O'Reilly on Data

SEPTEMBER 15, 2021

In June 2021, we asked the recipients of our Data & AI Newsletter to respond to a survey about compensation. There was a lot of uncertainty about stability, particularly at smaller companies: Would the company’s business model continue to be effective? Would your job still be there in a year? Executive Summary. Demographics.

Machine Learning 363

Machine Learning Statistics Reporting Consulting 363

AWS Big Data

DECEMBER 18, 2024

In the rapidly evolving landscape of AI-powered search, organizations are looking to integrate large language models (LLMs) and embedding models with Amazon OpenSearch Service. In this blog post, well dive into the various scenarios for how Cohere Rerank 3.5 OpenSearch Service natively supports BM25.

Metrics 96

Metrics Modeling Data Processing Machine Learning 96

O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. Why is high-quality and accessible data foundational?

Machine Learning 364

Machine Learning Statistics Data Quality Data Collection 364

O'Reilly on Data

NOVEMBER 28, 2023

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. But 18% already have applications in production.

Enterprise 339

Enterprise Modeling Testing Reporting 339

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 1) Data Quality Management (DQM). We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. foundation model (FM) in Amazon Bedrock as the LLM. Can it also help write SQL queries?

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

datapine

DECEMBER 11, 2019

“Software as a service” (SaaS) is becoming an increasingly viable choice for organizations looking for the accessibility and versatility of software solutions and online data analysis tools without the need to rely on installing and running applications on their own computer systems and data centers. Dispelling 3 Common SaaS Myths.

Software 314

Software Cost-Benefit Data-driven Data Processing 314

datapine

DECEMBER 4, 2019

Each year, we hear about buzzwords that enter the community, language, market and drive businesses and companies forward. Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. The accuracy of the predictions depends on the data used to create the model.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Cloudera

DECEMBER 4, 2024

Today, Artificial Intelligence (AI) and Machine Learning (ML) are more crucial than ever for organizations to turn data into a competitive advantage. To unlock the full potential of AI, however, businesses need to deploy models and AI applications at scale, in real-time, and with low latency and high throughput. Why did we build it?

Metrics 73

Metrics Data Processing Machine Learning Deep Learning 73

datapine

MARCH 31, 2022

Does data excite, inspire, or even amaze you? Does the idea of discovering patterns in large volumes of information make you want to roll up your sleeves and get to work? 4) Business Intelligence Job Roles. 5) Main Challenges Of A BI Career. 6) Main Players In The BI Industry. The BI industry is expected to soar to a value of $26.50

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

Ontotext

JANUARY 10, 2025

Introduction In the real world, obtaining high-quality annotated data remains a challenge. Generative AI (GenAI) models, such as GPT-4, offer a promising solution, potentially reducing the dependency on labor-intensive annotation. This blog post summarizes our findings, focusing on NER as a first-step key task for knowledge extraction.

Informatics 59

Informatics Modeling Metadata Experimentation 59

Smarten

NOVEMBER 26, 2024

Why is Data Insight So Important? Every business (large or small) creates and depends upon data. But too much data can also create issues. If the data is not easily gathered, managed and analyzed, it can overwhelm and complicate decision-makers.

Machine Learning 62

Machine Learning Data Quality Predictive Modeling Metadata 62

Domino Data Lab

JULY 15, 2021

In the multiverse of data science, the tool options continue to expand and evolve. While there are certainly engineers and scientists who may be entrenched in one camp or another (the R camp vs. Python, for example, or SAS vs. MATLAB), there has been a growing trend towards dispersion of data science tools. What Are Data Science Tools?

Data Science 145

Data Science Visualization Enterprise Modeling 145

CIO Business Intelligence

NOVEMBER 20, 2024

At its Microsoft Ignite 2024 show in Chicago this week, Microsoft and industry partner experts showed off the power of small language models (SLMs) with a new set of fine-tuned, pre-trained AI models using industry-specific data. Among the first models released is E.L.Y.

Manufacturing 121

Manufacturing Marketing Finance Modeling 121

datapine

SEPTEMBER 4, 2019

Exclusive Bonus Content: Download Data Implementation Tips! A dashboard in business is a tool used to manage all the business information from a single point of access. It helps managers and employees to keep track of the company’s KPIs and utilizes business intelligence to help companies make data-driven decisions.

Dashboards 263

Dashboards Analytics Key Performance Indicator Sales 263

datapine

MARCH 25, 2022

There is not a clear line between business intelligence and analytics, but they are extremely connected and interlaced in their approach towards resolving business issues, providing insights on past and present data, and defining future decisions. Your Chance: Want to extract the maximum potential out of your data? Table of Contents.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Data Virtualization

AUGUST 23, 2024

The climate is full of creativity and innovation, and we’re learning that large language models (LLMs) have capabilities we can exploit in many ways. The post Querying Minds Want to Know: Can a Data Fabric and RAG Clean up LLMs? In previous posts, I spoke.

Data Integration 98

Data Integration Modeling Management Data Architecture 98

CIO Business Intelligence

OCTOBER 13, 2023

In the next six to 12 months, some of the most popular anticipated uses for gen AI include content creation (42%), data analytics (53%), software development (41%), business insight (51%), internal customer support (45%), product development (40%), security (42%), and process automation (51%).

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Data Science 101

SEPTEMBER 6, 2023

But I’d say in the near future I’m most excited about large language models, after that would be spatial computing. OK, let’s talk about Large Language Models (LLMs). Large language models are basically AI trained to understand and generate human-like text.

