O'Reilly on Data

OCTOBER 13, 2020

The field of AI product management continues to gain momentum. As the AI product management role advances in maturity, more and more information and advice has become available. One area that has received less attention is the role of an AI product manager after the product is deployed. I/O validation.

Management 240

Management Metrics Machine Learning Modeling 240

Rocket-Powered Data Science

FEBRUARY 15, 2023

Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. These changes may include requirements drift, data drift, model drift, or concept drift. encouraging and rewarding) a culture of experimentation across the organization.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

DataRobot Blog

DECEMBER 6, 2022

Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

CIO Business Intelligence

OCTOBER 4, 2022

Business leaders, recognizing the importance of elevated customer experiences, are looking to the CIO and their IT teams to help harness the power of data, predictive analytics, and cloud resources to create more engaging, seamless experiences for customers. Embed CX into your data strategy. Consider three key areas of focus: 1.

Data-driven 98

Data-driven Machine Learning Interactive Predictive Analytics 98

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 361

Marketing Experimentation Metrics Testing 361

CIO Business Intelligence

MAY 9, 2024

Its ability to automate routine processes and provide data-driven insights helps create a conducive environment for deep work. Experimentation drives momentum: How do we maximize the value of a given technology? Via experimentation. Example: Creating a tailored customer relationship management (CRM) application.

Enterprise 97

Enterprise Experimentation Sales Optimization 97

DataRobot Blog

JANUARY 12, 2023

Organizations that want to accelerate AI and generate significant business impact are now able to deliver augmented intelligence at scale with DataRobot Dedicated Managed AI Cloud and Google Cloud. Offering a seamless workflow, the platform integrates with the cloud and data sources in the ecosystem today. Delivering more than 1.4

Management 59

Management Data-driven ROI Cost-Benefit 59

CIO Business Intelligence

FEBRUARY 16, 2024

ADP’s aggressive digital transformation has not only cut costs and enabled more innovation but, most importantly, it has facilitated the payroll administrator’s evolution into a human capital management (HCM) service provider, which provides services to its customers from “hire to retire,” Nagrath says.

Digital Transformation 109

Digital Transformation Experimentation Cost-Benefit Machine Learning 109

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch presented “ Product Management for AI ” at Rev. Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Session Summary. It is similar to R&D.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. What Is Model Risk? Types of Model Risk. Model implementation.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

O'Reilly on Data

OCTOBER 19, 2021

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. Why: Data Makes It Different. Much has been written about struggles of deploying machine learning projects to production. This approach is not novel.

IT 342

IT Testing Experimentation Software 342

CIO Business Intelligence

NOVEMBER 4, 2022

Rigid requirements to ensure the accuracy of data and veracity of scientific formulas as well as machine learning algorithms and data tools are common in modern laboratories. When Bob McCowan was promoted to CIO at Regeneron Pharmaceuticals in 2018, he had previously run the data center infrastructure for the $81.5

Data Lake 109

Data Lake IT Experimentation Data-driven 109

DataKitchen

DECEMBER 1, 2022

Data Team members, have you ever felt overwhelmed? At DataKitchen, we’re trying to give people the tools and best practices to help them succeed with data and keep their job enjoyable and rewarding. With DataOps, data teams can ship data analytics systems faster and more confidently. So don’t wait any longer.

Experimentation 130

Experimentation Data-driven Risk Optimization 130

DataRobot Blog

MARCH 16, 2023

To deliver on this new approach, one that we are calling Value-Driven AI , we set out to design new and enhanced platform capabilities that enable customers to realize value faster. Best-Practice Compliance and Governance: Businesses need to know that their Data Scientists are delivering models that they can trust and defend over time.

Experimentation 98

Experimentation Data-driven Modeling Metadata 98

datapine

MAY 20, 2020

To ensure that your customer-facing communications and efforts are constantly improving and evolving, investing in customer relationship management (CRM) is vital. At its core, CRM dashboard software is a smart vessel for data analytics and business intelligence – digital innovation that hosts a wealth of insightful CRM reports.

Dashboards 265

Dashboards Reporting KPI Visualization 265

AWS Big Data

FEBRUARY 12, 2024

Objective Gupshup wanted to build a messaging analytics platform that provided: Build a platform to get detailed insights, data, and reports about WhatsApp/SMS campaigns and track the success of every text message sent by the end customers. Additionally, extract, load, and transform (ELT) data processing is sped up and made easier.

Data Warehouse 102

Data Warehouse Analytics Snapshot Cost-Benefit 102

DataKitchen

JANUARY 20, 2021

As DataOps activity takes root within an enterprise, managers face the question of whether to build centralized or decentralized DataOps capabilities. We’ll also discuss building DataOps expertise around the data organization, in a decentralized fashion, using DataOps centers of excellence (COE) or DataOps Dojos. Deploy to production.

Metrics 243

Metrics Experimentation Measurement Testing 243

Rocket-Powered Data Science

JULY 6, 2021

In at least one way, it was not different, and that was in the continued development of innovations that are inspired by data. This steady march of data-driven innovation has been a consistent characteristic of each year for at least the past decade.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

CIO Business Intelligence

DECEMBER 19, 2023

After all, every department is pressured to drive efficiencies and is clamoring for automation, data capabilities, and improvements in employee experiences, some of which could be addressed with generative AI. As every CIO can attest, the aggregate demand for IT and data capabilities is straining their IT leadership teams.

Digital Transformation 140

Digital Transformation Unstructured Data Machine Learning Risk Management 140

CIO Business Intelligence

FEBRUARY 14, 2024

Fundamentals like security, cost control, identity management, container sprawl, data management, and hardware refreshes remain key strategic areas for CIOs to deal with. Data due diligence Generative AI especially has particular implications for data security, Mann says.

