CIO Business Intelligence

DECEMBER 11, 2023

Traditionally, the work of the CFO and the finance team was focused on protecting the company’s assets and reputation and guarding against risk. They can even optimize capital allocation decisions, such as dividend distribution versus share buy-back, by rapidly modeling multiple scenarios and market conditions.

Finance 99

Finance Forecasting IoT Predictive Modeling 99

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. With the exponential growth of large datasets, predictive analytics is being leveraged by enterprises across industries.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

DataKitchen

SEPTEMBER 21, 2023

L1 is usually the raw, unprocessed data ingested directly from various sources; L2 is an intermediate layer featuring data that has undergone some form of transformation or cleaning; and L3 contains highly processed, optimized, and typically ready for analytics and decision-making processes. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Smarten

SEPTEMBER 28, 2022

In order to understand how businesses might use assisted predictive modeling and predictive analytics, let’s look at some business use cases and how analytical techniques can help the enterprise derive concise, clear information to support decisions and strategies. Marketing Optimization. Quality Control. Demand Planning.

Predictive Analytics 52

Predictive Analytics Analytics Predictive Modeling Forecasting 52

Rocket-Powered Data Science

OCTOBER 6, 2023

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. Another way of saying this is: given some desired optimal outcome Y, what conditions X should we put in place.

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

IBM Big Data Hub

MAY 17, 2024

But as businesses around the globe rapidly adopt the technology to augment processes from merchandising to order management, there is some risk. Generative AI can also help brands maintain consistency across all touchpoints, ensuring that product information is accurate, up-to-date and optimized for conversions. 

B2B 68

B2B Interactive Optimization Forecasting 68

Cloudera

JUNE 27, 2023

During the COVID-19 pandemic, telcos made unprecedented use of data and data-driven automation to optimize their network operations, improve customer support, and identify opportunities to expand into new markets. Modernize data flows. Most telcos rely on legacy applications that create data silos and limit interoperability.

Data Architecture 62

Data Architecture Predictive Modeling Data Governance Data-driven 62

CIO Business Intelligence

AUGUST 23, 2023

Optimization problems, for which a whole chorus of variables must be fine-tuned and modulated, routinely plague financial firms, especially when it comes to highly engineered financial products such as those developed through quantitative analysis. If there’s an industry steeped in computations, it’s the financial services sector.

IT 84

IT Machine Learning Risk Optimization 84

Smart Data Collective

SEPTEMBER 17, 2020

Financial and banking industries worldwide are now exploring new and intriguing techniques through which they can smoothly incorporate big data analytics in their systems for optimal results. Here are a few of the advantages of Big Data in the banking and financial industry: Improvement in risk management operations.

Big Data 141

Big Data Finance Risk Management Risk 141

DataRobot

OCTOBER 19, 2021

DataRobot applied an innovative, hybrid modeling approach, which combines mechanist epidemiological modeling with the enhanced predictive power of AI to identify COVID-19 hotspots months in advance by optimizing parameters daily to match rapidly changing dynamics of viral spread. reporting backlogs).

Forecasting 98

Forecasting Predictive Modeling Optimization Testing 98

CIO Business Intelligence

MARCH 5, 2024

CIOs must also partner with CISOs, legal, human resources, and business leaders to build awareness of policies and develop a generative AI risk management strategy. CIOs may also want to consider each application’s usage, security, and risks to decide which devops teams should experiment with AI copilots.

Cost-Benefit 119

Cost-Benefit Advertising Experimentation Software 119

FineReport

APRIL 9, 2024

Optimized Operational Efficiency: These tools streamline processes and resource allocation, leading to cost savings and improved resource utilization. The implementation of robust healthcare data management strategies is imperative to mitigate the risks associated with data breaches and non-compliance.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

O'Reilly on Data

SEPTEMBER 15, 2020

Technical competence results in reduced risk and uncertainty. AI initiatives may also require significant considerations for governance, compliance, ethics, cost, and risk. Likewise, AI doesn’t inherently optimize supply chains, detect diseases, drive cars, augment human intelligence, or tailor promotions to different market segments.

