datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. The end-user is another factor to consider. Most BI software in the market are self-service.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

CIO Business Intelligence

MARCH 18, 2024

These microservices are provided as downloadable software containers used to deploy enterprise applications, Nvidia said in an official blog post. For NIM microservices the focus is on deployment times for generative AI apps, which the company said can be reduced “from weeks to minutes” with its services. Nvidia’s AI Enterprise 5.0

Enterprise 98

Enterprise Data Processing Optimization Modeling 98

datapine

SEPTEMBER 4, 2019

Determining which overarching category your dashboard sits in is the first order of business. They are often complex: utilizing complex models and what-if statements. Now that we have separated the dashboards into two large categories, let’s dig deeper. They are often used across various levels of an organization.

Dashboards 263

Dashboards Analytics Key Performance Indicator Sales 263

CIO Business Intelligence

MAY 3, 2024

The LLM gives agents the ability to confirm all responses suggested by the model. Gownder, in a blog post last November as UPS was putting its solution into limited production. As a result, UPS is investing in training the model on its corporate data set. For MeRA, UPS started with Microsoft OpenAI LLMs, GPT 3.5 Turbo and GPT4.

Testing 140

Testing Sales Enterprise Digital Transformation 140

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

Experimentation 73

Experimentation Deep Learning Modeling Data-driven 73

Cloudera

JUNE 11, 2024

More than two-thirds of companies are currently using Generative AI (GenAI) models, such as large language models (LLMs), which can understand and generate human-like text, images, video, music, and even code. However, the true power of these models lies in their ability to adapt to an enterprise’s unique context.

Enterprise 93

Enterprise Unstructured Data Contextual Data Data-driven 93

The Data Visualisation Catalogue

JANUARY 24, 2023

After consuming a number of YouTube videos, blog posts, articles, and playing around with ChatGPT, I felt the need to write down my thoughts and observations on the topic. For those unaware, ChatGPT is a large language model developed by OpenAI. There isn’t an ‘appropriate’ number of bars.

Visualization 113

Visualization Interactive Data-driven Testing 113

IBM Big Data Hub

MAY 1, 2023

In 1847, George Boole first described a formal language for logic reasoning and in 1936, Alan Turing described the Turing machine. After the success of Deep Blue, IBM again made the headlines with IBM Watson, an AI system capable of answering questions posed in natural language, when it won the quiz show Jeopardy against human champions.

Insurance 75

Insurance Predictive Modeling Cost-Benefit Statistics 75

AWS Big Data

SEPTEMBER 12, 2024

In this blog post, we will highlight how ZS Associates used multiple AWS services to build a highly scalable, highly performant, clinical document search platform. Based on the business use case for search, a graph model was defined. Models like Flan-t5 were also used for extraction of other similar entities used in the procedures.

Unstructured Data 111

Unstructured Data Metadata Machine Learning Consulting 111

AWS Big Data

JUNE 18, 2024

Amazon Titan Multimodal Embeddings G1 is a multimodal embedding model that generates embeddings to facilitate multimodal search. When you use the neural plugin’s connectors, you don’t need to build additional pipelines external to OpenSearch Service to interact with these models during indexing and searching.

Dashboards 119

Dashboards Metadata Modeling Visualization 119

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. the target or outcome variable is known).

Machine Learning 73

Machine Learning Modeling Deep Learning Predictive Modeling 73

Ontotext

AUGUST 16, 2024

And let’s emphasize that generative AI is more than just large language models. It allows you to be more scalable and handle large language models more effectively, ensuring you can trust the answers. When you try to ask a large language model about itself it doesn’t always give back great answers.

Modeling 69

Modeling Testing Interactive Marketing 69

IBM Big Data Hub

SEPTEMBER 20, 2023

Foundational models (FMs) are marking the beginning of a new era in machine learning (ML) and artificial intelligence (AI) , which is leading to faster development of AI that can be adapted to a wide range of downstream tasks and fine-tuned for an array of applications. What are large language models?

