CIO Business Intelligence

SEPTEMBER 9, 2024

But Stephen Durnin, the company’s head of operational excellence and automation, says the 2020 Covid-19 pandemic thrust automation around unstructured input, like email and documents, into the spotlight. “We This was exacerbated by errors or missing information in documents provided by customers, leading to additional work downstream. “We

Finance 118

Finance Dashboards Sales Testing 118

CIO Business Intelligence

OCTOBER 17, 2024

According to the indictment, Jain’s firm provided fraudulent certification documents during contract negotiations in 2011, claiming that their Beltsville, Maryland, data center met Tier 4 standards, which require 99.995% uptime and advanced resilience features. “If By then, the Commission had spent $10.7 million on the contract​. “In

Broadcasting 122

Broadcasting Risk Reporting Measurement 122

datapine

APRIL 15, 2020

Your Chance: Want to test an agile business intelligence solution? Working software over comprehensive documentation. Business intelligence is moving away from the traditional engineering model: analysis, design, construction, testing, and implementation. Test BI in a small group and deploy the software internally.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

CIO Business Intelligence

JANUARY 14, 2025

Documentation and diagrams transform abstract discussions into something tangible. By articulating fitness functions automated tests tied to specific quality attributes like reliability, security or performance teams can visualize and measure system qualities that align with business goals. Shawn McCarthy 3.

Enterprise 120

Enterprise Technology Metrics Measurement 120

O'Reilly on Data

NOVEMBER 28, 2023

Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. And there are tools for archiving and indexing prompts for reuse, vector databases for retrieving documents that an AI can use to answer a question, and much more. Only 4% pointed to lower head counts.

Enterprise 343

Enterprise Testing Modeling Reporting 343

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. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk.

Machine Learning 52

Machine Learning Management Enterprise Risk Management 52

CIO Business Intelligence

AUGUST 21, 2024

Adding smarter AI also adds risk, of course. “At The big risk is you take the humans out of the loop when you let these into the wild.” When it comes to security, though, agentic AI is a double-edged sword with too many risks to count, he says. “We That means the projects are evaluated for the amount of risk they involve.

Risk 136

Risk Insurance Cost-Benefit Software 136

CIO Business Intelligence

MAY 21, 2025

Sufficiently accessible and accurate tools could deliver operational improvements and revenue, as well as optimized costs and reduced risks in many areas of business decision making. Fraud detection and cybersecurity can do more extreme testing with synthetic data, he says.

Statistics 104

Statistics Testing Modeling Risk 104

CIO Business Intelligence

APRIL 30, 2025

At ServiceNow, theyre infusing agentic AI into three core areas: answering customer or employee requests for things like technical support and payroll info; reducing workloads for teams in IT, HR, and customer service; and boosting developer productivity by speeding up coding and testing. For others, integration remains the biggest obstacle.

IT 139

IT Sales Cost-Benefit Data-driven 139

CIO Business Intelligence

JANUARY 30, 2025

These changes can expose businesses to risks and vulnerabilities such as security breaches, data privacy issues and harm to the companys reputation. It also includes managing the risks, quality and accountability of AI systems and their outcomes. AI governance is critical and should never be just a regulatory requirement.

Testing 93

Testing Metrics Cost-Benefit Modeling 93

Smart Data Collective

MAY 7, 2023

million —and organizations are constantly at risk of cyber-attacks and malicious actors. In order to protect your business from these threats, it’s essential to understand what digital transformation entails and how you can safeguard your company from cyber risks. What is cyber risk?

Digital Transformation 129

Digital Transformation Risk Strategy Testing 129

O'Reilly on Data

DECEMBER 12, 2019

1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. These recommendations are based on our experience, both as a data scientist and as a lawyer, focused on managing the risks of deploying ML. 6] Debugging may focus on a variety of failure modes (i.e., Sensitivity analysis.

Machine Learning 285

Machine Learning Modeling Testing Risk Management 285

DataRobot Blog

APRIL 29, 2022

This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks.

