IBM Big Data Hub

JULY 5, 2023

However, cloud services costs can be higher than anticipated, so monitoring and optimizing your cloud spend is critical. Cloud cost optimization combines strategies, techniques, best practices and tools to help reduce cloud costs, find the most cost-effective way to run your applications in the cloud environment, and maximize business value.

Optimization 71

Optimization Forecasting ROI Metrics 71

datapine

SEPTEMBER 29, 2022

6) Data Quality Metrics Examples. Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. These needs are then quantified into data models for acquisition and delivery. Table of Contents. 1) What Is Data Quality Management?

Data Quality 241

Data Quality Metrics Data-driven Management 241

Smart Data Collective

FEBRUARY 9, 2022

Luckily, there are a few analytics optimization strategies you can use to make life easy on your end. For instance, they display trend lines, pivot points, low volatility and other metrics in distinct colors. A powerful back-testing engine: It allows you to generate performance metrics for multiple stocks at the touch of a button.

Visualization 130

Visualization Optimization Analytics Testing 130

Cloudera

JULY 21, 2022

Cloudera has partnered with Rill Data, an expert in metrics at any scale, as Cloudera’s preferred ISV partner to provide technical expertise and support services for Apache Druid customers. Deploying metrics shouldn’t be so hard. Rill solves this with pipeline services and Rill Developer, a free SQL-based data modeler.

Metrics 82

Metrics Slice and Dice Data Warehouse Dashboards 82

Cloudera

NOVEMBER 29, 2023

That’s why we’re excited to announce the Cloudera Model Registry as generally available, a game-changer that’s set to transform the way you manage your machine learning models in production environments. That’s where the Model Registry steps in. That’s where the Model Registry steps in.

Modeling 82

Modeling Machine Learning Metadata Metrics 82

Smart Data Collective

SEPTEMBER 21, 2021

A growing number of businesses are starting to look for new data-driven approaches to streamline their business models. However, your data-driven business model won’t be very helpful if you don’t focus on the right metrics. Targeting the Right Variables for Your Data-Driven Retail Business Model.

Data-driven 106

Data-driven Metrics Sales Big Data 106

AWS Big Data

JUNE 27, 2023

Our previous solution offered visualization of key metrics, but point-in-time snapshots produced only in PDF format. In this post, we discuss how we built a solution using QuickSight that delivers real-time visibility of key metrics to public sector recruiters. We can pick what we need, and use what we need with pay-as-you-go pricing.

Metrics 97

Metrics Dashboards Interactive Visualization 97

Smart Data Collective

AUGUST 16, 2021

Crazy Egg, Google Analytics, Voluum and other analytics tools make it a lot easier to create a well-optimized and profitable business. Analytics data can be very useful for companies trying to create profitable online business models. This metric is the average number you have to put in to get new customers. Acquisition Costs.

Metrics 129

Metrics Analytics Cost-Benefit Sales 129

Smart Data Collective

AUGUST 17, 2021

Many companies have found that analytics technology is ideal for optimizing their business models in a number of ways. The best way to measure and analyze the growth of a business is to use business metrics. There are a lot of data analytics tools that track these metrics and help businesses make more informed decisions.

Measurement 121

Measurement Optimization Analytics Metrics 121

Smart Data Collective

APRIL 1, 2020

Big data is the lynchpin of the Software as a Service (SaaS) business model. Panoply, a big data innovator, has talked about a new model called Data as a Service, which is a variation of the same idea. Big data is used at every junction of the SaaS model. SaaS Model Relies on Big Data Innovation. So, are you ready?

Metrics 100

Metrics Big Data Machine Learning Optimization 100

IBM Big Data Hub

AUGUST 15, 2023

The scale serves as your trusted navigator, providing tangible metrics and keeping you on track. Similarly, comprehending the savings realized in a cloud-cost-optimization journey offers valuable insights into the impact of your efforts. It also captures the impact from optimizing popular PaaS services like Azure App Service.