Modeling 83

Modeling Enterprise Software Data Science 83

Octopai

JULY 17, 2022

If you’re planning on taking a trip that crosses international borders, you would be wise to plan for inevitable differences, like: Language. Worse is if your “good morning” sounds like something else in the local language, and your addressee assumes he did process what you said. At best, your bright and cheery “good morning!”

Machine Learning 98

Machine Learning Visualization Enterprise Software 98

CIO Business Intelligence

OCTOBER 25, 2023

Zscaler Other industries, like finance, have shown steep growth in the use of AI/ML tools, largely driven by the adoption of generative AI chat tools like ChatGPT and Drift. Zscaler The risks of leveraging AI and ML tools As we discussed in a recent blog , the risks of using generative AI tools in the enterprises are significant.

Enterprise 133

Enterprise Manufacturing Risk Data-driven 133

Laminar Security

DECEMBER 13, 2023

ML, a subset of AI, involves training models on existing data sets so they can make predictions or decisions without being explicitly programmed to do so. This advanced approach not only enhances the efficiency of detection models but also yields more insightful and valuable outcomes.

Data-driven 119

Data-driven Machine Learning Deep Learning Risk 119

AWS Big Data

APRIL 24, 2023

It allows you to access diverse data sources, build business intelligence dashboards, build AI and machine learning (ML) models to provide customized customer experiences, and accelerate the curation of new datasets for consumption by adopting a modern data architecture or data mesh architecture. Choose Create bucket. Create two subfolders.

Data Lake 98

Data Lake Data Governance Machine Learning Cost-Benefit 98

Cloudera

NOVEMBER 15, 2021

This blog discusses quantifications, types, and implications of data. In other words, structured data has a pre-defined data model , whereas unstructured data doesn’t. . It facilitates AI because, to be useful, many AI models require large amounts of data for training. Quantifications of data. The challenges of data.

Unstructured Data 90

Unstructured Data Recreation/Entertainment Structured Data Reporting 90

IBM Big Data Hub

JANUARY 10, 2024

For example, learning, reasoning, problem-solving, perception, language understanding and more. Data: AI systems learn and make decisions based on data, and they require large quantities of data to train effectively, especially in the case of machine learning (ML) models.

Unstructured Data 75

Unstructured Data Deep Learning Cost-Benefit Machine Learning 75

IBM Big Data Hub

NOVEMBER 24, 2023

Generative AI becomes very handy here through its ability to correlate domain/functional capabilities to code and data and establish business capabilities view and connected application code and data—of course the models need to be tuned/contextualized for a given enterprise domain model or functional capability map.

Cost-Benefit 89

Cost-Benefit Testing Data-driven Enterprise 89

IBM Big Data Hub

NOVEMBER 14, 2023

High performing, data-driven organizations have created new business models, utility partnerships and enhanced existing offerings from data monetization that contributes more than 20% to the company’s profitability. Data products come in many forms including datasets, programs and AI models.

Strategy 103

Strategy Data-driven Cost-Benefit Measurement 103

IBM Big Data Hub

FEBRUARY 2, 2024

Not an easy task when you need to celebrate the achievements and stories of more than 1,000 nominees across nearly 100 categories. A generative AI content engine fueled by trusted data This year’s solution uses watsonx to leverage a powerful large language model (LLM) hosted in the watsonx.ai

Recreation/Entertainment 59

Recreation/Entertainment Broadcasting Consulting Dashboards 59

Smart Data Collective

OCTOBER 14, 2019

Ludwig is a tool that allows people to build data-based deep learning models to make predictions. Some examples of the projects you could undertake with help from Ludwig include text or image classification, machine-based language translation and sentiment analysis. The website breaks down the types of charts into categories.

Data Science 94

Data Science Machine Learning Big Data Interactive 94

Sisense

OCTOBER 6, 2020

These techniques allow you to: See trends and relationships among factors so you can identify operational areas that can be optimized Compare your data against hypotheses and assumptions to show how decisions might affect your organization Anticipate risk and uncertainty via mathematically modeling.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

IBM Big Data Hub

OCTOBER 12, 2023

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. The three kinds of AI based on capabilities 1.