Risk 111

Risk Modeling IT Risk Management 111

CIO Business Intelligence

FEBRUARY 21, 2025

Integration with Oracles systems proved more complex than expected, leading to prolonged testing and spiraling costs, the report stated. Change requests affecting critical aspects of the solution were accepted late in the implementation cycle, creating unnecessary complexity and risk.

Reporting 91

Reporting Risk Testing Risk Management 91

CIO Business Intelligence

FEBRUARY 26, 2025

But when an agent whose primary purpose is understanding company documents and tries to speak XML, it can make mistakes. If an agent needs to perform an action on an AWS instance, for example, youll actually pull in the data sources and API documentation you need, all based on the identity of the person asking for that action at runtime.

IT 141

IT Enterprise Interactive Data Quality 141

CIO Business Intelligence

JANUARY 30, 2025

particular, companies that use AI systems can share their voluntary commitments to transparency and risk control. At least half of the current AI Pact signatories (numbering more than 130) have made additional commitments, such as risk mitigation, human oversight and transparency in generative AI content.

Enterprise 128

Enterprise Risk Reporting Measurement 128

Rocket-Powered Data Science

FEBRUARY 15, 2023

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? Keep it agile, with short design, develop, test, release, and feedback cycles: keep it lean, and build on incremental changes. Test early and often. Test and refine the chatbot.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

AWS Big Data

OCTOBER 11, 2024

By implementing a robust snapshot strategy, you can mitigate risks associated with data loss, streamline disaster recovery processes and maintain compliance with data management best practices. Testing and development – You can use snapshots to create copies of your data for testing or development purposes.

Snapshot 110

Snapshot Dashboards Management Testing 110

O'Reilly on Data

JULY 11, 2023

Programmers who work for those companies risk losing their jobs to AI. Testing and debugging—well, if you’ve played with ChatGPT much, you know that testing and debugging won’t disappear. What does this mean for people who earn their living from writing software? AIs generate incorrect code, and that’s not going to end soon.

Testing 269

Testing Software Visualization Interactive 269

AWS Big Data

MAY 2, 2025

They consist of: A data sample of the documents you want to index. A pipeline of processors that apply transforms on ingested documents. An index constructed from the processed documents. The application is also untouched for a decade, so we aim to avoid changes to client-side code to reduce risk and implementation effort.

Machine Learning 86

Machine Learning Visualization Dashboards Metadata 86

O'Reilly on Data

SEPTEMBER 19, 2023

A single document may represent thousands of features. You can see a simulation as a temporary, synthetic environment in which to test an idea. Millions of tests, across as many parameters as will fit on the hardware. “Here’s our risk model. The solution led us to the next structural evolution.

Machine Learning 341

Machine Learning Testing Modeling Cost-Benefit 341

CIO Business Intelligence

MARCH 4, 2025

In fact, successful recovery from cyberattacks and other disasters hinges on an approach that integrates business impact assessments (BIA), business continuity planning (BCP), and disaster recovery planning (DRP) including rigorous testing. See also: How resilient CIOs future-proof to mitigate risks.)

Testing 65

Testing Risk Consulting Risk Management 65

O'Reilly on Data

MARCH 26, 2024

It’s ironic that, in this article, we didn’t reproduce the images from Marcus’ article because we didn’t want to risk violating copyright—a risk that Midjourney apparently ignores and perhaps a risk that even IEEE and the authors took on!) Because, in some sense, hallucination is all LLMs do. They are dream machines.

Modeling 325

Modeling Machine Learning Risk Advertising 325

CIO Business Intelligence

APRIL 8, 2025

Fragmented systems, inconsistent definitions, legacy infrastructure and manual workarounds introduce critical risks. The decisions you make, the strategies you implement and the growth of your organizations are all at risk if data quality is not addressed urgently. Manual entries also introduce significant risks.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

O'Reilly on Data

MARCH 23, 2023

What is it, how does it work, what can it do, and what are the risks of using it? It’s by far the most convincing example of a conversation with a machine; it has certainly passed the Turing test. Be very careful about documents that require any sort of precision. ChatGPT can be very convincing even when it is not accurate.