Interactive 111

Interactive IoT Sales Modeling 111

CIO Business Intelligence

JUNE 28, 2023

The fully managed AppFabric offering, which has been made generally available, is designed to help enterprises maintain SaaS application interoperability without having to develop connectors or workflows in-house while offering added security features, said Federico Torreti, the head of product for AppFabric.

Enterprise 136

Enterprise Machine Learning Metrics Modeling 136

erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

IBM Big Data Hub

FEBRUARY 13, 2024

They are now capable of natural language processing ( NLP ), grasping context and exhibiting elements of creativity. Demystifying generative AI At the heart of Generative AI lie massive databases of texts, images, code and other data types. Autoregressive models or large language models (LLMs) are used for text and language.

Enterprise 118

Enterprise Testing Modeling Data-driven 118

CIO Business Intelligence

AUGUST 30, 2024

Early examples of the technology include GitHub Copilot Workspace, an integrated code repository agent, and Google AI Teammate, an AI assistant that can manage projects by monitoring company processes, creating reports, and generating new tickets for programmers, notes Mikhail Dunaev, chief AI officer at ComplyControl, a banking technology provider.

ROI 138

ROI Recreation/Entertainment Machine Learning Interactive 138

CIO Business Intelligence

MAY 3, 2024

The LLM gives agents the ability to confirm all responses suggested by the model. Bala Subramanian, chief digital and technology officer at UPS, sees the company’s foray into generative AI as not only a winner for its customer contact center agents but something to be introduced to other business processes in the near future, he says.

Testing 140

Testing Sales Enterprise Digital Transformation 140

Domino Data Lab

FEBRUARY 19, 2021

spaCy is a python library that provides capabilities to conduct advanced natural language processing analysis and build models that can underpin document analysis, chatbot capabilities, and all other forms of text analysis. brings many improvements to help build, configure and maintain your NLP models, including.

Enterprise 119

Enterprise Data Science Modeling Visualization 119

Smarten

MARCH 19, 2025

To function, GenAI models must be trained, using large datasets. Generative AI utilizes neural networks to recognize and identify these patterns in training data, and use that data to generate content. Tools like DALL-E, Stable Diffusion, and ChatGPT are based on multimodal models. Talk of AI is everywhere.

Cost-Benefit 52

Cost-Benefit Digital Transformation Manufacturing Machine Learning 52

CIO Business Intelligence

SEPTEMBER 19, 2024

The challenge is that these architectures are convoluted, requiring multiple models, advanced RAG [retrieval augmented generation] stacks, advanced data architectures, and specialized expertise.” The goal at Goldcast is to link all these AI models and turn them into agents that do their assigned tasks without human prompts, she says.

IT 138

IT Cost-Benefit Consulting Modeling 138

CIO Business Intelligence

SEPTEMBER 21, 2023

AI is now a board-level priority Last year, AI consisted of point solutions and niche applications that used ML to predict behaviors, find patterns, and spot anomalies in carefully curated data sets. Today’s foundational models are jacks-of-all-trades. According to McKinsey, gen AI is poised to add up to an annual $4.4

Enterprise 129

Enterprise Consulting Modeling Cost-Benefit 129

CIO Business Intelligence

MAY 2, 2023

The move, which is expected to help SAP exploit the natural language processing (NLP) abilities of Watson AI along with predictive insights, is aimed at boosting the productivity of an enterprise and accelerating innovation, especially across retail, manufacturing, and utilities sectors, the companies said in a joint statement.

IT 115

IT Manufacturing Machine Learning Marketing 115

Ontotext

DECEMBER 9, 2020

Stop wasting time building data access code manually, let the Ontotext Platform auto-generate a fast, flexible, and scalable GraphQL APIs over your RDF knowledge graph. Are you having difficulty joining your knowledge graph APIs with other data sources? This leads to lots of small data fetches to/from GraphDB over the network.

Modeling 130

Modeling Management Optimization Machine Learning 130

CIO Business Intelligence

AUGUST 26, 2024

IBM is outfitting the next generation of its z and LinuxONE mainframes with its next-generation Telum processor and a new accelerator aimed at boosting performance of AI and other data-intensive workloads. New compute primitives have also been incorporated to better support large language models within the accelerator.

Enterprise 132

Enterprise Insurance Optimization Modeling 132

erwin

DECEMBER 9, 2024

When it comes to using AI and machine learning across your organization, there are many good reasons to provide your data and analytics community with an intelligent data foundation. For instance, Large Language Models (LLMs) are known to ultimately perform better when data is structured.

Metadata 52

Metadata Data Quality Sales Modeling 52

Domino Data Lab

APRIL 29, 2021

Summary: APIs will get better at transferring model components from one application to another and transferring pipelines to production. If we can crack the nut of enabling a wider workforce to build AI solutions, we can start to realize the promise of data science. Transfer learning entails more than just sharing pre-trained models.

Data Science 134

Data Science Deep Learning Modeling Forecasting 134

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. What Are Modeling Tools? Importance of Modeling Tools. Types of Modeling Tools.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

Smart Data Collective

MAY 1, 2022

Multiple emails, social media posts, blogs, articles, and other text forms are generated daily. This will eventually lead you to situations where you know that valuable data is inside these documents, but you cannot extract them. . If data had to be sorted manually, it would easily take months or even years to do it.

Unstructured Data 132

Unstructured Data Cost-Benefit Machine Learning Marketing 132