CIO Business Intelligence

JUNE 14, 2022

The UK Central Data and Digital Office (CDDO) has unveiled the Transforming for a Digital Future strategy, which sets out a collective cross-government roadmap and vision for 2025. The mission also suggests the imminent launch of a new mobile application strategy. One Login for government. Digital skills at scale.

Strategy 101

Strategy IT Digital Transformation Data Processing 101

Rocket-Powered Data Science

OCTOBER 6, 2023

What is the point of those obvious statistical inferences? In statistical terms, the joint probability of event Y and condition X co-occurring, designated P(X,Y), is essentially the probability P(Y) of event Y occurring. How do predictive and prescriptive analytics fit into this statistical framework?

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. This is like a denial-of-service (DOS) attack on your model itself.

Modeling 219

Modeling Machine Learning Predictive Modeling Consulting 219

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

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.

Strategy 99

Strategy Data Analytics Analytics Data-driven 99

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

MAY 7, 2024

Rethinking our thoughts on data When confronting a long-lived substantive problem — for example, why aren’t we getting full value from data — that is not immediately life threatening, I suggest conducting a mental model audit. How are we thinking about this problem? Gutman, Jordan Goldmeier.

Big Data 129

Big Data Statistics Machine Learning Data Science 129

CIO Business Intelligence

FEBRUARY 12, 2024

2 Key challenges include a shortage of talent and skills (62%), unclear investment priorities (47%), and the lack of a strategy for responsible AI (42%), BCG found. Such bleak statistics suggest that indecision around how to proceed with genAI is paralyzing organizations and preventing them from developing strategies that will unlock value.

IT 124

IT Consulting Cost-Benefit Uncertainty 124

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

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 118

Strategy Snapshot Risk IoT 118

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.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

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

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 126

Business Intelligence Data-driven Statistics Data Warehouse 126

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

Domino Data Lab

AUGUST 10, 2021

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. The process of creating models is called modeling.

Modeling 64

Modeling IT Risk Management Deep Learning 64

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

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

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.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

Smarten

MAY 17, 2024

For example, a Data Scientist can use PMML integration to Import models created in other languages like R and Python with a PMML format, and use those models with analytical workflows to roll out predictive models to users, enabling business users to participate in analysis and making Data Scientists more productive.

Analytics 52

Analytics Predictive Modeling ROI Cost-Benefit 52

Jet Global

APRIL 5, 2021

Enterprises actively use financial modeling to guide their financial planning and strategic decision-making. Financial models offer data-driven, quantitative analysis that tells you where your company stands and where it’s heading. That being said, one model can’t do it all. What Is Financial Modeling?

Modeling 98

Modeling Forecasting Metrics Finance 98

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 137

Risk Management Risk Cost-Benefit Technology 137

Occam's Razor

JULY 13, 2017

The sixteen examples neatly fall into nine strategies I hope you’ll cultivate in your analytics practice as you create data visualizations: 1: The Simplicity Obsession. 5: What-if Analysis Models. Strategy 1: The Simplicity Obsession. Strategy 2: If Complex, Focus! Strategy 3: Venn Diagrams FTW! sharply focused 2.

Visualization 124

Visualization Strategy Interactive Statistics 124

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 63

Modeling Predictive Analytics Predictive Modeling IT 63

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 122

Enterprise Modeling Testing Data-driven 122

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

Management 83

Management IT Machine Learning Metrics 83

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

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 80

Data Science Data Analytics Prescriptive Analytics Analytics 80

The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. It is also a sound strategy when experimenting with several parameters at the same time. And sometimes even if it is not[1].)

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

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

Rocket-Powered Data Science

JULY 14, 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.

Analytics 166

Analytics Internet of Things Prescriptive Analytics Data Science 166

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

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

IBM Big Data Hub

AUGUST 16, 2022

Let’s look at how IBM combines and analyzes this data to deliver statistics and analytics in natural language, and how we break open the “black box” of AI to deliver trustworthy, explainable insights that complement outside media sources. Likelihood to Win: A win probability model for each player.

Statistics 105

Statistics Unstructured Data Machine Learning Consulting 105

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

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. What Is Business Intelligence And Analytics? The end-user is another factor to consider.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

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 97

Digital Transformation Statistics Data-driven Strategy 97