Optimization 65

Optimization Measurement Cost-Benefit Dashboards 65

O'Reilly on Data

JULY 28, 2020

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 362

Marketing Experimentation Metrics Testing 362

MLWhiz

NOVEMBER 6, 2019

What do we want to optimize for? Every business problem is a little different, and it should be optimized differently. We all have created classification models. A lot of time we try to increase evaluate our models on accuracy. But do we really want accuracy as a metric of our model performance?

Metrics 86

Metrics Optimization Modeling IT 86

Jedox

JUNE 24, 2021

Typical metrics such as impressions, unique website visitors, raw and qualified leads, sales growth, sales target and target achievement, customer acquisition costs, customer churn rate, sales cycle length are among the ever-growing list of marketing metrics becoming commonly used. The evolution of marketing data.

Sales 94

Sales Marketing Optimization Metrics 94

IBM Big Data Hub

JULY 25, 2023

Smart grids turn this model on its head. Sensors and automation devices: These are installed throughout the grid to monitor voltage, current, and load capacity (among other metrics). This software, and the insights it provides, can help providers predict demand patterns, identify potential issues and optimize the distribution network.

Optimization 61

Optimization Technology Measurement Cost-Benefit 61

DataRobot

FEBRUARY 10, 2021

Even if all the code runs and the model seems to be spitting out reasonable answers, it’s possible for a model to encode fundamental data science mistakes that invalidate its results. These errors might seem small, but the effects can be disastrous when the model is used to make decisions in the real world.

Modeling 98

Modeling Deep Learning Machine Learning Testing 98

Decision Management Solutions

APRIL 22, 2020

In fact, they kicked off the project by saying that reducing fraud was the only metric that mattered to them – we just had to reduce the total value of fraudulent transactions. As we noted earlier , you can use models to define the relationships between the elements of your decision and your business results.

Optimization 66

Optimization Strategy Metrics Modeling 66

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. A machine learning model trained with labeled data will be able to detect outliers based on the examples it is given.

Machine Learning 72

Machine Learning Optimization Unstructured Data Sales 72

Smart Data Collective

SEPTEMBER 17, 2020

One of the most important benefits of data analytics with lead generation and optimization. Predictive analytics tools use a variety of scoring metrics to identify the probability that a lead will be converted into a paying customer. Monitor the Metrics. Big data is utilized in many facets of business.

Optimization 104

Optimization Data Analytics Analytics Sales 104

Decision Management Solutions

APRIL 8, 2020

Over the last few weeks we’ve blogged a couple of times on Decision Optimization. The Customer Journey to Decision Optimization. Instead of arguing about decision-making, you can model decision-making. You can develop what are called Decision Requirements Models using the Decision Model and Notation standard.

Modeling 72

Modeling Optimization Metrics Testing 72

CIO Business Intelligence

JANUARY 30, 2024

On the other hand, there are organizations with teams that are equipped with value-based plans and metrics. In this way, teams gain the ability to optimize value delivery and adapt more quickly. These digital operating models help enhance visibility, foster trust, and deliver tangible value.

Digital Transformation 140

Digital Transformation Metrics Enterprise Optimization 140

CIO Business Intelligence

APRIL 10, 2024

The company needs massive computing power with CPUs and GPUs that are optimized for AI development, says Clark, adding that Seekr looked at the infrastructure it would need to build and train its huge AI models and quickly determined that buying and maintaining the hardware would be prohibitively expensive. Clark says.

IT 119

IT Testing Optimization Modeling 119

Domino Data Lab

SEPTEMBER 3, 2019

This article covers how to perform hyperparameter optimization using a sequential model-based optimization (SMBO) technique implemented in the HyperOpt Python package. Feature engineering and hyperparameter optimization are two important model building steps. There is a complementary Domino project available.

Optimization 76

Optimization Dashboards Modeling Machine Learning 76

IBM Big Data Hub

AUGUST 7, 2023

Tackling complexities in clinical trial site selection: A playground for a new technology and AI operating model Enrollment strategists and site performance analysts are responsible for constructing and prioritizing robust end-to-end enrollment strategies tailored to specific trials. To do so they require data, which is in no shortage.

