AWS Big Data

MARCH 12, 2024

AWS Glue Data Quality reduces the effort required to validate data from days to hours, and provides computing recommendations, statistics, and insights about the resources required to run data validation. In this post, we provide benchmark results of running increasingly complex data quality rulesets over a predefined test dataset.

Data Quality 92

Data Quality Measurement Testing Visualization 92

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

datapine

MARCH 16, 2023

2) Pros & Cons Of Bar Charts 3) When To Use A Bar Graph 4) Types Of Bar Charts 5) Bar Graphs & Charts Best Practices 6) Bar Chart Examples In today’s fast-paced analytical landscape, data visualization has become one of the most powerful tools organizations can benefit from to be successful with their analytical efforts.

Visualization 196

Visualization KPI Cost-Benefit Dashboards 196

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 83

Data Science Data Analytics Prescriptive Analytics Analytics 83

AWS Big Data

APRIL 3, 2024

Many organizations already use AWS Glue Data Quality to define and enforce data quality rules on their data, validate data against predefined rules , track data quality metrics, and monitor data quality over time using artificial intelligence (AI). You can also visualize column-level data quality starting on the Schema tab.

Data Quality 91

Data Quality Visualization Metadata Metrics 91

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

Smarten

JUNE 29, 2018

This article discusses the Paired Sample T Test method of hypothesis testing and analysis. What is the Paired Sample T Test? The Paired Sample T Test is used to determine whether the mean of a dependent variable e.g., weight, anxiety level, salary, reaction time, etc., is the same in two related groups.

Business Analysis 40

Business Analysis Testing Statistics Advertising 40

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

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

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. It is possible to get good test and control groups (type of population, existing brand awareness, market penetration, competitive structures) for our experiments. Metrics are a problem.

Advertising 165

Advertising ROI Metrics Marketing 165

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

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

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.

Machine Learning 58

Machine Learning Data Science Statistics Deep Learning 58

FineReport

DECEMBER 9, 2021

Untracked metrics: data you will not track. This will be a subset of the metrics you track. This is a short project that validates the technical concept by proposing many simplified functions, verifying hypotheses, testing the functionality of the product, and ensuring that the concept can be implemented or vice versa.

Strategy 98

Strategy Business Intelligence KPI Key Performance Indicator 98

Octopai

OCTOBER 26, 2022

Continuous pipeline monitoring with SPC (statistical process control). SPC is the continuous testing of the results of automated manufacturing processes. products or product components) are checked to make sure that they do not deviate in a statistically significant way from the expected results. Results (i.e.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

O'Reilly on Data

DECEMBER 12, 2019

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. Because ML models can react in very surprising ways to data they’ve never seen before, it’s safest to test all of your ML models with sensitivity analysis. [9]

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

The Unofficial Google Data Science Blog

JANUARY 16, 2018

We present data from Google Cloud Platform (GCP) as an example of how we use A/B testing when users are connected. Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. Figure 4 is a visual representation of these steps.

Testing 58

Testing Experimentation Measurement Modeling 58

Smarten

NOVEMBER 8, 2022

By providing this course as a free online offering Smarten hopes to further support and encourage users and businesses to embrace the very real benefits of the Citizen Data Scientist approach to analytics and objective, data-driven metrics and results. About Smarten.

Business Intelligence 52

Business Intelligence Predictive Modeling Statistics Data-driven 52

DataRobot

APRIL 20, 2021

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. Use Multiple Tools and Visualizations. When you have the data in hand, assess its quality.

Measurement 52

Measurement Visualization Advertising Metrics 52

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. His name was William Gosset and he is credited to have developed the student t-test. Visual Analytics and Data Visualization.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

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

" ~ 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 124

KPI Metrics Measurement ROI 124

Juice Analytics

MARCH 30, 2021

The answer is not simply a better dashboard or more carefully designed data visualizations. Data authors need to be comfortable with core statistical concepts and comfortable with manipulating data. Data only becomes valuable when you start to get insights from it and apply those insights to actions.

Cost-Benefit 131

Cost-Benefit Statistics Metrics Dashboards 131

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. Once all packages have been imported, we can move on to loading our test data. We can now pass the preprocessed data to the Pumas NCAReport function, which calculates a wide range of relevant NCA metrics.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

Birst BI

AUGUST 23, 2018

Data scientists building AI applications require numerous skills – data visualization, data cleansing, artificial intelligence algorithm selection and diagnostics. Develop and test a model in R Studio. Use Birst Pronto to implement the model by creating an R transform step that creates a new metric.

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

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. 3) What Are KPI Best Practices?

KPI 221

KPI Management Key Performance Indicator Measurement 221

AWS Big Data

FEBRUARY 6, 2023

In this post, we dive deep into the tool, walking through all steps from log ingestion, transformation, visualization, and architecture design to calculate TCO. With QuickSight, you can visualize YARN log data and conduct analysis against the datasets generated by pre-built dashboard templates and a widget.

Dashboards 76

Dashboards Optimization Data Lake Cost-Benefit 76

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. Technical Look at your distributions While we typically use summary metrics (means, median, standard deviation, etc.) more than value Y, does it matter?”

Metrics 107

Metrics Measurement Statistics Data Collection 107

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. To generate accurate probabilities of future behavior, predictive analytics combine historical data from any number of applications with statistical algorithms.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Smarten

NOVEMBER 22, 2017

These tools allow the enterprise to establish and monitor key metrics and to objectively assess results. Your business users can perform advanced analytics, using sophisticated tools in an easy-to-use, drag and drop interface, with no advanced skill requirement for statistical analysis, algorithms or technical knowledge.

Analytics 40

Analytics IT Business Intelligence Visualization 40

Cloudera

JUNE 28, 2022

A dashboard feeds from the Kudu database to show fraud summary statistics. The path that the data takes in a NiFi flow is determined by visual connections between the different processors. In this blog we showed how Cloudera DataFlow makes it easy to create, test, and deploy data pipelines in the cloud.

Dashboards 81

Dashboards Machine Learning Statistics KPI 81

IBM Big Data Hub

AUGUST 11, 2023

Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. These insights can help drive decisions in business, and advance the design and testing of applications. MLOps and IBM Watsonx.ai

Data Science 57

Data Science Machine Learning Cost-Benefit Deep Learning 57

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. The Data Science Toolkit.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

Occam's Razor

OCTOBER 31, 2011

It artificially inflates the importance of a change in the metric might not be all that important. In this case for my data it is not statistically significant (more on that later in this post), but there is no way you would know that (or not know that) just from the data in front of you. Statistical Significance is Your BFF.

Statistics 130

Statistics Testing Reporting Key Performance Indicator 130

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

DataKitchen

MAY 10, 2021

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. Below we will explain how to virtually eliminate data errors using DataOps automation and the simple building blocks of data and analytics testing and monitoring. .

Testing 214

Testing Manufacturing Data Quality Statistics 214