IBM Big Data Hub

APRIL 28, 2020

During these times of uncertainty, all companies are being stressed in new ways; supply chains are being halted with employee sickness, retail store doors are closed to encourage social distancing, and health care facilities are overwhelmed by patient demand.

Uncertainty 82

Uncertainty Data Science Risk 82

Rocket-Powered Data Science

JULY 19, 2023

The latter is associated primarily with “watching” the data for interesting patterns, while precursor analytics is associated primarily with training the business systems to quickly identify those specific patterns and events that could be associated with high-risk events, thus requiring timely attention, intervention, and remediation.

Data-driven 186

Data-driven Enterprise Analytics Machine Learning 186

BizAcuity

MARCH 18, 2019

The consumer lending business is centered on the notion of managing the risk of borrower default. Credit scoring systems and predictive analytics model attempt to quantify uncertainty and provide guidance for identifying, measuring and monitoring risk. Benefits of Predictive Analytics in Unsecured Consumer Loan Industry.

Predictive Analytics 83

Predictive Analytics Analytics Cost-Benefit Data mining 83

erwin

AUGUST 13, 2020

managing risk vs ROI and emerging countries)? Compliance and Legislation : How do we manage uncertainty around legislative change (e.g., data protection, personal and sensitive data, tax issues and sustainability/carbon emissions)? Data Overload : How do we find and convert the right data to knowledge (e.g.,

Enterprise 143

Enterprise Cost-Benefit Uncertainty ROI 143

IBM Big Data Hub

FEBRUARY 20, 2024

The model could potentially be used to identify conditions that raise the risks of wildfires and predict hurricanes and droughts. The United Nations’ Intergovernmental Panel on Climate Change (IPCC) predicts people living in Africa, Australia, North America and Europe will face health risks due to rising temperatures and heat waves.

Modeling 122

Modeling Forecasting Reporting Risk 122

datapine

MAY 31, 2022

Since we live in a digital age, where data discovery and big data simply surpass the traditional storage and manual implementation and manipulation of business information, companies are searching for the best possible solution for handling data. The next part of our cloud computing risks list involves costs.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

IBM Big Data Hub

SEPTEMBER 28, 2023

This process is designed to help mitigate risks so that model outputs can be deployed responsibly with the assistance of watsonx.data and watsonx.governance (coming soon). Building transparency into IBM-developed AI models To date, many available AI models lack information about data provenance, testing and safety or performance parameters.

Testing 94

Testing Finance Enterprise Modeling 94

AWS Big Data

JUNE 27, 2023

Given the limitations of the static PDF charts used for its recruitment marketing data, we recognized the opportunity to introduce real-time interactive dashboards to improve insights needed to drive recruitment marketing initiatives.

Metrics 97

Metrics Dashboards Interactive Visualization 97

Smart Data Collective

MARCH 21, 2022

Amidst all this, data professionals, such as scientists, engineers and analysts are locking horns with qualitative transforming of raw data into actionable feed. . In a centralized ecosystem, everyone is dependent upon everyone else thereby creating uncertainties and interrupted flow of accurate data.

Management 66

Management Data Lake Uncertainty Data Warehouse 66

Cloudera

MAY 15, 2018

Over the past decade, we have observed open source powered big data and analytics platforms evolve from large data storage containers to massively scalable advanced modeling platforms that seamlessly operate on-premises and in a multi-cloud environment. Probability, Uncertainty and Quantitative Risk (2017) 2:6.

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

IBM Big Data Hub

APRIL 18, 2024

The AGI would need to handle uncertainty and make decisions with incomplete information. It might analyze real-time data from cameras, LiDAR and other sensors to identify objects, assess risks and anticipate environmental changes like sudden weather events or unexpected obstacles.

Cost-Benefit 95

Cost-Benefit Modeling Manufacturing Interactive 95

IBM Big Data Hub

JULY 31, 2023

Banks have the most to gain if they succeed (and the most to lose if they fail) at bringing their mainframe application and data estates up to modern standards of cloud-like flexibility, agility and innovation to meet customer demand. Couldn’t execs have run better analyses to spot risks within the data?

Digital Transformation 54

Digital Transformation Uncertainty Risk Data Warehouse 54

IBM Big Data Hub

OCTOBER 18, 2022

It’s more vexing than regulation, cyber risk, and even supply chain disruptions. Most admit uncertainty around ROI and nearly half struggle with adequate insights from their data. It’s the most frequently identified challenge CEOs expect to face over the next two to three years.

Uncertainty 52

Uncertainty Strategy Measurement ROI 52

Cloudera

NOVEMBER 19, 2018

One of Cloudera’s partners offers “Sustainability Services” with a goal of assisting organizations in turning costs and risks associated with changing regulatory and workforce environments, as well as supply chain uncertainties and volatile markets, into business opportunities.

Digital Transformation 40

Digital Transformation IoT Cost-Benefit Uncertainty 40

Sisense

OCTOBER 6, 2020

These techniques allow you to: See trends and relationships among factors so you can identify operational areas that can be optimized Compare your data against hypotheses and assumptions to show how decisions might affect your organization Anticipate risk and uncertainty via mathematically modeling.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

Peter James Thomas

JUNE 20, 2019

Here we come back to the upward trend in searches for Data Science. It could be argued of course that this is yet another business fad (indeed some are speaking about Big Data in just those terms already [7] ), but I believe that there is more substance to the area than this. And a more competent Chief Risk Officer. .