Machine Learning 67

Machine Learning Deep Learning Interactive Modeling 67

Ontotext

JULY 2, 2024

That’s why the usual method of analyzing them automatically involves traditional natural language processing techniques. Instead, we propose a new approach: Retrieval-Augmented Generation (RAG) , combining a highly normalized knowledge graph with large language models (LLMs). Then, the LLM also functions as a recommender.

Measurement 59

Measurement Visualization Snapshot Testing 59

IBM Big Data Hub

JULY 6, 2023

This blog post will clarify some of the ambiguity. Categories of AI Three main categories of AI are: Artificial Narrow Intelligence (ANI) Artificial General Intelligence (AGI) Artificial Super Intelligence (ASI) ANI is considered “weak” AI, whereas the other two types are classified as “strong” AI.

Deep Learning 56

Deep Learning Machine Learning Unstructured Data Modeling 56

Occam's Razor

JULY 15, 2014

We need to create two categories of dashboards. For both categories, especially the valuable second kind of dashboards, we need words – lots of words and way fewer numbers. I recommend a shift to Profit Per Click and Avinash Kaushik's custom attribution model. They need more English language. Your insights.

Dashboards 160

Dashboards Key Performance Indicator Snapshot Slice and Dice 160

erwin

JUNE 7, 2022

This blog is based upon webcast which can be watched here. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. As with the part 1 of this blog series, the cloud is not nirvana.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

Ontotext

MAY 22, 2023

What is the future of knowledge graphs in the era of ChatGPT and Large Language Models? To start with, Large Language Models (LLM) will not replace databases. They are good for compressing information, but one cannot retrieve from such a model the same information that it got trained on.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

Insight

MARCH 28, 2019

These categories are relatively broad (e.g. To measure this sentiment, Derek classified each sentence in a review as belonging to one of five categories: Culture & Values, Work/Life Balance, Senior Management, Compensation & Benefits, Career Opportunities (the same five dimensions Glassdoor asks employees to rate along).

Dashboards 70

Dashboards Data Science Visualization Machine Learning 70

Domino Data Lab

MARCH 6, 2019

This blog recaps Miner & Kasch ’s first Maryland Data Science Conference hosted at UMBC and dives into the Deep Learning on Imagery and Text talk presented by Florian Muellerklein and Bryan Wilkinson. These multi-stage representations are at the heart of improving the accuracy of models and they apply to a variety of use cases.

Deep Learning 55

Deep Learning Data Science Machine Learning Data Processing 55

Insight

OCTOBER 25, 2019

In this blog, I’ll illustrate an approach by walking you through my project during my Data Science Fellowship at Insight , followed by a quick discussion pertaining to broader application. Among these categories, one consists of only two objects (objects 27 and 29). a large number of training images.

Snapshot 57

Snapshot Testing Deep Learning Visualization 57

Sisense

MARCH 23, 2020

And we consider the role played by change agents within large businesses that make this process happen. An advanced BI and analytics platform is an essential tool for these teams to integrate data insights into workflows with analytic apps and technology such as AI and Natural Language Processing.

Analytics 64

Analytics Data-driven Consulting Marketing 64

Ontotext

FEBRUARY 26, 2024

From a technological perspective, RED combines a sophisticated knowledge graph with large language models (LLM) for improved natural language processing (NLP), data integration, search and information discovery, built on top of the metaphactory platform. Let’s have a quick look under the bonnet.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Ontotext

NOVEMBER 9, 2023

The most popular solution to this problem in the RDF world is called SHACL , the SHApes Constraint Language “The old ways” — how validation used to work Prior to the introduction of SHACL, validation would mostly be manual, or reliant on OWL ( Web Ontology Language ) constraints. Shapes are very similar to classes in OWL.

Data Quality 64

Data Quality Testing Reporting Metadata 64

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. Knowledge graphs model knowledge of a domain as a graph with a network of entities and relationships. Increasingly, organizations are using both.

Modeling 53

Modeling Metadata Data Quality Enterprise 53