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

CIO Business Intelligence

SEPTEMBER 2, 2024

Younus Al Nasser, Chief Executive of the Dubai Data and Statistics Establishment, commented, “With the ongoing global transformations, new economic patterns and business models are emerging, presenting future opportunities for dynamic economies like Dubai’s. The data centre economy exemplifies these transformations.

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Statistics Data-driven Strategy Technology 123

Smart Data Collective

NOVEMBER 4, 2021

If the answer is so easy why the worrying statistics? 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.

Strategy 119

Strategy Snapshot Risk IoT 119

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

Alation

JUNE 2, 2022

These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. Currently, models are managed by modelers and by the software tools they use, which results in a patchwork of control, but not on an enterprise level. And until recently, such governance processes have been fragmented.

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Modeling Data Governance Statistics Unstructured Data 52

Rocket-Powered Data Science

MARCH 19, 2021

Focus on the strategies that aim these tools, talents, and technologies on reaching business mission and goals: e.g., data strategy, analytics strategy, observability strategy ( i.e., why and where are we deploying the data-streaming sensors, and what outcomes should they achieve?).

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

CIO Business Intelligence

OCTOBER 26, 2023

Through use of data analytics, data visualization, and data modeling techniques and technologies, BI analysts can identify trends that can help other departments, managers, and executives make business decisions to modernize and improve processes in the organization. What does a business intelligence analyst do?

Business Intelligence 125

Business Intelligence Data-driven Statistics Data Warehouse 125

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. It helps to automate and makes the usage of the R programming statistical language easier and much more effective. perfect for statistical computing and design.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

CIO Business Intelligence

JANUARY 26, 2024

Carnegie Mellon University The Machine Learning Department of the School of Computer Science at Carnegie Mellon University was founded in 2006 and grew out of the Center for Automated Learning and Discovery (CALD), itself created in 1997 as an interdisciplinary group of researchers with interests in statistics and machine learning.

Machine Learning 104

Machine Learning Statistics Recreation/Entertainment Data Science 104

CIO Business Intelligence

AUGUST 9, 2024

In cases where privacy is essential, we try to anonymize as much as possible and then move on to training the model,” says University of Florence technologist Vincenzo Laveglia. “A We have to make sure there’s a balance between various classes of information, otherwise the model becomes an expert on one topic and very uncertain on others.”

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Risk Measurement Modeling Data Lake 138

datapine

JANUARY 24, 2021

It is not just important to gather all the existing information, but to consider the preparation of data and utilize it in the proper way, has become an indispensable value in developing a successful business strategy. For example, you need to develop a sales strategy and increase revenue. Today, big data is about business disruption.

IT 317

IT Statistics KPI Data-driven 317

Smarten

JULY 23, 2019

Predictive Modeling allows users to test theories and hypotheses and develop the best strategy. Data modeling provides a picture of products, services, locations, customers, investments, resources, competitors, marketing, sales and other aspects of the organization that will impact forecasting and planning.

Modeling 64

Modeling Predictive Analytics Predictive Modeling IT 64

CIO Business Intelligence

MAY 20, 2022

The Machine Learning Department at Carnegie Mellon University was founded in 2006 and grew out of the Center for Automated Learning and Discovery (CALD), itself created in 1997 as an interdisciplinary group of researchers with interests in statistics and machine learning. Stanford offers both PhDs and an MSCS with an AI specialization.

Machine Learning 145

Machine Learning Statistics Recreation/Entertainment Data Science 145

Sisense

SEPTEMBER 12, 2019

Every business needs a business intelligence strategy to take it forward. . As the Global Team Lead of BI Consultants at Sisense, I can say that the projects I’ve worked on where a BI strategy was involved, were more successful than projects without a strategy. But what is a BI strategy in today’s world?

Strategy 81

Strategy Dashboards Diagnostic Analytics Prescriptive Analytics 81

CIO Business Intelligence

JANUARY 19, 2024

The US Bureau of Labor Statistics (BLS) forecasts employment of data scientists will grow 35% from 2022 to 2032, with about 17,000 openings projected on average each year. You need experience in machine learning and predictive modeling techniques, including their use with big, distributed, and in-memory data sets.

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Data Science Machine Learning Predictive Modeling Experimentation 125

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. Many functions of data analytics—such as making predictions—are built on machine learning algorithms and models that are developed by data scientists.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

datapine

MARCH 31, 2022

This all-encompassing branch of online data analysis is a particularly interesting field because its roots are firmly planted in two separate areas: business strategy and computer science. The Bureau of Labor Statistics also states that in 2015, the annual median salary for BI analysts was $81,320.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

IBM Big Data Hub

FEBRUARY 13, 2024

This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Generative adversarial networks (GANs) or variational autoencoders (VAEs) are used for images, videos, 3D models and music. Autoregressive models or large language models (LLMs) are used for text and language.

Enterprise 118

Enterprise Testing Modeling Data-driven 118

CIO Business Intelligence

NOVEMBER 8, 2022

This is why executing a persistent data and analytics strategy is so important. It allows you to create a baseline of the past, identify when change happens, adapt your strategy, and make new, informed decisions. Ensure explainability and transparency in models. Or, in other words, what is the learning rate of your organization?

