strategy 59

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

It is important to make clear distinctions among each of these, and to advance the state of knowledge through concerted observation, modeling and experimentation. Another concern is that the Google results page sometimes contains visual elements, such as images, that may create sharp changes in user attention.

Slice and Dice 46

Slice and Dice Experimentation Data-driven Data Science 46

O'Reilly on Data

APRIL 19, 2021

We’ll look at this later, but being able to reproduce experimental results is critical to any science, and it’s a well-known problem in AI. When asked which tools they planned to incorporate over the coming 12 months, roughly half of the respondents answered model monitoring (57%) and model visualization (49%). Maturity by Continent.

Enterprise 364

Enterprise Risk Modeling Manufacturing 364

Occam's Razor

OCTOBER 23, 2006

Start with measuring these Outcomes metrics (revenue, leads, profit margins, improved product mix, number of new customers etc). Get competitive data (we are at x% of zz metric and our competition is at x+9% of zz metric). Great for a couple months and then you lose the audience. 6 Reporting is not Analysis. Your Choice? .

Data-driven 118

Data-driven Metrics KPI Reporting 118

Occam's Razor

AUGUST 22, 2011

" ~ Web Metrics: "What is a KPI? " + Standard Metrics Revisited Series. "Engagement" Is Not A Metric, It's An Excuse. Defining a "Master Metric", + a Framework to Gain a Competitive Advantage in Web Analytics. Six Data Visualizations That Rock! How do I choose well?

KPI 125

KPI Metrics Measurement ROI 125

Occam's Razor

OCTOBER 19, 2010

Mongoose Metrics ~ ifbyphone. I know Mongoose Metrics a bit more and have been impressed with their solution and evolution over the last couple of years. Experimentation and Testing Tools [The "Why" – Part 1]. Twitter to me is a proxy of how data collection is changing and what the future of relevant metrics might look like.

Analytics 136

Analytics Testing Measurement Optimization 136

Domino Data Lab

MAY 8, 2019

On the other hand, as Lipton emphasized, while the tooling produces interesting visualizations, visualizations do not imply interpretation. ML model interpretability and data visualization. From my experiences leading data teams, when a business is facing difficult challenges, data visualizations can help or hurt.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105