IBM Big Data Hub

JANUARY 16, 2024

A finely tuned product development strategy is a holistic, cross-collaborative endeavor with the capacity to help any organization weather unforeseen events or market changes. Why is a strong product development strategy important? Consumers have access to more information than ever to compare products and brands.

Strategy 75

Strategy Cost-Benefit Testing Manufacturing 75

IBM Big Data Hub

MAY 28, 2024

Companies continue to create more attack surfaces with hybrid models, scattering critical data across cloud, third-party and on-premises locations, while threat actors constantly devise new and creative ways to exploit vulnerabilities. What is a data protection strategy? million, a 15 percent increase over three years.

Strategy 82

Strategy Measurement Risk Cost-Benefit 82

IBM Big Data Hub

SEPTEMBER 6, 2023

With the right generative AI strategy, marketers can mitigate these concerns. If the training data is biased or incomplete, the models may generate inaccurate content. This might include a virtual model wearing outfits that match the customer’s body type, fashion choices and activities of interest.

Marketing 113

Marketing Strategy B2B Cost-Benefit 113

CIO Business Intelligence

MARCH 6, 2024

While the product team was busy doing that, my team worked with the operations functions and our strategy team to completely reimagine our front- and back-office processes and supporting applications to enable this new cloud company. What has IT’s role been in the transformation to a SaaS model? Today, we’re a $1.6

Modeling 116

Modeling Management IT Metrics 116

CIO Business Intelligence

MARCH 25, 2024

Modern digital organisations tend to use an agile approach to delivery, with cross-functional teams, product-based operating models , and persistent funding. But to deliver transformative initiatives, CIOs need to embrace the agile, product-based approach, and that means convincing the CFO to switch to a persistent funding model.

Modeling 124

Modeling Cost-Benefit IT ROI 124

O'Reilly on Data

DECEMBER 12, 2019

Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]

Machine Learning 198

Machine Learning Modeling Testing Risk Management 198

TDAN

MARCH 16, 2021

The purpose of this article is to provide a model to conduct a self-assessment of your organization’s data environment when preparing to build your Data Governance program. Take the […].

Data Governance 105

Data Governance Testing Modeling Data Quality 105

CIO Business Intelligence

MARCH 9, 2022

Today’s cloud strategies revolve around two distinct poles: the “lift and shift” approach, in which applications and associated data are moved to the cloud without being redesigned; and the “cloud-first” approach, in which applications are developed or redesigned specifically for the cloud. Embrace cloud-native principles.

Strategy 145

Strategy Consulting Risk Testing 145

CIO Business Intelligence

MARCH 15, 2022

Synthetic data is artificially generated information that can be used in place of real historic data to train AI models when actual data sets are lacking in quality, volume, or variety. Artificial data has many uses in enterprise AI strategies. This can slow down the development of new AI models. Synthetic data use cases.

Strategy 145

Strategy Testing Sales Modeling 145

CIO Business Intelligence

JULY 31, 2023

They note, too, that CIOs — being top technologists within their organizations — will be running point on those concerns as companies establish their gen AI strategies. Here’s a rundown of the top 20 issues shaping gen AI strategies today. How has, say, ChatGPT hit your business model?” This is an issue for CIOs.

Strategy 98

Strategy Risk Enterprise Risk Management 98

CDW Research Hub

JUNE 23, 2020

As virtual desktop infrastructure (VDI) gains popularity among enterprises across multiple industries, and with many desktops migrating to the cloud, testing your virtual desktop environment has never been so important. Here are three reasons why testing is so important before setting up a virtual desktop environment.

Testing 92

Testing Strategy Data Processing Enterprise 92

DataKitchen

MAY 10, 2024

Development: Observability in development includes conducting regression tests and impact assessments when new code, tools, or configurations are introduced, helping maintain system integrity as new code of data sets are introduced into production. How Many Tests Ran In The Qa Environment? How Many Models Dashboards Were Deployed?

Testing 124

Testing Cost-Benefit Data Quality Dashboards 124

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. Leveraging that data, in AI models, for example, depends entirely on the accessibility, quality, granularity, and latency of your organization’s data. The important point is to start and keep moving.