Digital Transformation 98

Digital Transformation Statistics Data-driven Strategy 98

CIO Business Intelligence

SEPTEMBER 30, 2024

AI ‘bake-offs’ under way Mathematica’s PaaS has not yet implemented AI models in production, but Bell grasps the power of machine learning (ML) and generative AI to uncover new insights that will help Mathematica’s clients.

Data Quality 113

Data Quality Experimentation Insurance Statistics 113

CIO Business Intelligence

JUNE 11, 2024

A 1958 Harvard Business Review article coined the term information technology, focusing their definition on rapidly processing large amounts of information, using statistical and mathematical methods in decision-making, and simulating higher order thinking through applications. What comes first: A new brand or operating model?

IT 135

IT Digital Transformation Business Objectives Broadcasting 135

DataRobot Blog

SEPTEMBER 1, 2022

For example, a recent IDC study 1 shows that it takes about 290 days on average to deploy a model into production from start to finish. Once you move your model into production, you need to monitor and manage your models to ensure that you can trust predictions and turn them into the right business decisions.

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Metrics Statistics Modeling Data Science 145

Rocket-Powered Data Science

JULY 6, 2023

This is not entirely due to or related to ChatGPT and LLMs (large language models), though those have been the main drivers. This year, artificial intelligence (AI) has become a major conversation centerpiece at home, in the park, at the gym, at work, everywhere.

Strategy 153

Strategy Enterprise Software Marketing 153

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. Drag-and-drop Modeler for creating pipelines, IBM integrations.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

bridgei2i

OCTOBER 7, 2020

Adoption of Automated Sales & Underwriting Strategies can Transform Insurance. Importance of capturing market data for optimized pricing models. The insurance industry—which, in the US alone, stands at $1.2 trillion, is seeing the volume of insurance transactions growing every year. Authors: Sonam Jain & Prabuddha Jagadeb.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

IBM Big Data Hub

APRIL 9, 2024

Preparing and annotating data IBM watsonx.data helps organizations put their data to work, curating and preparing data for use in AI models and applications. “For the Masters we use 290 traditional AI models to project where golf balls will land,” says Baughman. ” Watsonx.ai ” Watsonx.ai

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Management IT Machine Learning Metrics 78

CIO Business Intelligence

JULY 23, 2024

Third-party data breaches The CIO’s AI strategies and objectives in driving a data-driven organization result in the addition of many third-party partners, solutions, and SaaS tools. Be paranoid about third-party data breaches and security incidents,” warns Brad Hibbert, COO and chief strategy officer at Prevalent. “To

Risk 142

Risk IT Risk Management Cost-Benefit 142

CIO Business Intelligence

MAY 9, 2024

They should lead the efforts to tie AI capabilities to data analytics and business process strategies and champion an AI-first mindset throughout the organization. For companies with a central strategy function, the CAIO will be a key partner in driving success.” Artificial Intelligence, IT Leadership

Risk Management 138

Risk Management Risk Cost-Benefit Technology 138

CIO Business Intelligence

SEPTEMBER 30, 2024

She points to a recent initiative in which the job matching and hiring platform company started using large language models (LLMs) to add a highly customized sentence or two to the emails it sends to job seekers about open positions that match their qualifications.

Machine Learning 141

Machine Learning ROI Data Processing Optimization 141

Domino Data Lab

OCTOBER 7, 2020

Statistical methods for analyzing this two-dimensional data exist. This statistical test is correct because the data are (presumably) bivariate normal. When there are many variables the Curse of Dimensionality changes the behavior of data and standard statistical methods give the wrong answers. Data Has Properties.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

datapine

JUNE 7, 2022

From political issues to sports statistics and the recent report you received on the ROI of your company blog, the internet as well as informational reports are flooded with examples of misleading data visualization. If you want to go deeper into the topic, take a look at our misleading statistics blog post. Correlating Causation.

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Visualization Metrics Statistics Dashboards 267

Smart Data Collective

MARCH 27, 2023

Data Scientists and Analysts use various tools such as machine learning algorithms, statistical modeling, natural language processing (NLP), and predictive analytics to identify trends, uncover opportunities for improvement, and make better decisions.

Data Science 92

Data Science Statistics Data-driven Machine Learning 92

Rocket-Powered Data Science

JULY 19, 2023

This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

FineReport

MARCH 24, 2024

Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis. They identify and interpret trends in complex datasets, optimize statistical results, and maintain databases while devising new data collection processes.

Statistics 52

Statistics Data mining Visualization Reporting 52

O'Reilly on Data

MARCH 31, 2020

This means that the AI products you build align with your existing business plans and strategies (or that your products are driving change in those plans and strategies), that they are delivering value to the business, and that they are delivered on time. We won’t go into the mathematics or engineering of modern machine learning here.

Management 341

Management Machine Learning Experimentation Metrics 341

Smart Data Collective

MAY 16, 2022

It also helps in the analysis of the data using sophisticated statistical tools and then producing reports and presentations for the decision-makers. Some data management strategies are in-house and others are outsourced. A database consists of data structures or data models which are used to store and organize information.

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Management Data mining Data Warehouse Data Collection 127