AWS Big Data

DECEMBER 18, 2024

The service also provides multiple query languages, including SQL and Piped Processing Language (PPL) , along with customizable relevance tuning and machine learning (ML) integration for improved result ranking. Lexical search relies on exact keyword matching between the query and documents.

Metrics 87

Metrics Modeling Data Processing Machine Learning 87

O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”. While useful, these constructs are not beyond criticism. Monitoring.

Management 314

Management Machine Learning Metrics Modeling 314

Cloudera

NOVEMBER 13, 2024

LLMs deployed as internal enterprise-specific agents can help employees find internal documentation, data, and other company information to help organizations easily extract and summarize important internal content. Increase Productivity. Evaluate the performance of trained LLMs. Deploy trained LLMs to production environments.

Cost-Benefit 87

Cost-Benefit Data Processing Machine Learning Testing 87

O'Reilly on Data

JANUARY 17, 2023

” If none of your models performed well, that tells you that your dataset–your choice of raw data, feature selection, and feature engineering–is not amenable to machine learning. All of this leads us to automated machine learning, or autoML. Perhaps you need a different raw dataset from which to start.

Machine Learning 363

Machine Learning Predictive Modeling Software Modeling 363

AWS Big Data

NOVEMBER 27, 2024

Within seconds of transactional data being written into Amazon Aurora (a fully managed modern relational database service offering performance and high availability at scale), the data is seamlessly made available in Amazon Redshift for analytics and machine learning. or a later version) database.

Data Warehouse 104

Data Warehouse Analytics Testing Sales 104

KDnuggets

OCTOBER 16, 2019

This week on KDnuggets: Beyond Word Embedding: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI; Activation maps for deep learning models in a few lines of code; There is No Such Thing as a Free Lunch; 8 Paths to Getting a Machine Learning Job Interview; and much, much more.

Metrics 62

Metrics Deep Learning Machine Learning Modeling 62

CIO Business Intelligence

MARCH 5, 2025

These large-scale, asset-driven enterprises generate an overwhelming amount of information, from engineering drawings and standard operating procedures (SOPs) to compliance documentation and quality assurance data. Document management and accessibility are vital for teamsworking on construction projects in the energy sector.

Management 86

Management Data-driven Cost-Benefit Risk 86

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

Machine Learning 73

Machine Learning Modeling Deep Learning Predictive Modeling 73

CIO Business Intelligence

MARCH 19, 2025

Mark Brooks, who became CIO of Reinsurance Group of America in 2023, did just that, and restructured the technology organization to support the platform, redefined the programs success metrics, and proved to the board that IT is a good steward of the dollar. One significant change we made was in our use of metrics to challenge my team.

Metrics 64

Metrics Enterprise Cost-Benefit Experimentation 64

Smart Data Collective

MAY 31, 2022

Machine learning and artificial intelligence (AI) have certainly come a long way in recent times. Towards Data Science published an article on some of the biggest developments in machine learning over the past century. A number of new applications are making machine learning technology more robust than ever.

Machine Learning 128

Machine Learning Cost-Benefit Data Processing Metrics 128

datapine

DECEMBER 11, 2019

SaaS is less robust and less secure than on-premises applications: Despite some SaaS-based teething problems or technical issues reported by the likes of Google, these occurrences are incredibly rare with software as a service applications – and there hasn’t been one major compromise of a SaaS operation documented to date. 2) Vertical SaaS.

Software 314

Software Cost-Benefit Data-driven Data Processing 314

datapine

NOVEMBER 27, 2019

Often seen as the highest foe-friend of the human race in movies ( Skynet in Terminator, The Machines of Matrix or the Master Control Program of Tron), AI is not yet on the verge to destroy us, in spite the legit warnings of some reputed scientists and tech-entrepreneurs. 1 for data analytics trends in 2020.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

AWS Big Data

JULY 29, 2024

This enables more informed decision-making and innovative insights through various analytics and machine learning applications. You will learn about an open-source solution that can collect important metrics from the Iceberg metadata layer. It supports two types of reports: one for commits and one for scans.