Cost-Benefit 290

Cost-Benefit Advertising ROI Machine Learning 290

datapine

NOVEMBER 27, 2019

This is one of the major trends chosen by Gartner in their 2020 Strategic Technology Trends report , combining AI with autonomous things and hyperautomation, and concentrating on the level of security in which AI risks of developing vulnerable points of attacks. Industries harness predictive analytics in different ways.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

JUNE 8, 2022

‘Citizen Data Scientists can create new models, share models and collaborate, thereby improving business results and data literacy.’. In this article, we provide some examples of what a Citizen Data Scientist can do to advance the goals and interests of the organization and optimize their productivity and performance.

Predictive Analytics 52

Predictive Analytics Predictive Modeling Forecasting Optimization 52

Cloudera

SEPTEMBER 7, 2023

But it’s also fraught with risk. This June, for example, the European Union (EU) passed the world’s first regulatory framework for AI, the AI Act , which categorizes AI applications into “banned practices,” “high-risk systems,” and “other AI systems,” with stringent assessment requirements for “high-risk” AI systems.

Insurance 81

Insurance Risk Data-driven Finance 81

Smarten

MAY 17, 2019

Whether you need to anticipate and plan for equipment maintenance, target online customers, control customer churn, or identify ways to cross-sell and upsell customers on existing and new products and services, these predictive analytics tools can help you to optimize your marketing budget and your resources and mitigate risk and market missteps.

Predictive Analytics 65

Predictive Analytics Forecasting Analytics Predictive Modeling 65

IBM Big Data Hub

MAY 6, 2024

Predicting site performance, spotting underperforming sites and formulating timely interventions are essential. Optimize protocols using historical and synthetic data Complex and stringent protocols are notorious for delaying clinical trials and eroding patient engagement.

Advertising 84

Advertising Data-driven Optimization Strategy 84

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. HYBRID & MULTI-CLOUD INNOVATION. SECURITY AND GOVERNANCE LEADERSHIP. PEOPLE FIRST.

Digital Transformation 68

Digital Transformation Machine Learning Optimization Data Lake 68

Sisense

MARCH 27, 2019

Finally, real-time BI helps better understand trends and create more accurate predictive models for organizations. There are several industries, sectors, and fields where using real-time BI can optimize an organization: Customer relationship management suites (CRMs) can use real-time data to provide better service for consumers.

Business Intelligence 74

Business Intelligence Data Warehouse Predictive Modeling Visualization 74

Smarten

MAY 17, 2019

These techniques can be beneficial for infrastructure planning, construction, highway planning and management, government, agriculture, weather, travel and city planning, and can help the business to plan for resources, locations, supply chain, marketing, inventory, pricing, risk management, maintenance and other planning activities.

Predictive Analytics 58

Predictive Analytics Analytics Predictive Modeling Risk Management 58

Smarten

MAY 16, 2019

Perhaps the greatest risk to a lending organization is that presented by loan applicants who are unprepared to fulfill the long-term obligation of paying off a loan. Use Assisted Predictive Modeling to define the perfect loan applicant profile and to monitor and manage existing loans to anticipate and mitigate loan defaults.

Predictive Analytics 40

Predictive Analytics Analytics Predictive Modeling Insurance 40

IBM Big Data Hub

JUNE 29, 2023

Enterprises are constantly looking for new ways to optimize performance, increase reliability and extend asset lifespans—all without adding unnecessary costs. This information is then used to build predictive models of an asset’s performance over time and help spot potential problems before they arise.

Cost-Benefit 84

Cost-Benefit Measurement Management Predictive Analytics 84

Smarten

MAY 16, 2019

In the interim, there is loss of productivity and the risk of crucial mistakes. Augmented analytics can also identify the need for training, the types of jobs that are most at risk of frequent turnover, the key skills for a particular position and the probability of advancement. Marketing Optimization. Customer Targeting.

