CIO Business Intelligence

MARCH 25, 2025

Using the companys data in LLMs, AI agents, or other generative AI models creates more risk. Build up: Databases that have grown in size, complexity, and usage build up the need to rearchitect the model and architecture to support that growth over time.

Risk 140

Risk Cost-Benefit Data-driven Digital Transformation 140

O'Reilly on Data

FEBRUARY 19, 2021

The data that powers ML applications is as important as code, making version control difficult; outputs are probabilistic rather than deterministic, making testing difficult; training a model is processor intensive and time consuming, making rapid build/deploy cycles difficult. ML presents a problem for CI/CD for several reasons.

Data Lake 361

Data Lake Machine Learning Data Warehouse Modeling 361

O'Reilly on Data

SEPTEMBER 19, 2023

” Each step has been a twist on “what if we could write code to interact with a tamper-resistant ledger in real-time?” Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools. ” Most recently, I’ve been thinking about this in terms of the space we currently call “AI.”

Machine Learning 339

Machine Learning Testing Modeling Cost-Benefit 339

O'Reilly on Data

JUNE 7, 2022

DeepMind’s new model, Gato, has sparked a debate on whether artificial general intelligence (AGI) is nearer–almost at hand–just a matter of scale. Gato is a model that can solve multiple unrelated problems: it can play a large number of different games, label images, chat, operate a robot, and more. If we had AGI, how would we know it?

Modeling 364

Modeling Interactive Optimization Deep Learning 364

CIO Business Intelligence

MARCH 19, 2025

Meanwhile, in December, OpenAIs new O3 model, an agentic model not yet available to the public, scored 72% on the same test. Were developing our own AI models customized to improve code understanding on rare platforms, he adds. SS&C uses Metas Llama as well as other models, says Halpin. Devin scored nearly 14%.

Software 143

Software Risk Enterprise Cost-Benefit 143

CIO Business Intelligence

NOVEMBER 25, 2024

AI has the potential to transform industries, but without reliable, relevant, and high-quality data, even the most advanced models will fall short. Data quality is about ensuring that what you feed into the model is accurate, consistent, and relevant to the problem you’re trying to solve. Coverage across platforms for full context.

Data Quality 99

Data Quality ROI Interactive Modeling 99

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. 16% of respondents working with AI are using open source models. A few have even tried out Bard or Claude, or run LLaMA 1 on their laptop.

Enterprise 342

Enterprise Testing Modeling Reporting 342

CIO Business Intelligence

FEBRUARY 6, 2025

The hype around large language models (LLMs) is undeniable. They promise to revolutionize how we interact with data, generating human-quality text, understanding natural language and transforming data in ways we never thought possible. Tableau, Qlik and Power BI can handle interactive dashboards and visualizations.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

CIO Business Intelligence

DECEMBER 18, 2024

Using deep neural networks and Azure GPUs built with NVIDIA technology, startup Riskfuel is developing accelerated models based on AI to determine derivative valuation and risk sensitivity. As new fraud patterns are identified, GenAI is used to create synthetic data and examples used to train enhanced fraud detection models.

Forecasting 105

Forecasting Predictive Analytics Risk Finance 105

CIO Business Intelligence

FEBRUARY 26, 2025

AI agents are powered by gen AI models but, unlike chatbots, they can handle more complex tasks, work autonomously, and be combined with other AI agents into agentic systems capable of tackling entire workflows, replacing employees or addressing high-level business goals. Infrastructure modernization In December, Tray.ai

IT 141

IT Enterprise Interactive Data Quality 141

CIO Business Intelligence

JUNE 13, 2024

Not instant perfection The NIPRGPT experiment is an opportunity to conduct real-world testing, measuring generative AI’s computational efficiency, resource utilization, and security compliance to understand its practical applications. It is not training the model, nor are responses refined based on any user inputs.

Testing 119

Testing Experimentation Data Processing Modeling 119

AWS Big Data

NOVEMBER 27, 2024

After the data is in Amazon Redshift, dbt models are used to transform the raw data into key metrics such as ticket trends, seller performance, and event popularity. Create dbt models in dbt Cloud. Deploy dbt models to Amazon Redshift. Choose Test Connection. Choose Next if the test succeeded.

