CIO Business Intelligence

MARCH 13, 2024

We did side-by-side testing,” he says. AI models are able to present best practice code systems to help junior developers learn and hone their skills.” In testing, gen AI was also particularly good at generating test cases and creating dummy data for testing.

IT 126

IT Consulting Testing Cost-Benefit 126

Insight

FEBRUARY 19, 2020

My goal here is not to improve upon the current prediction algorithms but rather to describe a model I devised, called ReelRisk , that uses random resampling to generate a range of predictions which can then be used as a risk assessment tool to determine early on whether to fund a movie.

Risk 67

Risk ROI Modeling Metrics 67

Cloudera

AUGUST 25, 2020

One of the key takeaways from recent times that should be considered into the future, is that banks need to rethink how they look at tail risk or extreme events that rarely happen. . Machine Learning and AI provide powerful predictive engines that rely on historical data to fit the models.

Prescriptive Analytics 70

Prescriptive Analytics Technology Machine Learning Risk 70

CIO Business Intelligence

APRIL 13, 2023

Gartner projects that spending on information security and risk management products and services will grow 11.3% To better focus security spend, some chief information security officers (CISOs) are shifting their risk assessments from IT systems to the data, applications, and processes that keep the business going.

IT 111

IT Cost-Benefit Risk Consulting 111

AWS Big Data

AUGUST 14, 2023

Taken together, the posts in this series lay out some possible operating models for data mesh within an organization. Earlier in their lifecycle, data products may be measured by alternative metrics, including adoption (number of consumers) and level of activity (releases, interaction with consumers, and so on).

Management 76

Management Risk Measurement Optimization 76

datapine

AUGUST 29, 2022

And with that understanding, you’ll be able to tap into the potential of data analysis to create strategic advantages, exploit your metrics to shape them into stunning business dashboards , and identify new opportunities or at least participate in the process. Product/market fit is THE most important factor to get right.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Grooper

OCTOBER 23, 2019

With the increasing value of data and more tools to process and analyze information than ever before, companies with information governance and master data model programs are outpacing their peers. Now is the time to get organized, and view information management as the single most important initiative for business growth and innovation.

Metrics 59

Metrics Measurement Strategy Optimization 59

CIO Business Intelligence

JULY 11, 2023

In recent years, we have witnessed a tidal wave of progress and excitement around large language models (LLMs) such as ChatGPT and GPT-4. By deploying the LLM within their own VPC, the company can benefit from the AI’s insights without risking the exposure of their valuable data.

Modeling 71

Modeling Testing Experimentation Risk Management 71

IBM Big Data Hub

JULY 12, 2023

Team members discuss possible risks, analyze the risk impact of each one and propose courses of action to increase their overall preparedness. Plans should be tested at least once annually, and new risk assessments performed. RTO is usually measured with a simple time metric, such as days, hours or minutes.

Risk 40

Risk Cost-Benefit Internet of Things Testing 40

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 82

Data Architecture Risk Management Risk Management 82

DataRobot Blog

JULY 21, 2022

Data scientists need to understand the business problem and the project scope to assess feasibility, set expectations, define metrics, and design project blueprints. Outline clear metrics to measure success. Document assumptions and risks to develop a risk management strategy. Define project scope.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

IBM Big Data Hub

FEBRUARY 22, 2024

Earning trust in the outputs of AI models is a sociotechnical challenge that requires a sociotechnical solution. There must be a concerted effort to make these principles a reality through consideration of the functional and non-functional requirements in the models and the governance systems around those models.

Metadata 102

Metadata Measurement Risk Modeling 102

CIO Business Intelligence

MARCH 5, 2024

CIOs must also partner with CISOs, legal, human resources, and business leaders to build awareness of policies and develop a generative AI risk management strategy. CIOs and IT leaders are at the center and must decide what copilots to test, who should receive access, and whether experiments are delivering business value.

Cost-Benefit 115

Cost-Benefit Advertising Experimentation Software 115

IBM Big Data Hub

APRIL 4, 2024

By connecting workflow management, centralizing data management , and fostering collaboration and communication, BPM enables organizations to remain competitive by providing access to accurate and timely data. BPM can also provide real-time visibility into claim status and performance metrics.

Management 60

Management Cost-Benefit Metrics Consulting 60

Andrew White

JANUARY 11, 2021

How do you think Technology Business Management plays into this strategy? Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. Value Management or monetization. Product Management. Governance. Architecture.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

O'Reilly on Data

OCTOBER 18, 2022

What if a named entity recognition (NER) system, based on a cutting-edge large language model (LLM), fails for Chinese, Cyrillic, or Arabic text? As AI technologies are adopted more broadly in security and other high-risk applications, we’ll all need to know more about AI audit and risk management. For our audits, BNH.AI

Risk Management 291

Risk Management Risk Testing Measurement 291

IBM Big Data Hub

JULY 28, 2023

In response, enterprises have made vulnerability management a key component of their cyber risk management strategies. The vulnerability management lifecycle offers a formal model for effective vulnerability management programs in an ever-changing cyberthreat landscape.

Management 69

Management Metrics Risk Measurement 69

Cloudera

MAY 18, 2021

In this article, we will be using synthetic market data generated by an agent-based model (ABM) developed by Simudyne. Rather than a top-down approach, ABMs model autonomous actors (or agents) within a complex system — for example, different kinds of buyers and sellers in financial markets. Intraday VaR. Image Source: [link].

Risk 94

Risk Marketing Risk Management Data-driven 94

DataRobot Blog

DECEMBER 20, 2022

Yet, in the digital transformation era, the pricing and assessment of real estate assets is more difficult than described by brokers’ presentations, valuation reports, and traditional analytical approaches like hedonic models. We’ll then empirically test this assumption based on an example of real estate asset assessment.

Management 59

Management Machine Learning Optimization Modeling 59

Cloudera

MARCH 18, 2021

A revised internal models approach (IMA) combined with an overhaul of the standardized approach (SA). A means of incorporating the risk of market illiquidity, including liquidity horizons that range from 10 to 250 days. Continuous monitoring will be required, and banks will need to conduct back-testing to ensure accuracy.

Risk 55

Risk Machine Learning Risk Management Measurement 55

CIO Business Intelligence

FEBRUARY 3, 2023

More recently, The Royal Mint has evolved its business model in the face of declining cash usage, from its core business of coins and metal manufacturing through to bullion trading, a new consumer business and jewellery line, as well as tentative steps into digital gold and recycling e-waste.

IT 52

IT Experimentation Scorecard Digital Transformation 52

CIO Business Intelligence

MAY 17, 2022

The company is on a mission to revolutionize the banking industry through technology and data and serves as a model for harnessing the power of data for growth. . A few years ago, the leadership realized that the banking industry is going to be dominated by great tech companies that manage risk exceptionally well.

ROI 52

ROI Risk Marketing Modeling 52

Alation

FEBRUARY 8, 2022

Data mesh inverts the common model of having a centralized team (such as a data engineering team), who manage and transform data for wider consumption. Data mesh supporters argue that this centralized model is no longer tenable in the expanding data universe of the enterprise. That model has failed to support rapid data growth.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. Models trained in DataRobot can also be easily deployed to Azure Machine Learning, allowing users to host models easier in a secure way.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59