IBM Big Data Hub

NOVEMBER 29, 2023

Creating synthetic test data to expedite testing, optimization and validation of new applications and features. In other words, a differentially private synthetic dataset still reflects the statistical properties of your real dataset.

Metrics 88

Metrics Machine Learning Risk Statistics 88

IBM Big Data Hub

APRIL 13, 2023

Creating train/test partitions of the dataset Before collecting deeper insights into the data, I’ll divide this dataset into train and test partitions using Db2’s RANDOM_SAMPLING SP. outtable=FLIGHT.FLIGHTS_TRAIN, by=FLIGHTSTATUS') Copy the remaining records to a test PARTITION. Create a TRAIN partition.

Modeling 90

Modeling Statistics Machine Learning Testing 90

AWS Big Data

MARCH 27, 2024

By testing the solution against key metrics, a POC provides insights that allow you to make an informed decision on the suitability of the technology for the intended use case. Complete the implementation tasks such as data ingestion and performance testing. Collect data metrics and statistics on the completed tasks.

Testing 98

Testing Data Warehouse Metrics Cost-Benefit 98

IBM Big Data Hub

DECEMBER 18, 2023

Does that imply that there are “fake” user metrics as well? Synthetic data is a statistical representation of reality. This delivers business value in several ways: It improves performance by choosing the fastest connection to a particular geography, the fastest available CDN, or other metrics you define.

IT 70

IT Metrics Optimization Testing 70

DataKitchen

JANUARY 19, 2022

Imagine a large enterprise yielding significant value from their Matillion-Snowflake integration, but wishing to expand the scope of data pipeline deployment, testing, and monitoring. DataKitchen triggers a Matillion job, then retrieves execution parameters that can be used in DataKitchen tests. Unifying Heterogeneous Toolchains.

Testing 130

Testing Data Integration Data Warehouse Enterprise 130

DataKitchen

JULY 3, 2023

This innovative approach merges the agility of Agile Development, the stability of DevOps, and the meticulousness of Statistical Process Controls, orchestrating a dynamic, enriched, and nimble data ecosystem that is truly remarkable. They need help creating data tests and observing the entire Data Journey for success.

Testing 130

Testing Risk Data-driven Statistics 130

IBM Big Data Hub

MAY 17, 2024

” Given the statistics—82% of surveyed respondents in a 2023 Statista study cited managing cloud spend as a significant challenge—it’s a legitimate concern. With this organizational change, new teams are being defined, agile project groups created and feedback and testing loops established. Why move to cloud?

Modeling 82

Modeling Cost-Benefit Optimization Digital Transformation 82

IBM Big Data Hub

AUGUST 9, 2023

A phishing simulation is a cybersecurity exercise that tests an organization’s ability to recognize and respond to a phishing attack. After the simulation, organizations also receive metrics on employee click rates and often follow up with additional phishing awareness training. million phishing sites.

Testing 80

Testing Measurement Behavioral Analytics Reporting 80

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.

Advertising 165

Advertising ROI Metrics Marketing 165

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. For example, business analysts can use BI dashboards to conduct in-depth business analytics and visualize key performance metrics compiled from relevant datasets.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

datapine

JANUARY 6, 2022

More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. Let’s quickly review the most common statistical terms: Mean: a mean represents a numerical average for a set of responses. Standard deviation: this is another statistical term commonly appearing in quantitative analysis.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

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

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. These contribute to the structure and size of components.

Testing 58

Testing Experimentation Measurement Modeling 58

Cloudera

DECEMBER 3, 2021

In part 1 of this blog post, we discussed the need to be mindful of data bias and the resulting consequences when certain parameters are skewed. There are a number of metrics that can be used to measure the performance of a system; they include accuracy, precision and F-score to name only three. Model Drift. The post In AI we trust?

Uncertainty 98

Uncertainty Measurement Metrics Risk 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

datapine

MARCH 19, 2019

According to the statistics portal Statista , there are currently around 4.78 It offers ease of access through mobile devices, on the go, with critical metrics displayed at-a-glance. You should hold internal focus groups to test how ‘scannable’ your dashboard designs are and find out which areas need improvement.

Dashboards 112

Dashboards Visualization Metrics KPI 112

Sisense

JANUARY 21, 2020

One of the simplest ways to start exploring your data is to aggregate the metrics you are interested in by their relevant dimensions. This is an example of Simpon’s paradox , a statistical phenomenon in which a trend that is present when data is put into groups reverses or disappears when the data is combined.

Testing 104

Testing Risk Data-driven Statistics 104

datapine

MARCH 16, 2023

For that purpose, we are creating a series of blog posts that will take an in-depth look at the most common types of graphs and charts out there and explore their main uses through insightful business examples. Your Chance: Want to test modern data visualization software for free? We will discuss each of them below.

Visualization 196

Visualization KPI Cost-Benefit Dashboards 196

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 59

Machine Learning Data Science Statistics Deep Learning 59

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

datapine

JULY 17, 2019

Picture procurement metrics – you need to know if suppliers fulfill your demands, their capacity to respond to urgent demands, costs of orders, and many other indicators to efficiently track your company’s performance. Quick Ratio / Acid Test. This will form the foundations of your ultimate KPI reporting success.

KPI 223

KPI Reporting Key Performance Indicator Dashboards 223

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 81

Dashboards Machine Learning Statistics KPI 81

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

Domino Data Lab

JULY 17, 2021

While more advanced models for speaker verification exist, this blog will form a basis of speech signal processing. NOTE : The scope of this blog is a machine learning approach to TISV. The likelihood function measures the goodness of fit of a statistical model to a sample of data for given values of the unknown parameters.

Modeling 64

Modeling Testing Machine Learning Measurement 64

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 Are KPI Best Practices?

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

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature. Among these, only statistical uncertainty has formal recognition.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

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

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. Because individual observations have so little information, statistical significance remains important to assess.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

Occam's Razor

FEBRUARY 7, 2022

Since you're reading a blog on advanced analytics, I'm going to assume that you have been exposed to the magical and amazing awesomeness of experimentation and testing. Insights worth testing. This blog post was originally published as an edition of my newsletter TMAI Premium. You can test landing pages.

Experimentation 101

Experimentation Testing Optimization Marketing 101

Occam's Razor

MAY 22, 2006

This post is a primer on the delightful world of testing and experimentation (A/B, Multivariate, and a new term from me: Experience Testing). Experimentation and testing help us figure out we are wrong, quickly and repeatedly and if you think about it that is a great thing for our customers, and for our employers.

Experimentation 103

Experimentation Testing Optimization Measurement 103

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. Do let us know if you found the blog useful in the comments.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

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.

Data Science 57

Data Science Machine Learning Cost-Benefit Deep Learning 57

Occam's Razor

OCTOBER 31, 2011

Creating graphs is easy, and I could fill five blog posts with all the nonsense one can accomplish by playing with the axes. It artificially inflates the importance of a change in the metric might not be all that important. Statistical Significance is Your BFF. Yes it is a pet peeve of mine. Look at it carefully? Download it.

Statistics 130

Statistics Testing Reporting Key Performance Indicator 130

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

CDW Research Hub

AUGUST 19, 2019

Will it include a readout summary of volumes of orders and customers, distilled application monitoring metrics, review and signoff of marketing content? This requires coordination across multiple teams to get all of these applied and tested within the various environments, so don’t leave it to the last minute.

Testing 49

Testing Optimization Data Processing Strategy 49