Data Warehouse 94

Data Warehouse Analytics Testing Modeling 94

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. The model and the data specification become more important than the code. Let’s get everybody to do X.

Machine Learning 364

Machine Learning Statistics Data Quality Data Collection 364

Cloudera

NOVEMBER 13, 2024

Large Language Models (LLMs) will be at the core of many groundbreaking AI solutions for enterprise organizations. These enable customer service representatives to focus their time and attention on more high-value interactions, leading to a more cost-efficient service model.

Cost-Benefit 87

Cost-Benefit Data Processing Machine Learning Testing 87

datapine

APRIL 15, 2020

Your Chance: Want to test an agile business intelligence solution? 17 software developers met to discuss lightweight development methods and subsequently produced the following manifesto : Manifesto for Agile Software Development: Individuals and interactions over processes and tools. Finalize testing. Train end-users.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

CIO Business Intelligence

APRIL 9, 2025

Many of her current projects focus on freeing up staff to focus on personal interactions, which are especially important in the university setting, such as where a student needs extra support to stay in school. Right now, we support 55 large language models, says Gonick. We do millions of ServiceNow tickets every year, he says.

Interactive 108

Interactive Technology Statistics Consulting 108

O'Reilly on Data

SEPTEMBER 17, 2024

Prompts” implies chat and dialogue, but we’re using it for any kind of interaction, even (especially) if you’re writing software that generates or modifies prompts). Chain-of-thought prompts often include some examples of problems, procedures, and solutions that are done correctly, giving the AI a model to emulate.

Modeling 303

Modeling Reporting Sales Testing 303

O'Reilly on Data

JUNE 14, 2024

Generative AI models are trained on large repositories of information and media. They are then able to take in prompts and produce outputs based on the statistical weights of the pretrained models of those corpora. In essence, the latest O’Reilly Answers release is an assembly line of LLM workers.

Metadata 298

Metadata Publishing Data-driven Modeling 298

AWS Big Data

JANUARY 9, 2025

This capability can be useful while performing tasks like backtesting, model validation, and understanding data lineage. You can refer to this metadata layer to create a mental model of how Icebergs time travel capability works. Also, the time travel feature can further mitigate any risks of lookahead bias.

Metadata 107

Metadata Snapshot Cost-Benefit Optimization 107

CIO Business Intelligence

MARCH 5, 2025

The next thing is to make sure they have an objective way of testing the outcome and measuring success. Large software vendors are used to solving the integration problems that enterprises deal with on a daily basis, says Lee McClendon, chief digital and technology officer at software testing company Tricentis.

Testing 99

Testing Measurement Technology Experimentation 99

CIO Business Intelligence

JANUARY 7, 2025

Transformational CIOs continuously invest in their operating model by developing product management, design thinking, agile, DevOps, change management, and data-driven practices. Focusing on classifying data and improving data quality is the offense strategy, as it can lead to improving AI model accuracy and delivering business results.

Digital Transformation 143

Digital Transformation Experimentation Cost-Benefit Strategy 143

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. For example, in a July 2018 survey that drew more than 11,000 respondents, we found strong engagement among companies: 51% stated they already had machine learning models in production.

Machine Learning 279

Machine Learning Technology Deep Learning Data Science 279

O'Reilly on Data

JUNE 27, 2023

Doing so means giving the general public a freeform text box for interacting with your AI model. ” ) With a chatbot, the web form passes an end-user’s freeform text input—a “prompt,” or a request to act—to a generative AI model. The model is not deterministic. That leads us to the next step.

Risk Management 321

Risk Management Risk Management Modeling 321

AWS Big Data

AUGUST 8, 2024

AppsFlyer empowers digital marketers to precisely identify and allocate credit to the various consumer interactions that lead up to an app installation, utilizing in-depth analytics. Additionally, we discuss the thorough testing, monitoring, and rollout process that resulted in a successful transition to the new Athena architecture.

