Cloudera

JUNE 26, 2023

For data engineering and data science teams, CDSW is highly effective as a comprehensive platform that trains, develops, and deploys machine learning models. It can provide a complete solution for data exploration, data analysis, data visualization, viz applications, and model deployment at scale.

Testing 75

Testing Data Processing Visualization Data Science 75

AWS Big Data

AUGUST 21, 2023

For the demo, we’re using the Amazon Titan foundation model hosted on Amazon Bedrock for embeddings, with no fine tuning. It similarly codes the query as a vector and then uses a distance metric to find nearby vectors in the multi-dimensional space. The algorithm for finding nearby vectors is called kNN (k Nearest Neighbors).

Data Processing 93

Data Processing Experimentation Visualization Metrics 93

IBM Big Data Hub

OCTOBER 16, 2023

They differ from virtual machines in that they leverage the features and resources of the host OS versus requiring a guest OS in every instance. Containerization helps DevOps teams avoid the complications that arise when moving software from testing to production.

Data Processing 75

Data Processing Dashboards Metrics Software 75

CIO Business Intelligence

NOVEMBER 29, 2023

If you choose not to use a cloud provider’s native services in order to remain agnostic, you lose many of the ‘better, cheaper, faster’ business case metrics,” says Holcombe. Most of the time, those CIOs decide to keep the multi-cloud model because they’re locked in. You’re trapped, big time,” says Nag. Adopt a hybrid cloud approach.

Recreation/Entertainment 124

Recreation/Entertainment Testing Strategy Risk 124

Cloudera

JULY 24, 2023

As a result, the platform development team needs to test many different combinations to ultimately identify the right major / minor version of each project that properly integrates with the rest of the custom distribution. data engineering pipelines, machine learning models).

Analytics 65

Analytics Testing Metrics Management 65

O'Reilly on Data

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. For machine learning systems used in consumer internet companies, models are often continuously retrained many times a day using billions of entirely new input-output pairs.

Management 332

Management Machine Learning Experimentation Metrics 332

AWS Big Data

JUNE 14, 2023

This post focuses on how to properly size your MSK tiered storage cluster, which metrics to monitor, and the best practices to consider when running a production workload. Therefore, we model these three different consumer groups in the equation to account for their impact on infrastructure usage.

Metrics 86

Metrics Cost-Benefit Testing Optimization 86

CIO Business Intelligence

MARCH 13, 2024

We did side-by-side testing,” he says. AI models are able to present best practice code systems to help junior developers learn and hone their skills.” In testing, gen AI was also particularly good at generating test cases and creating dummy data for testing. It’s not about reducing headcount, he adds.

IT 128

IT Consulting Testing Cost-Benefit 128

DataRobot

JUNE 29, 2021

Well, just imagine a production machine learning model that always stays accurate after it’s deployed—all by itself. Machine learning models trained on 2019 data didn’t know what to do. Continuous AI not only retrains your current production models for you. Why do I think this? Sounds pretty cool, right? Over and over.

Machine Learning 80

Machine Learning Data Processing Forecasting Modeling 80

datapine

JUNE 18, 2019

We live in a data-driven age, and the ability to use financial insights and metrics to your advantage will set you apart from the pack. Our monthly reports are on top illustrated with beautiful data visualizations that provide a better understanding of the metrics tracked. The reporting tools to do that exist for that very purpose.

Reporting 251

Reporting Metrics KPI Finance 251

CIO Business Intelligence

SEPTEMBER 22, 2022

Seeing that remote working continues to be a pressing issue still finding its footing after nearly three years in beta testing, the work surrounding feasible solutions seems to compound as time goes on, with some intending a full return to office while others have forged the company future on remote models.

Uncertainty 110

Uncertainty Forecasting Visualization Big Data 110

DataRobot

JUNE 10, 2021

To foster innovation in this area, AICrowd hosted a competition to predict the olfactory properties of a molecule. DataRobot’s AutoML uses different feature engineering techniques and a variety of machine learning algorithms to identify the best model for multilabel classification. With DataRobot this is a one-click step.