IT 349

IT Modeling Testing Risk 349

Cloudera

SEPTEMBER 28, 2020

They have dev, test, and production clusters running critical workloads and want to upgrade their clusters to CDP Private Cloud Base. Customer Environment: The customer has three environments: development, test, and production. Test and QA. Test and QA. Review the Upgrade document topic for the supported upgrade paths.

Testing 132

Testing Metadata Risk Data Science 132

IBM Big Data Hub

SEPTEMBER 12, 2023

The UK government’s Ecosystem of Trust is a potential future border model for frictionless trade, which the UK government committed to pilot testing from October 2022 to March 2023.

Testing 83

Testing Modeling Cost-Benefit Consulting 83

CIO Business Intelligence

DECEMBER 11, 2024

Without this setup, there is a risk of building models that are too slow to respond to customers, exhibit training-serving skew over time and potentially harm customers due to lack of production model monitoring. Data governance needs to follow a similar path, transitioning from policy documents and confluence pages to data policy as code.

Management 111

Management Data Governance Data Science Reporting 111

Domino Data Lab

AUGUST 6, 2021

All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards. The primary focus of model governance involves tracking, testing and auditing. First is the data the model is using.

Machine Learning 145

Machine Learning Modeling Testing Data Science 145

O'Reilly on Data

JUNE 14, 2024

And Miso had already built an early LLM-based search engine using the open-source BERT model that delved into research papers—it could take a query in natural language and find a snippet of text in a document that answered that question with surprising reliability and smoothness.

Metadata 302

Metadata Publishing Data-driven Modeling 302

O'Reilly on Data

MARCH 24, 2020

John Myles White , data scientist and engineering manager at Facebook, wrote: “The biggest risk I see with data science projects is that analyzing data per se is generally a bad thing. The assumed value of data is a myth leading to inflated valuations of start-ups capturing said data. Let’s get everybody to do X.

Machine Learning 364

Machine Learning Statistics Data Quality Data Collection 364

DataKitchen

JANUARY 18, 2023

Good testing, like exercise and veganism, is the subject of fervent talk and half-hearted action. There are lots of reasons good people test inadequately. Testing is intrinsic to the job. . By automating your tests, then running them with each refresh, you build in safety valves for your data pipeline. . Of course not.

Testing 130

Testing Data-driven Risk Strategy 130

Smart Data Collective

SEPTEMBER 17, 2020

Financial institutions such as banks have to adhere to such a practice, especially when laying the foundation for back-test trading strategies. Some prominent banking institutions have gone the extra mile and introduced software to analyze every document while recording any crucial information that these documents may carry.

Big Data 145

Big Data Finance Risk Management Risk 145

erwin

OCTOBER 8, 2020

And you can’t risk false starts or delayed ROI that reduces the confidence of the business and taint this transformational initiative. But even with the “need for speed” to market, new applications must be modeled and documented for compliance, transparency and stakeholder literacy.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

Smart Data Collective

DECEMBER 26, 2022

Before prioritizing your threats, risks, and remedies, determine the rules and regulations that your company is obliged to follow. Prioritize Your Risks and Assets. Once you are done with enlisting your threat vectors, it is important to go through a risk assessment and create a prioritization list of your assets.

Strategy 137

Strategy Testing Risk Software 137

DataKitchen

FEBRUARY 2, 2023

This will drive a new consolidated set of tools the data team will leverage to help them govern, manage risk, and increase team productivity. Enterprises are more challenged than ever in their data sprawl , so reducing risk and lowering costs drive software spending decisions. What will exist at the end of 2025?

Metadata 130

Metadata Testing Data Science Risk 130

DataKitchen

DECEMBER 6, 2022

The document they wrote is exceptionally close to what we see in the market and what our products do ! This document is essential because buyers look to Gartner for advice on what to do and how to buy IT software. T est Automation : Business rules validation, test scripts management, test data management.

Software 130

Software Marketing Data Lake Testing 130