Metadata 125

Metadata Snapshot Data Lake Metrics 125

Smart Data Collective

AUGUST 11, 2022

Sustaining the responsible use of machines. Human labeling and data labeling are however important aspects of the AI function as they help to identify and convert raw data into a more meaningful form for AI and machine learning to learn. AI and Machine Learning ensure that data trends are identified.

Data Quality 139

Data Quality Machine Learning Digital Transformation Big Data 139

datapine

JANUARY 21, 2020

The balance sheet gives an overview of the main metrics which can easily define trends and the way company assets are being managed. Artificial intelligence and machine-learning algorithms used in those kinds of tools can foresee future values, identify patterns and trends, and automate data alerts. It doesn’t stop here.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

CIO Business Intelligence

APRIL 8, 2025

Publish metadata, documentation and use guidelines. Make it easy to discover, understand and use data through accessible catalogs and standardized documentation. Invest in AI-powered quality tooling AI and machine learning are transforming data quality from profiling and anomaly detection to automated enrichment and impact tracing.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

CIO Business Intelligence

NOVEMBER 27, 2024

To avoid all these problems, you need to involve people with the expertise to differentiate between genuine errors and meaningful signals, document the decisions you make about data cleaning and the reasons for them, and regularly review the impact of data cleaning on both model performance and business outcomes.

Enterprise 141

Enterprise Data Quality Structured Data Modeling 141

CIO Business Intelligence

MAY 1, 2024

Gen AI takes us from single-use models of machine learning (ML) to AI tools that promise to be a platform with uses in many areas, but you still need to validate they’re appropriate for the problems you want solved, and that your users know how to use gen AI effectively. Now nearly half of code suggestions are accepted.

Cost-Benefit 143

Cost-Benefit Metrics Insurance Measurement 143

CIO Business Intelligence

MAY 28, 2022

Eight years ago, McGlennon hosted an off-site think tank with his staff and came up with a “technology manifesto document” that defined in those early days the importance of exploiting cloud-based services, becoming more agile, and instituting cultural changes to drive the company’s digital transformation.

Insurance 145

Insurance Machine Learning Digital Transformation Cost-Benefit 145

CIO Business Intelligence

JANUARY 23, 2024

For example, McKinsey suggests five metrics for digital CEOs , including the financial return on digital investments, the percentage of leaders’ incentives linked to digital, and the percentage of the annual tech budget spent on bold digital initiatives. As a result, outcome-based metrics should be your guide.

Measurement 141

Measurement Digital Transformation KPI Metrics 141

AWS Big Data

JANUARY 6, 2025

Refer to API Dimensions & Metrics for details. Follow the documentation to clean up the Google resources. Whether youre archiving historical data, performing complex analytics, or preparing data for machine learning, this connector streamlines the process, making it accessible to a broader range of data professionals.

Analytics 98

Analytics Data Warehouse Big Data Metrics 98

AWS Big Data

MARCH 13, 2024

RAG is a machine learning (ML) architecture that uses external documents (like Wikipedia) to augment its knowledge and achieve state-of-the-art results on knowledge-intensive tasks. Each service implements k-nearest neighbor (k-NN) or approximate nearest neighbor (ANN) algorithms and distance metrics to calculate similarity.

Data Processing 130

Data Processing Dashboards Machine Learning Metrics 130

AWS Big Data

SEPTEMBER 5, 2024

It comes in two modes: document-only and bi-encoder. For more details about these two terms, see Improving document retrieval with sparse semantic encoders. Simply put, in document-only mode, term expansion is performed only during document ingestion. We care more about the recall metric.

Metrics 110

Metrics Testing Experimentation Modeling 110

CIO Business Intelligence

MAY 13, 2024

IBM is betting big on its toolkit for monitoring generative AI and machine learning models, dubbed watsonx.governance , to take on rivals and position the offering as a top AI governance product, according to a senior executive at IBM. watsonx.governance is a toolkit for governing generative AI and machine learning models.

Machine Learning 122

Machine Learning Risk Enterprise Modeling 122

Domino Data Lab

SEPTEMBER 9, 2019

Data science teams in industry must work with lots of text, one of the top four categories of data used in machine learning. Next, let’s run a small “document” through the natural language parser: In [2]: text = "The rain in Spain falls mainly on the plain."? doc = nlp(text)?? for token in doc:?.