Interactive 118

Interactive Metadata Optimization Testing 118

CIO Business Intelligence

JANUARY 21, 2025

DevOps teams follow their own practices of using continuous integration and continuous deployment (CI/CD) tools to automatically merge code changes and automate testing steps to deploy changes more frequently and reliably. DevOps may push thousands of changes daily, and the CAB process is simply too slow. or Can I look at change collision?

Risk 98

Risk Data-driven Interactive Management 98

O'Reilly on Data

JULY 11, 2023

He’s asking whether large language models eliminate programming as we know it, and he’s excited that the answer is “yes”: eventually, if not in the immediate future. Testing and debugging—well, if you’ve played with ChatGPT much, you know that testing and debugging won’t disappear. But what does this mean in practice?

Testing 267

Testing Software Visualization Interactive 267

O'Reilly on Data

SEPTEMBER 15, 2020

This in turn would increase the platform’s value for users and thus increase engagement, which would result in more eyes to see and interact with ads, which would mean better ROI on ad spend for customers, which would then achieve the goal of increased revenue and customer retention (for business stakeholders).

Advertising 362

Advertising Cost-Benefit ROI Machine Learning 362

Corinium

JUNE 6, 2019

Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments. It is also important to have a strong test and learn culture to encourage rapid experimentation. Therefore, understanding customers for cross and up-sell is paramount.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

CIO Business Intelligence

OCTOBER 24, 2024

The challenge is that these architectures are convoluted, requiring diverse and multiple models, sophisticated retrieval-augmented generation stacks, advanced data architectures, and niche expertise,” they said. The rest of their time is spent creating designs, writing tests, fixing bugs, and meeting with stakeholders. “So

ROI 127

ROI Data-driven Enterprise Experimentation 127

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. Another increasing factor in the future of business intelligence is testing AI in a duel. The predictive models, in practice, use mathematical models to predict future happenings, in other words, forecast engines.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

AWS Big Data

NOVEMBER 22, 2024

Athena plays a critical role in this ecosystem by providing a serverless, interactive query service that simplifies analyzing vast amounts of data stored in Amazon Simple Storage Service (Amazon S3) using standard SQL. Scheduling and automation – dbt Cloud comes with a job scheduler, allowing you to automate the execution of dbt models.

Data Lake 84

Data Lake Data Warehouse Cost-Benefit Data Transformation 84

datapine

SEPTEMBER 1, 2020

Your Chance: Want to test a market research reporting software? On a typical market research results example, you can interact with valuable trends, gain an insight into consumer behavior, and visualizations that will empower you to conduct effective competitor analysis. Your Chance: Want to test a market research reporting software?

Reporting 247

Reporting Marketing KPI Dashboards 247

AWS Big Data

NOVEMBER 19, 2024

This approach simplifies the management of access rights, making sure only authorized users can access and interact with specific documents based on their roles, departments, and other relevant attributes. The process starts by creating a vector based on the question (embedding) by invoking the embedding model.

Management 94

Management Metadata Manufacturing Testing 94

O'Reilly on Data

JULY 15, 2019

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Sources of model risk. Model risk management. Image by Ben Lorica.

Machine Learning 51

Machine Learning Management Enterprise Risk Management 51

O'Reilly on Data

OCTOBER 11, 2022

Selenium , the first tool for automated browser testing (2004), could be programmed to find fields on a web page, click on them or insert text, click “submit,” scrape the resulting web page, and collect results. But the core of the process is simple, and hasn’t changed much since the early days of web testing. What’s required?

Data Integration 353

Data Integration Insurance Dashboards Data-driven 353

O'Reilly on Data

JUNE 24, 2020

The argument is that some systems are intrinsically difficult to model. There are too many causes and too many effects that interact with each other in ways that are difficult to predict or even understand. For COVID-19 and all the problems we’re facing, that’s the real work, the hard work that can’t wait for the modelling to be done.

Measurement 335

Measurement Testing Interactive Modeling 335