Strategy 116

Strategy Management Key Performance Indicator ROI 116

CIO Business Intelligence

FEBRUARY 14, 2023

To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making. It’s clear how these real-time data sources generate data streams that need new data and ML models for accurate decisions.

Data Strategy 116

Data Strategy Strategy Machine Learning Data-driven 116

CIO Business Intelligence

JANUARY 25, 2024

Among their biggest concerns: exposing intellectual property through publicly available generative AI models, revealing the personal data of users to third-party vendors or service providers, and securing the AI itself from criminal hackers. Two-thirds of risk executives surveyed by Gartner consider gen AI a top emerging risk.

Strategy 109

Strategy Risk ROI Sales 109

Dataiku

APRIL 10, 2023

The process of converting a trained machine learning (ML) model into actual large-scale business and operational impact (known as operationalization) is one that can only happen once model deployment takes place.

Machine Learning 52

Machine Learning Modeling Testing Strategy 52

CIO Business Intelligence

JUNE 16, 2022

Cloud-first applications support a manageable OpEx cost model, metered like a utility, as opposed to requiring significant upfront capital investments in infrastructure and software licenses. That’s illustrated by the ability of cloud-first businesses to pivot to a remote work-from-home model with unprecedented speed and scale.”.

Strategy 138

Strategy Enterprise Digital Transformation Data Processing 138

CIO Business Intelligence

JUNE 13, 2024

That’s what a number of IT leaders are learning of late, as the AI market and enterprise AI strategies continue to evolve. But purpose-built small language models (SLMs) and other AI technologies also have their place, IT leaders are finding, with benefits such as fewer hallucinations and a lower cost to deploy.

IT 101

IT Cost-Benefit Machine Learning Testing 101

CIO Business Intelligence

JULY 11, 2023

Bryan Kirschner, Vice President, Strategy at DataStax Ignoring the potential of generative AI to increase productivity is a surefire way to fall behind as an individual, a team, and an organization. The most powerful framework I’ve found for effective strategic thinking is what Roger Martin calls the “strategy choice cascade.”

Strategy 75

Strategy Uncertainty Data-driven Consulting 75

DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. When business decisions are made based on bad models, the consequences can be severe. As machine learning advances globally, we can only expect the focus on model risk to continue to increase.

Risk 111

Risk Modeling IT Risk Management 111

IBM Big Data Hub

APRIL 13, 2023

After developing a machine learning model, you need a place to run your model and serve predictions. If your company is in the early stage of its AI journey or has budget constraints, you may struggle to find a deployment system for your model. Also, a column in the dataset indicates if each flight had arrived on time or late.

Modeling 81

Modeling Statistics Machine Learning Testing 81

Dataiku

JUNE 21, 2022

Evaluating different models is a critical step in both design and production, especially when you want to run Champion/Challenger or A/B testing strategies. The model evaluation and comparison capabilities of Dataiku make this crucial step even easier for practitioners.

Modeling 59

Modeling Testing Strategy 59

CIO Business Intelligence

MAY 3, 2024

During pilot testing, UPS earned 50% reduction in the time agents spent resolving e-mails. The LLM gives agents the ability to confirm all responses suggested by the model. As a result, UPS is investing in training the model on its corporate data set. That frees up human agents to handle the more complex questions.”

Testing 140

Testing Sales Enterprise Digital Transformation 140

CIO Business Intelligence

MAY 24, 2023

Security, strategy and cost were among the top reasons for migrating workloads. And just as campers must pick the best equipment to ensure a successful trip, developers seek the best tools with which to build, test and launch their applications. Isn’t it time to put your stake in the ground-to-cloud strategy?

Strategy 98

Strategy Digital Transformation Cost-Benefit Software 98

Smarten

JANUARY 10, 2024

Engaging Technology – It is perhaps no surprise that Musk decided to give his AI model a bit of a personality. Training Models – The current Grok training model is based on 33 billion parameters, as compared to ChatGPT 3.5 with a 175 billion parameter training model and GPT 4 with 1.76 trillion parameters.