IT 142

IT Metadata Data-driven Management 142

Insight

APRIL 28, 2020

Originally posted on Open Data Science (ODSC). In this article, we share some data-driven advice on how to get started on the right foot with an effective and appropriate screening process. Designing a Data Science Interview Onsite interviews are indispensable, but they are time-consuming.

Data-driven 53

Data-driven Data Science Experimentation Measurement 53

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity.

Testing 300

Testing Machine Learning Consulting Data Quality 300

CIO Business Intelligence

JUNE 16, 2022

By George Trujillo, Principal Data Strategist, DataStax. Any enterprise data management strategy has to begin with addressing the 800-pound gorilla in the corner: the “innovation gap” that exists between IT and business teams. This scarcity of quality data might feel akin to dying of thirst in the middle of the ocean.

IT 122

IT Experimentation IoT Data-driven 122

DataKitchen

MARCH 8, 2023

These three objectives are interconnected and essential to the success of any data team. Delivering insight to customers without error is critical to the success of any data team. The team must ensure that the data they are working with is clean and accurate and that the analysis created from it is rigorous and reliable.

Analytics 130

Analytics Manufacturing Data-driven Data Analytics 130

CIO Business Intelligence

APRIL 24, 2024

Sales and marketing departments have long been at the forefront of embracing new technologies, and according to data provided by the Alexander Group, a revenue consultancy, 80% of hundreds of survey responses detailed that CROs have formally invested in AI for their marketing teams. And revenue operations is part of that.

Sales 123

Sales Finance Experimentation Cost-Benefit 123

DataRobot Blog

NOVEMBER 15, 2022

Organizations are looking to deliver more business value from their AI investments, a hot topic at Big Data & AI World Asia. At the well-attended data science event, a DataRobot customer panel highlighted innovation with AI that challenges the status quo. Automate with Rapid Iteration to Get to Scale and Compliance.

Big Data 52

Big Data Experimentation Data-driven Machine Learning 52

CIO Business Intelligence

MAY 30, 2024

Case in point is its new conversational assistant copilot, AlpiGPT an internal search engine of corporate data that can personalize travel packages and quickly answer questions, says company CIO, Francesco Ciuccarelli. Employees are even calling it a trusted colleague. At first, I was wary of generative AI,” he says.

Cost-Benefit 96

Cost-Benefit Sales Modeling Experimentation 96

CIO Business Intelligence

NOVEMBER 15, 2022

Gartner’s managing VP Mary Mesaglio said she remained optimistic for tech investments, with the latest crisis offering CIOs yet another opportunity to “make the difference”. But released the next day, the 2023 Gartner CIO and Technology Executive Survey revealed that EMEA-based CIOs expect IT budgets to increase 4.4% global inflation rate.

Digital Transformation 138

Digital Transformation Experimentation Risk Metrics 138

DataRobot

JANUARY 20, 2022

While ICSs have been operating in shadow-format for a number of years, this long-awaited shift determines that health and care delivery in England is regionally managed and focused around the needs of the local population. Key Data Challenges for Integrated Care Systems in 2022. Building data communities. National guidance.

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145

CIO Business Intelligence

FEBRUARY 21, 2024

So students should learn about how to use the technology, and how to manage teams that use the tools — especially engineering teams. But we also have teams responsible for data analytics, and teams of audio-visual experts to ensure our concert halls and event centers can support a range of activities.

Recreation/Entertainment 126

Recreation/Entertainment Experimentation Modeling Data-driven 126

datapine

JANUARY 31, 2022

Because things are changing and becoming more competitive in every sector of business, the benefits of business intelligence and proper use of data analytics are key to outperforming the competition. BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. Visual IDE for data pipelines; RPA for rote tasks. Highlights.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

CIO Business Intelligence

FEBRUARY 7, 2024

Stephen Franchetti, CIO of Samsara, a fleet management SaaS provider that went public in 2021, believes the only way to optimize your AI strategy (or any emerging technology strategy, in fact) is with a bottoms-up approach. We’ve seen an ongoing iteration of experimentation with a number of promising pilots in production,” he says.

KPI 88

KPI Measurement Experimentation Finance 88

CIO Business Intelligence

NOVEMBER 21, 2023

But for a select few, the deeper challenges of departmental technologies being funded, procured, and managed without IT involvement are the missed opportunities to better engage and fulfill departmental technology needs. That’s not to downplay the inherent risks of shadow IT.

IT 131

IT Risk Cost-Benefit Risk Management 131

CIO Business Intelligence

JANUARY 9, 2024

Many organizations know that commercially available, “off-the-shelf” generative AI models don’t work well in enterprise settings because of significant data access and security risks. Lesson 1: Don’t start from scratch to train your LLM model Massive amounts of data and computational resources are needed to train an LLM.

Enterprise 106

Enterprise Experimentation Modeling Data-driven 106

CIO Business Intelligence

DECEMBER 6, 2023

Much of our digital agenda is around data. The migration, still in its early stages, is being designed to benefit from the learned efficiencies, proven sustainability strategies, and advances in data and analytics on the AWS platform over the past decade. Before we were quite fragmented across different technologies.

Manufacturing 79

Manufacturing Data Lake Digital Transformation Machine Learning 79

IBM Big Data Hub

DECEMBER 5, 2023

Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time. The impact of these investments will become evident in the coming years.

Unstructured Data 91

Unstructured Data Cost-Benefit Experimentation Machine Learning 91