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110

Smart Data Collective

JULY 1, 2023

Image annotation is the act of labeling images for AI and machine learning models. The resulting structured data is then used to train a machine learning algorithm. There are a lot of image annotation techniques that can make the process more efficient with deep learning.

Machine Learning 93

Machine Learning Metrics Uncertainty Deep Learning 93

CIO Business Intelligence

JUNE 7, 2022

They process and analyze data, build machine learning (ML) models, and draw conclusions to improve ML models already in production. A data scientist is a mix of a product analyst and a business analyst with a pinch of machine learning knowledge, says Mark Eltsefon, data scientist at TikTok.

Machine Learning 145

Machine Learning Data Science Metrics Consulting 145

CIO Business Intelligence

MAY 15, 2024

Generative AI (genAI) arrived on the scene with use cases such as “support chatbots” or “talk to your documentation apps” that were so obviously useful that many companies are well on their way to taking them into production. No one today looks back fondly on the time their organization spent in “pilot purgatory.”

Digital Transformation 130

Digital Transformation Strategy Machine Learning Metrics 130

Smart Data Collective

FEBRUARY 9, 2022

Learn how DirectX visualization can improve your study and assessment of different trading instruments for maximum productivity and profitability. A growing number of traders are using increasingly sophisticated data mining and machine learning tools to develop a competitive edge.

Visualization 145

Visualization Optimization Analytics Testing 145

CIO Business Intelligence

AUGUST 1, 2024

But more recently, executive management has asked IT to justify these projects by documenting the benefits and value to the business. Dev teams can use existing metrics as guideposts for application design, evaluating the current apps to identify the most beneficial ways to use AI. This is a smart move.

ROI 105

ROI Metrics Measurement Risk 105

CIO Business Intelligence

APRIL 8, 2024

Computer vision, AI, and machine learning (ML) all now play a role. million video frames and documents about 100 million locations and positions of players on the field. Jamie Capel-Davies, head of science and technical for ITF, says metrics don’t mean much if you can’t communicate them effectively in time to make use of them.

Analytics 118

Analytics Broadcasting Predictive Analytics Machine Learning 118

Smart Data Collective

JUNE 6, 2021

The collection and use of relevant metrics can, therefore, potentially boost your chances of engaging new prospects while keeping existing customers satisfied. Customer experience is another key area that can benefit from big data analytics. Big data analytics advantages. Is Google BigQuery the future of big data analytics?

Big Data 137

Big Data Data Analytics Analytics Cost-Benefit 137

AWS Big Data

AUGUST 21, 2023

Lexical search looks for words in the documents that appear in the queries. Background A search engine is a special kind of database, allowing you to store documents and data and then run queries to retrieve the most relevant ones. OpenSearch Service supports a variety of search and relevance ranking techniques.

Data Processing 98

Data Processing Visualization Experimentation Metrics 98

CIO Business Intelligence

AUGUST 15, 2024

A virtual assistant may save employees time when searching for old documents or composing emails, but most organizations have no idea how much time those tasks have taken historically, having never tracked such metrics before, she says. There are a lot of cool AI solutions that are cheaper than generative AI,” Stephenson says.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

AWS Big Data

APRIL 2, 2024

Data consumers need detailed descriptions of the business context of a data asset and documentation about its recommended use cases to quickly identify the relevant data for their intended use case. This reduces the need for time-consuming manual documentation, making data more easily discoverable and comprehensible.

Metadata 109

Metadata Metrics Data-driven Contextual Data 109

IBM Big Data Hub

MARCH 6, 2024

Traditional metrics, such as lines of code written or hours worked, often fall short in capturing the intricacies of complex workflows. DevOps Research and Assessment metrics (DORA), encompassing metrics like deployment frequency, lead time and mean time to recover , serve as yardsticks for evaluating the efficiency of software delivery.

Metrics 106

Metrics Testing Measurement Key Performance Indicator 106

AWS Big Data

JANUARY 9, 2024

2023 was a year of rapid innovation within the artificial intelligence (AI) and machine learning (ML) space, and search has been a significant beneficiary of that progress. Lexical search In lexical search, the search engine compares the words in the search query to the words in the documents, matching word for word.

Visualization 116

Visualization Cost-Benefit Modeling Machine Learning 116