Cost-Benefit 55

Cost-Benefit Data Warehouse Consulting Data Science 55

Smart Data Collective

JULY 31, 2022

Predictive analytics tools can be particularly valuable during periods of economic uncertainty. Predictive Analytics Helps Traders Deal with Market Uncertainty. However, predictive analytics will probably be even more important as global uncertainty is higher than ever. Analytics Vidhya, Neptune.AI

Predictive Analytics 134

Predictive Analytics Analytics Uncertainty Forecasting 134

Domino Data Lab

JULY 22, 2019

By virtue of that, if you take those log files of customers interactions, you aggregate them, then you take that aggregated data, run machine learning models on them, you can produce data products that you feed back into your web apps, and then you get this kind of effect in business. That was the origin of big data.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Andrew White

APRIL 22, 2020

In this second phase executive leaders will need to make critical business decisions with even less data and with more uncertainty. Many highly leveraged firms will be at risk; debt will be at record levels in public and private so anyone who has cash will be predatory. Big data; small data.

Software 52

Software Uncertainty Measurement Marketing 52

Cloudera

NOVEMBER 18, 2021

As a bank that understands the future of financial services as data-driven, Bank of the West chose to adopt the Cloudera platform as the linchpin of its digital transformation. In doing so, Bank of the West has modernized and centralized its Big Data platform in just one year. Data for Good.

Data Lake 74

Data Lake Cost-Benefit Digital Transformation Risk 74

IBM Big Data Hub

SEPTEMBER 11, 2023

Government executives face several uncertainties as they embark on their journeys of modernization. When substantial investments of taxpayers’ money are allocated toward IT modernization, agencies are mandated by local legislature and judiciary to deliver meaningful improvements.

Data-driven 90

Data-driven IT Measurement Cost-Benefit 90

IBM Big Data Hub

OCTOBER 2, 2023

In a world marked by volatility, uncertainty, complexity, and ambiguity (VUCA) building a holistic planning environment is inevitable for successful steering.” Without a well-defined goal, there’s a risk of the platform developing in a direction that may not align with their needs or expectations.

Analytics 94

Analytics Manufacturing Uncertainty Machine Learning 94

Domino Data Lab

JUNE 2, 2019

ans from Nick Elprin, CEO and co-founder of Domino Data Lab, about the importance of model-driven business: “Being data-driven is like navigating by watching the rearview mirror. If your business is using big data and putting dashboards in front of analysts, you’re missing the point.”. Because of compliance.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110

Cloudera

OCTOBER 3, 2018

In 2008, I co-founded Cloudera with folks from Google, Facebook, and Yahoo to deliver a big data platform built on Hadoop to the enterprise market. We believed then, and we still believe today, that the rest of the world would need to capture, store, manage and analyze data at massive scale. Forward-Looking Statements.

Uncertainty 75

Uncertainty IoT Risk Reporting 75

The Unofficial Google Data Science Blog

JULY 22, 2020

One reason to do ramp-up is to mitigate the risk of never before seen arms. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. For example, imagine a fantasy football site is considering displaying advanced player statistics.

Experimentation 95

Experimentation Statistics Testing Strategy 95

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. 105, -17) or even “Python” (No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Peter James Thomas

AUGUST 12, 2018

A clear parallel would be credit risk in Retail Banking, but something as simple as an estimate of potentially delinquent debtors is an inherently statistical figure (albeit one that may not depend on the output of a statistical model). Ideas for avoiding Big Data failures and for dealing with them if they happen (2017).

Metrics 49

Metrics Statistics Data Quality Measurement 49

Smart Data Collective

FEBRUARY 14, 2023

There are many other reasons AI and big data technology is changing finance. Before you can create a strategy, you must determine your risk tolerance. Finding the right balance between risk and reward is all about your establishing personal investment goals. Do you prefer to play it safe or put it all on the line?

Predictive Analytics 109

Predictive Analytics Management Analytics Risk 109

Domino Data Lab

JUNE 23, 2019

This was all enabled and accelerated by an earlier wave of big data technologies ushered in by Google’s MapReduce paper and the open source project Hadoop. If you have a user facing product, the data that you had when you prototype the model may be very different from what you actually have in production.

Management 110

Management Machine Learning Experimentation Metrics 110

Sisense

DECEMBER 13, 2021

Without leveraging this information, businesses can easily fall into the same patterns that can stunt growth–failing to attract new customers and even leaving themselves open to security risks. Many financial institutions face common challenges when it comes to turning their big data sets into actionable business intelligence.

Data-driven 59

Data-driven IT Business Intelligence Cost-Benefit 59

datapine

DECEMBER 28, 2021

With the rise of advanced technology and globalized operations, statistical analyses grant businesses an insight into solving the extreme uncertainties of the market. Drinking tea increases diabetes by 50%, and baldness raises the cardiovascular disease risk up to 70%! Transparency and Data-Driven Business Solutions.

Statistics 363

Statistics Advertising Visualization Data mining 363