Predictive Analytics 51

Predictive Analytics Analytics Predictive Modeling Cost-Benefit 51

Smarten

MAY 13, 2019

The cost of acquiring a new customer includes marketing and advertising, resources and personnel, customer support, search engine optimization and more. Use Predictive Analytics to identify at risk customers and issues that will impact customer churn and customer retention. Marketing Optimization. Fraud Mitigation.

Predictive Analytics 51

Predictive Analytics Analytics Predictive Modeling Advertising 51

Business Over Broadway

SEPTEMBER 27, 2018

pharmacogenomics) and risk assessment of genetic disorders (e.g., Analytics applied to these types of data help you generate better predictive models because your integrated data contain all the key variables that are useful in predicting customer churn. Machine Learning and Predictive Modeling of Customer Churn.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

CIO Business Intelligence

OCTOBER 5, 2023

CBRE has also used AI to optimize portfolios for several clients, and recently launched a self-service generative AI product that enables employees to interact with CBRE and external data in a conversational manner. For AI, the high-value quadrant is where you’ll find most predictive modeling.

Experimentation 126

Experimentation Strategy Machine Learning Interactive 126

IBM Big Data Hub

FEBRUARY 14, 2024

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. Banks and other lenders can use ML classification algorithms and predictive models to suggest loan decisions.

Cost-Benefit 86

Cost-Benefit Insurance Unstructured Data Machine Learning 86

Smart Data Collective

SEPTEMBER 30, 2021

Drought Risk Assessment and Prediction. 2 Through artificial intelligence-based prediction, there can be improvement in decision making regarding droughts and better methods and timing employed to ensure optimal water resource allocation and disseminating information ahead of drought events.

Machine Learning 120

Machine Learning Cost-Benefit Optimization Forecasting 120

DataKitchen

JUNE 19, 2023

This pillar emphasizes the importance of implementing thorough data validation tests to mitigate the risks of erroneous analysis or decision-making based on faulty data. The above image shows an example custom ‘data in use’ test of a predictive model and API. The value here is improved end-user experienc e.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

CIO Business Intelligence

DECEMBER 13, 2022

We’re also doing a lot with population health management, performing more comprehensive patient assessments, managing our high-risk patients, stabilizing transitions of care, optimizing outpatient care, and really trying to call out things that help us understand disease progression.

Strategy 97

Strategy Technology Digital Transformation Data Lake 97

Smarten

AUGUST 21, 2019

Assisted Predictive Modeling – These tools enable the average business user to leverage sophisticated predictive algorithms without requiring statistical or data science skills. Users can highlight trends and patterns, test hypotheses and theories to reduce business risk, and easily predict and forecast results.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

CIO Business Intelligence

MARCH 22, 2023

Homomorphic encryption often requires custom hardware to optimize performance, which can be expensive to develop and maintain. It is often used to train machine learning models and protect sensitive data in healthcare and finance. Synthetic data can generate large amounts of data quickly and bypass privacy risks.

Machine Learning 104

Machine Learning Cost-Benefit Modeling Risk 104

Smarten

JANUARY 31, 2019

Today’s Advanced Analytics Tools allow business users to leverage features like self-serve data preparation, smart data visualization and assisted predictive modeling. Advanced Analytics is the logical tool to help a business optimize its investments and achieve its goals.

Business Intelligence 40

Business Intelligence Analytics Predictive Modeling Forecasting 40

Domino Data Lab

JULY 28, 2021

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

AUGUST 28, 2023

Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs. A targeted approach will optimize the user experience and enhance an organization’s ROI.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

Smarten

JANUARY 8, 2019

Assisted predictive modeling suggests techniques to analyze data that will result in the right outcome for the goals of the analysis. Business users get support for day-to-day decisions and can quickly and easily test theories and hypotheses in a risk-free environment.

Analytics 40

Analytics Predictive Modeling Visualization Business Analysis 40