CIO Business Intelligence

DECEMBER 20, 2023

This has spurred interest around understanding and measuring developer productivity, says Keith Mann, senior director, analyst, at Gartner. Therefore, engineering leadership should measure software developer productivity, says Mann, but also understand how to do so effectively and be wary of pitfalls.

Measurement 116

Measurement Software IT Metrics 116

AWS Big Data

DECEMBER 7, 2023

In this post, we outline planning a POC to measure media effectiveness in a paid advertising campaign. We chose to start this series with media measurement because “Results & Measurement” was the top ranked use case for data collaboration by customers in a recent survey the AWS Clean Rooms team conducted.

Measurement 92

Measurement Advertising Testing Data-driven 92

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 106

Digital Transformation Risk Strategy Testing 106

Cloudera

OCTOBER 20, 2021

As governments gather to push forward climate and renewable energy initiatives aligned with the Paris Agreement and the UN Framework Convention on Climate Change, financial institutions and asset managers will monitor the event with keen interest. What are the key climate risk measurements and impacts?

Risk 80

Risk Modeling Risk Management Measurement 80

CIO Business Intelligence

AUGUST 4, 2023

In collaboration with our peers, we have a solid business sense that carefully weighs innovation and risk in order to gain valuable ROI while protecting the organization from all forms of risk associated with each project. If reversible, then there’s clearly less risk. What’s new and different today?

Risk 88

Risk Risk Management ROI Technology 88

O'Reilly on Data

MAY 14, 2020

In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. In this article, we shift our focus to the AI Product Manager’s skill set, as it is applied to day to day work in the design, development, and maintenance of AI products. The AI Product Pipeline.

Management 363

Management Experimentation B2B Machine Learning 363

O'Reilly on Data

JUNE 15, 2023

Should we risk loss of control of our civilization?” If we want prosocial outcomes, we need to design and report on the metrics that explicitly aim for those outcomes and measure the extent to which they have been achieved. And they are stress testing and “ red teaming ” them to uncover vulnerabilities.

Metrics 292

Metrics Reporting Measurement Finance 292

datapine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 5) How Do You Measure Data Quality? However, with all good things comes many challenges and businesses often struggle with managing their information in the correct way. Enters data quality management. What Is Data Quality Management (DQM)? Table of Contents.

Data Quality 241

Data Quality Metrics Data-driven Management 241

datapine

MARCH 8, 2021

Your Chance: Want to test a healthcare reporting software for free? Preventative management. This information proved invaluable in offering tailored therapy while taking all-important measures to reduce suicide rates. Your Chance: Want to test a healthcare reporting software for free? What Is Healthcare Reporting?

Reporting 198

Reporting KPI Management Cost-Benefit 198

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

Decision Management Solutions

APRIL 23, 2019

, in which he states there are only three levers of value in insurance: Sell More, Manage Risk Better (aka underwriting and adjusting), and Cost Less to Operate. Let’s dive into greater detail on the second lever – Manage Risk Better. Insurers can also manage risk more effectively through continuous improvement.

Insurance 69

Insurance Risk Technology Management 69

IBM Big Data Hub

APRIL 9, 2024

It would be a huge challenge for a human to manage these models, so we use the autoAI feature of watsonx to help us build the right model and pick the best projection.” We also measure response time since this is a near real-time system. Watsonx.governance makes it easy to manage and deploy all these models effectively.”

Management 79

Management IT Machine Learning Metrics 79

CIO Business Intelligence

JUNE 9, 2023

It’s a time-tested truth: Getting a head start improves outcomes. Such is the case with a data management strategy. That gap is becoming increasingly apparent because of artificial intelligence’s (AI) dependence on effective data management. The benefits of data management are universal. The second best time is now.”

Strategy 105

Strategy Management Key Performance Indicator ROI 105

DataKitchen

SEPTEMBER 20, 2021

Figure 2: The DataKitchen Platform helps you reduce time spent managing errors and executing manual processes from about half to 15%. The other 78% of their time is devoted to managing errors, manually executing production pipelines and other supporting activities. Start with just a few critical tests and build gradually.

Testing 246

Testing Metrics Measurement Dashboards 246

CIO Business Intelligence

JUNE 15, 2023

Despite headlines warning that artificial intelligence poses a profound risk to society , workers are curious, optimistic, and confident about the arrival of AI in the enterprise, and becoming more so with time, according to a recent survey by Boston Consulting Group (BCG). For many, their feelings are based on sound experience.

Management 103

Management Experimentation Optimization Enterprise 103

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools.

Management 339

Management Machine Learning Experimentation Metrics 339

DataKitchen

MARCH 5, 2024

The Patchwork Quilt: Fixes by Another Team Another team may be picking up the slack, fixing and patching errors before they become visible to higher management or external stakeholders. The Stakeholder Confidence Crisis Relying on hope as a data accuracy and integrity strategy is fraught with risks. It’s just a matter of time.

Data Quality 146

Data Quality Measurement Testing Data-driven 146

CIO Business Intelligence

AUGUST 16, 2023

Today, state-owned Svevia is the country’s largest company in the operation and maintenance of roads and bridges, and manages over 50% of the road network yet, just like in the construction industry, it’s been relatively late to digitization. In some areas, they’re testing the use of roadside sensors, weather data, and data from vehicles.

Risk 77

Risk Cost-Benefit Digital Transformation Internet of Things 77

O'Reilly on Data

JULY 28, 2020

The Core Responsibilities of the AI Product Manager. Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. Product managers for AI must satisfy these same responsibilities, tuned for the AI lifecycle.