Metrics 52

Metrics Machine Learning Visualization Experimentation 52

AWS Big Data

FEBRUARY 26, 2024

When you start the process of designing your data model for Amazon Keyspaces, it’s essential to possess a comprehensive understanding of your access patterns, similar to the approach used in other NoSQL databases. Now that all components have been deployed, we can test the solution and conduct various searches on the OpenSearch Service index.

Dashboards 65

Dashboards Testing Metrics Optimization 65

AWS Big Data

JANUARY 9, 2024

Traditional lexical search, based on term frequency models like BM25, is widely used and effective for many search applications. Semantic search In semantic search, the search engine uses an ML model to encode text or other media (such as images and videos) from the source documents as a dense vector in a high-dimensional vector space.

Cost-Benefit 96

Cost-Benefit Visualization Modeling Machine Learning 96

Occam's Razor

SEPTEMBER 15, 2011

Winners, well before they think data or tool, have a well structured Digital Marketing & Measurement Model. This article guides you in understanding the value of the Digital Marketing & Measurement Model (notice the repeated emphasis on Marketing, not just Measurement), and how to create one for yourself. Here’s a great test.

Measurement 166

Measurement Marketing Modeling Key Performance Indicator 166

AWS Big Data

MAY 2, 2023

If your updates to a dataset triggers multiple subsequent DAGs, then you can use the Airflow metric max_active_tasks_per_dag to control the parallelism of the consumer DAG and reduce the chance of overloading the system. The workflow steps are as follows: The producer DAG makes an API call to a publicly hosted API to retrieve data.

Testing 105

Testing Experimentation Management Metadata 105

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. Because data analysts often build machine learning models, programming and AI knowledge are also valuable. It’s also necessary to understand data cleaning and processing techniques.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56

AWS Big Data

NOVEMBER 16, 2023

As with all AWS services, Amazon Redshift is a customer-obsessed service that recognizes there isn’t a one-size-fits-all for customers when it comes to data models, which is why Amazon Redshift supports multiple data models such as Star Schemas, Snowflake Schemas and Data Vault.

Enterprise 87

Enterprise Data Warehouse Snapshot Cost-Benefit 87

CIO Business Intelligence

OCTOBER 13, 2022

Hosting the entire infrastructure on-premise will turn out to be exorbitant,” he says. This is followed by an end-to-end testing upgrading from component,” Kumar says. “If At the end of that sprint, users would have a UI/UX for testing and it would be open to any changes if required instead of being there till the end of the project.”.

ROI 132

ROI IT Sales Consulting 132

O'Reilly on Data

APRIL 22, 2020

For example, payday lending businesses are no doubt compliant with the law, but many aren’t models for good corporate citizenship. There aren’t simple standards and tests for ethical behavior, nor are you as likely to be called into court for acting unethically. Ethics is much more slippery.

Cost-Benefit 249

Cost-Benefit Finance Strategy Data-driven 249

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

DataRobot

JANUARY 15, 2020

Kaggle is a popular online forum that hosts machine learning competitions with real-world data, often provided by commercial or non-profit enterprises to crowd-source AI solutions to their problems. For every competition, the host provides a training and test set of data. Their accuracy is then ranked on a public leaderboard.

Data Processing 16

Data Processing Testing Metrics Machine Learning 16

DataKitchen

APRIL 13, 2021

Testing and Data Observability. DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Testing and Data Observability.

Testing 300

Testing Machine Learning Consulting Data Quality 300

Occam's Razor

APRIL 25, 2011

The issues of course include people and jaded mental models and bureaucracy and a lack of time and the missing desire to be great and org structures, and bosses. Doing anything on the web without a Web Analytics Measurement Model. Making lame metrics the measures of success: Impressions, Click-throughs, Page Views.

Marketing 126

Marketing Measurement Metrics Testing 126

DataKitchen

NOVEMBER 29, 2021

Model developers will test for AI bias as part of their pre-deployment testing. Quality test suites will enforce “equity,” like any other performance metric. Continuous testing, monitoring and observability will prevent biased models from deploying or continuing to operate. Companies Commit to Remote.