Marketing 52

Marketing Modeling IT Digital Transformation 52

DataRobot Blog

MAY 26, 2022

Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. In summary, to ensure that they have built a robust model, modelers must make certain that they have designed the model in a way that is backed by research and industry-adopted practices.

Risk 52

Risk Modeling Metrics Business Objectives 52

Cloudera

OCTOBER 20, 2021

Stress testing was heavily scrutinized in the post 2008 financial crisis. In a BIS advisory report , it was highlighted that the stress testing scenarios used by the banks were insufficient to capture the extreme risks and fluctuations that were realized. Transition : the changes in asset values, business models, etc. (ex.

Risk 80

Risk Modeling Risk Management Measurement 80

Smart Data Collective

JANUARY 30, 2023

Mixed reality In times of chaos, do you really have enough funds to build test models, organize accurate product testing with clients before you start selling, or spend time and money on fixing the potential issues that may or may not occur? When used appropriately, it can significantly improve your overall ROI.

Software 98

Software Strategy Testing Advertising 98

Smart Data Collective

NOVEMBER 4, 2021

But before that, companies actually have to look back and ask themselves whether the cloud suits their business structure and business model and what advantages they have after implementing that. In industries such as healthcare, gaming, financial and other penetration testing of cloud resources is a part of a standard IT process.

Strategy 119

Strategy Snapshot Risk IoT 119

Smart Data Collective

FEBRUARY 21, 2021

A growing number of marketers are using data analytics technology to optimize their lead generation models. But what lead generation strategies can you use in conjunction with your data analytics tools. You need to know which strategies work for lead generation in order to utilize data analytics effectively. Create Webinars.

Strategy 99

Strategy Data Analytics Analytics Data-driven 99

CIO Business Intelligence

MAY 30, 2024

The State of Generative AI in the Enterprise report from Deloitte found that 75% of organizations expect generative AI technology to impact talent strategies within the next two years, and 32% of organizations that reported “very high” levels of generative AI expertise are already on course to make those changes.

Digital Transformation 137

Digital Transformation Machine Learning Software Testing 137

Rocket-Powered Data Science

SEPTEMBER 25, 2022

This is all fueled and facilitated by data flows across processes, products, and people’s activities, used in synergy with computational models and simulations of the system being digitally twinned. All phases of the MVT process are discussed: strategy, designs, pilot, implementation, test, validation, operations, and monitoring.

Diagnostic Analytics 216

Diagnostic Analytics Prescriptive Analytics Internet of Things IoT 216

CIO Business Intelligence

MARCH 29, 2024

That’s why Rocket Mortgage has been a vigorous implementor of machine learning and AI technologies — and why CIO Brian Woodring emphasizes a “human in the loop” AI strategy that will not be pinned down to any one generative AI model. Today, 60% to 70% of Rocket’s workloads run on the cloud, with more than 95% of those workloads in AWS.

Data Lake 134

Data Lake Machine Learning Data Warehouse Unstructured Data 134

IBM Big Data Hub

MAY 20, 2024

Machine learning (ML) has become a critical component of many organizations’ digital transformation strategy. The answer lies in the data used to train these models and how that data is derived. This can save time and resources by reducing the need for extensive testing and debugging.

Machine Learning 87

Machine Learning Modeling Strategy Digital Transformation 87

CIO Business Intelligence

SEPTEMBER 26, 2023

For instance, a recent report from Accenture Strategy found that 67% of senior tech leaders view a lack of tech-fluency among their peers as a major barrier to integrating technology into strategy development. In other words, what architecture best ensures model outputs are relevant, reliable, and usable.

Enterprise 135

Enterprise Modeling Strategy Testing 135

CIO Business Intelligence

JUNE 4, 2024

Developer tools SAP’s clean core strategy is getting a boost with new capabilities in both SAP’s low-code and pro-code development tools. On the pro-code front, Andreas Welsch, VP and head of AI marketing, said in an interview that SAP is leveraging its partnership with Nvidia to fine tune an LLM model on ABAP code.

IT 119

IT Data Governance ROI Business Objectives 119