Marketing 363

Marketing Experimentation Metrics Testing 363

AWS Big Data

AUGUST 14, 2023

At the same time, unstructured approaches to data mesh management that don’t have a vision for what types of products should exist and how to ensure they are developed are at high risk of creating the same effect through simple neglect. How do we define “risk” and “value” in the context of data products, and how can we measure this?

Management 79

Management Risk Measurement Optimization 79

DataRobot Blog

MAY 26, 2022

To start with, SR 11-7 lays out the criticality of model validation in an effective model risk management practice: Model validation is the set of processes and activities intended to verify that models are performing as expected, in line with their design objectives and business uses.

Risk 52

Risk Modeling Metrics Business Objectives 52

IBM Big Data Hub

MAY 28, 2024

A data protection strategy is a set of measures and processes to safeguard an organization’s sensitive information from data loss and corruption. It can also help them reduce vulnerabilities and ensure data is efficiently managed, compliant with regulations, and not at risk of misuse or loss.

Strategy 82

Strategy Measurement Risk Cost-Benefit 82

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

JULY 17, 2023

Cloud infrastructure is especially sensitive, as many critical applications are at risk, such as customer-facing applications. Its WAAP security platform enables organizations to implement effective security into modern web applications, innovate faster and mitigate risks with its unified, multi-layer approach. Network Security

Management 90

Management Data Processing Risk Digital Transformation 90

CIO Business Intelligence

MARCH 3, 2024

One component of corporate IT that has long been ‘in range’ for cyber criminals that is often overlooked when protection measures are being put in place are multifunction printers – widely used in almost every organisation. Doing penetration testing.

IT 97

IT Measurement Risk Testing 97

CIO Business Intelligence

AUGUST 28, 2023

Agile project management definition Agile project management is a methodology used primarily in software development that favors flexibility and collaboration, incorporating customer feedback throughout the project life cycle.

Management 93

Management Software Testing Risk 93

CIO Business Intelligence

NOVEMBER 6, 2023

This makes it more critical than ever to adopt strong security measures to protect sensitive information and infrastructure. This can come in the form of appending a Privileged Access Management solution to supplement your company’s directory like IBM’s Red Hat Directory or Microsoft’s Active Directory.

Risk 121

Risk Measurement Cost-Benefit Strategy 121

CIO Business Intelligence

JUNE 13, 2024

Ryan O’Leary: “The big ethical challenges are the risks of misinformation, biases, and potential privacy breaches. Safeguards need to be in place when testing such powerful new tools.” RO: “Companies can start by rigorously vetting training data to make sure it is diverse and representative, thereby reducing the risk of bias.

Risk 104

Risk Forecasting Finance Machine Learning 104

CIO Business Intelligence

FEBRUARY 13, 2023

Six Sigma is a quality management methodology used to help businesses improve current processes, products, or services by discovering and eliminating defects. Six Sigma is specifically designed to help large organizations with quality management. What is Six Sigma? Six Sigma was trademarked by Motorola in 1993.

Management 72

Management Statistics Manufacturing Measurement 72

CIO Business Intelligence

JUNE 7, 2022

It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. To ensure robust analysis, data analytics teams leverage a range of data management techniques, including data mining, data cleansing, data transformation, data modeling, and more.

Data Analytics 125

Data Analytics Diagnostic Analytics Management Analytics 125

O'Reilly on Data

JUNE 16, 2020

The quality of the decision is based on known information and an informed risk assessment, while chance involves hidden information and the stochasticity of the world. Consider risk not only in terms of likelihood but also in terms of the impact of your decisions. Risk, Probability, Impact, and Decisions.

Uncertainty 282

Uncertainty Testing Risk Reporting 282

Cloudera

JUNE 3, 2024

Cloudera’s AI Inference service uniquely streamlines the deployment and management of large-scale AI models, delivering high performance and efficiency while maintaining strict privacy and security standards.

Optimization 80

Optimization Enterprise Data Architecture Modeling 80

Jet Global

JUNE 17, 2021

A large US-headquartered multinational manufacturer with sales in 100 countries wanted to manage operational transfer pricing at year-end with more accuracy and transparency, and to move toward a position where it could analyze the meaning behind its reported numbers in more detail. Managing Data Integrity. The Need to Free Up Time.

Risk 98

Risk Recreation/Entertainment Forecasting Manufacturing 98

IBM Big Data Hub

MAY 24, 2024

The Clearing Corporation of India Limited (CCIL) recently recommended (link resides outside ibm.com) IBM® MQ as the messaging software requirement for all its members to manage the triparty repo dealing system. This reduces the risk of errors and miscommunications, which can lead to significant losses in the financial industry.

Measurement 88

Measurement Software Marketing Risk 88

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Smart Data Collective

OCTOBER 8, 2023

A growing number of companies are recognizing that they need to take proactive measures to help bolster their data security. Software companies are among those most heavily affected, so they are taking dramatic measures. And today, we’ll talk about the most significant of these risks. However, they also pose a considerable risk.

Software 108

Software IoT Risk Internet of Things 108

DataKitchen

NOVEMBER 18, 2022

As he thinks through the various journeys that data take in his company, Jason sees that his dashboard idea would require extracting or testing for events along the way. Data and tool tests. Observability users are then able to see and measure the variance between expectations and reality during and after each run.

Testing 130

Testing Statistics Measurement Metrics 130