Testing 245

Testing Data Lake Data Architecture Manufacturing 245

Occam's Razor

SEPTEMBER 9, 2013

One of the key things we are going to learn today is to align our metrics and dimensions optimally to ensure we report good, clean, sensible data. The above graphic is from post, Excellent Analytics Tip #23: Align Hits, Sessions, Metrics, Dimensions! Your effort will make this post 100x more valuable.

Analytics 145

Analytics Metrics Marketing Reporting 145

O'Reilly on Data

JANUARY 17, 2023

Building Models. A common task for a data scientist is to build a predictive model. You’ll try this with a few other algorithms, and their respective tuning parameters–maybe even break out TensorFlow to build a custom neural net along the way–and the winning model will be the one that heads to production.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

AWS Big Data

MARCH 13, 2024

For building any generative AI application, enriching the large language models (LLMs) with new data is imperative. Each service implements k-nearest neighbor (k-NN) or approximate nearest neighbor (ANN) algorithms and distance metrics to calculate similarity. This is where the Retrieval Augmented Generation (RAG) technique comes in.

Data Processing 115

Data Processing Dashboards Machine Learning Management 115

datapine

APRIL 15, 2020

Your Chance: Want to test an agile business intelligence solution? Business intelligence is moving away from the traditional engineering model: analysis, design, construction, testing, and implementation. In the traditional model communication between developers and business users is not a priority. Finalize testing.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

Occam's Razor

DECEMBER 9, 2009

The four pronged real world tested probing and loaded with politics framework to find a home for Web Analytics: 1. Who owns the power to make changes to the site (not who owns updating pages or hosting the site)? Which physical organizational model will work best for you? Are there standard tools deployed? Centralized?

Analytics 95

Analytics Data-driven Marketing Sales 95

DataRobot Blog

FEBRUARY 2, 2023

Large language models, also known as foundation models, have gained significant traction in the field of machine learning. These models are pre-trained on large datasets, which allows them to perform well on a variety of tasks without requiring as much training data. What Are Large Language Models?

Modeling 52

Modeling Machine Learning Data Processing Interactive 52

IBM Big Data Hub

NOVEMBER 13, 2023

Kubernetes can also run on bare metal servers and virtual machines (VMs) in private cloud, hybrid cloud and edge settings, provided the host OS is a version of Linux or Windows. Overall, Kubernetes provides the flexibility, portability and scalability needed to train, test, schedule and deploy ML and generative AI models.

Machine Learning 112

Machine Learning Data-driven Software Testing 112

The Unofficial Google Data Science Blog

JULY 17, 2018

Alternatively, guidance and insight may be delivered below the executive level to product managers and engineering leads, directing product feature development via metrics and A/B experiments. This measure of web page value is on a meaningful linear scale, such that our freshness metric (a weighted average) has an intuitive interpretation.

Data Science 85

Data Science Snapshot Data Processing Optimization 85

Cloudera

SEPTEMBER 13, 2021

Cruise Control is integrated with Kafka through metrics reporting. In CDP it connects to Cloudera Manager’s time series database to fetch metrics. Metrics Reporting. This is a pluggable component that fetches and stores Kafka metrics. The open source version of Cruise Control stores metrics back to Kafka or Prometheus.

Metrics 69

Metrics Data Processing Optimization Testing 69

AWS Big Data

OCTOBER 11, 2023

Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities. These metrics help agents improve their call handle time and also reallocate agents across organizations to handle pending calls in the queue. We use two datasets in this post.

Management 109

Management Metadata Analytics Dashboards 109

CIO Business Intelligence

AUGUST 15, 2023

Shamim Mohammad, CIO, CarMax CarMax That volume created a Sisyphean task for the company’s content writers, as they struggled to provide up-to-date information by make, model, and year for each vehicle in the company’s constantly changing inventory. And it yields multiple business metric improvements, such as limiting surplus inventory.

IT 98

IT Manufacturing IoT Cost-Benefit 98

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. DataRobot Notebooks is a fully hosted and managed notebooks platform with auto-scaling compute capabilities so you can focus more on the data science and less on low-level infrastructure management.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52