Optimization 60

Optimization Forecasting Data-driven Strategy 60

IBM Big Data Hub

APRIL 19, 2024

Sensoring and monitoring also contribute to the direct measurement of sustainability environmental, social and governance (ESG) metrics such as energy efficiency and greenhouse gas emission or wastewater flows. The introduction of (generative) AI models in the asset management domain has brought a full toolbox of new optimization tools.

Management 94

Management Internet of Things Risk IoT 94

DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States.

Risk 64

Risk Modeling Machine Learning Data Quality 64

O'Reilly on Data

JUNE 15, 2023

The world changed on November 30, 2022 as surely as it did on August 12, 1908 when the first Model T left the Ford assembly line. If we want prosocial outcomes, we need to design and report on the metrics that explicitly aim for those outcomes and measure the extent to which they have been achieved.

Metrics 285

Metrics Reporting Measurement Finance 285

Occam's Razor

APRIL 8, 2013

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. This should not be news to you. But it is not routine.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Rocket-Powered Data Science

DECEMBER 16, 2018

In a related post we discussed the Cold Start Problem in Data Science — how do you start to build a model when you have either no training data or no clear choice of model parameters. See the related post for more details about the cold start challenge.

Machine Learning 203

Machine Learning Metrics Optimization Data Science 203

Smart Data Collective

NOVEMBER 14, 2019

The subscription-based business model is no longer the preserve of magazines and home security systems. In order for these operations to be profitable and sustainable, however, they require constant optimization. Five KPIs and Metrics Worth Tracking. Here are a few that we recommend you try to keep tabs on: 1. Member Engagement.

Metrics 65

Metrics Key Performance Indicator Cost-Benefit Optimization 65

CIO Business Intelligence

NOVEMBER 20, 2023

Well-known metrics, such as deployment frequency, are useful when it comes to tracking teams but not individuals. The developer productivity metrics that matter most The reason we believe this is that we are working with 20 tech, finance, and pharmaceutical companies that are doing it. So, it’s complicated. Talent capability.

Measurement 126

Measurement Metrics Software Testing 126

O'Reilly on Data

APRIL 23, 2024

Instead of continuing to deploy their attention optimization algorithms for their users’ and suppliers’ benefit, the tech giants began to use them to favor themselves. Some of those innovations, like Amazon’s cloud computing business, represented enormous new markets and a new business model. But over time, something went very wrong.

Advertising 270

Advertising Cost-Benefit Marketing Risk 270

DataRobot Blog

APRIL 15, 2022

There is a need to optimize supply to meet demand. Predicting these irradiance metrics across a day will allow us to accurately assess the amount of solar power that can be generated. For supervised machine learning models, you need historical data to train the models and make forecasts for the future.

Forecasting 52

Forecasting Optimization Measurement Machine Learning 52

DataRobot Blog

SEPTEMBER 1, 2022

For example, a recent IDC study 1 shows that it takes about 290 days on average to deploy a model into production from start to finish. Once you move your model into production, you need to monitor and manage your models to ensure that you can trust predictions and turn them into the right business decisions.

Metrics 145

Metrics Statistics Modeling Data Science 145

CIO Business Intelligence

JANUARY 10, 2024

Optimizing cloud investments requires close collaboration with the rest of the business to understand current and future needs, building effective FinOps teams, partnering with providers, and ongoing monitoring of key performance metrics. We need hard metrics because we’re running 800 instances of cloud computers.

Cost-Benefit 124

Cost-Benefit Measurement Optimization Metrics 124

IBM Big Data Hub

APRIL 9, 2024

” Watsonx.data lets organizations optimize workloads for different uses. Preparing and annotating data IBM watsonx.data helps organizations put their data to work, curating and preparing data for use in AI models and applications. Watsonx.governance makes it easy to manage and deploy all these models effectively.”

Management 87

Management IT Machine Learning Metrics 87

Domino Data Lab

SEPTEMBER 10, 2020

Building models requires a lot of time and effort. Data scientists can spend weeks just trying to find, capture and transform data into decent features for models, not to mention many cycles of training, tuning, and tweaking models so they’re performant. Certainly, organizations need to hire expert data science professionals.

Modeling 101

Modeling IT Data Science Experimentation 101