IBM Big Data Hub

MARCH 25, 2024

This blog and the IBM Institute for Business Value study The Revolutionary Content Supply Chain aim to answer these questions to help executives and their employees to better understand the changing landscape in content creation and embrace the power of generative AI models when it comes to optimizing their content supply chains.

Uncertainty 97

Uncertainty Cost-Benefit Risk Measurement 97

IBM Big Data Hub

DECEMBER 16, 2022

Over the last week, millions of people around the world have interacted with OpenAI’s ChatGPT, which represents a significant advance for generative artificial intelligence (AI) and the foundation models that underpin many of these use cases. It’s a fitting way to end what has been another big year for the industry.

Uncertainty 113

Uncertainty Metadata Modeling Data Collection 113

CIO Business Intelligence

APRIL 28, 2022

Right from the start, auxmoney leveraged cloud-enabled analytics for its unique risk models and digital processes to further its mission. Particularly in Asia Pacific , revenues for big data and analytics solutions providers hit US$22.6bn in 2020 , with financial services companies ranking among their biggest clients.

Analytics 82

Analytics Insurance Big Data Uncertainty 82

IBM Big Data Hub

FEBRUARY 20, 2024

Climate models provide answers Human activities precipitated changes to the Earth’s climate in the 20th century and will largely determine the future climate. Global climate models have given climate scientists a set of expectations as to what the future could hold, both for the Earth at large and for specific regions.

Modeling 114

Modeling Forecasting Reporting Risk 114

AWS Big Data

AUGUST 7, 2023

Many businesses use different software tools to analyze historical data and past patterns to forecast future demand and trends to make more accurate financial, marketing, and operational decisions. Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future.

Forecasting 84

Forecasting Data Warehouse Machine Learning Modeling 84

Rocket-Powered Data Science

JULY 19, 2023

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. 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

IBM Big Data Hub

SEPTEMBER 28, 2023

An AI and data platform, such as watsonx, can help empower businesses to leverage foundation models and accelerate the pace of generative AI adoption across their organization. Business-targeted, IBM-developed foundation models built from sound data Business leaders charged with adopting generative AI need model flexibility and choice.

Testing 87

Testing Finance Enterprise Modeling 87

erwin

AUGUST 13, 2020

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., big data, analytics and insights)?

Enterprise 143

Enterprise Cost-Benefit Uncertainty ROI 143

BizAcuity

MARCH 18, 2019

Credit scoring systems and predictive analytics model attempt to quantify uncertainty and provide guidance for identifying, measuring and monitoring risk. The terms of such loans, including approval and receipt, are therefore most often contingent on the borrower’s credit score.

Predictive Analytics 83

Predictive Analytics Analytics Cost-Benefit Data mining 83

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.

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

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 67

Management Data Lake Uncertainty Data Warehouse 67

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 89

Cost-Benefit Modeling Manufacturing Interactive 89

The Unofficial Google Data Science Blog

MARCH 31, 2016

KUEHNEL, and ALI NASIRI AMINI In this post, we give a brief introduction to random effects models, and discuss some of their uses. Through simulation we illustrate issues with model fitting techniques that depend on matrix factorization. Random effects models are a useful tool for both exploratory analyses and prediction problems.

Modeling 40

Modeling Statistics Advertising Testing 40

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. We used row-level security with tag-based rules in QuickSight to restrict data on a per-user basis.

Metrics 97

Metrics Dashboards Interactive Visualization 97

Domino Data Lab

JUNE 2, 2019

If you lead a data science team/org, DM me and I’ll send you an invite to data-head.slack.com ”. We had data science leaders presenting about lessons learned while leading data science teams, covering key aspects including scalability, being model-driven, being model-informed, and how to shape the company culture effectively.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110

Smart Data Collective

MAY 3, 2021

Big data has played a huge role in the evolution of employment models. Big data has made the gig economy stronger than ever and helped many people find new employment. Data savvy freelancers that understand concepts like self-tracking can get a lot more value out of their work. are your thoughts?

Big Data 122

Big Data Data mining Cost-Benefit Insurance 122

Cloudera

NOVEMBER 18, 2021

By adopting a custom developed application based on the Cloudera ecosystem, Carrefour has combined the legacy systems into one platform which provides access to customer data in a single data lake. In doing so, Bank of the West has modernized and centralized its Big Data platform in just one year.

Data Lake 77

Data Lake Cost-Benefit Digital Transformation Risk 77

Cloudera

AUGUST 26, 2021

This means that there is out of the box support for Ozone storage in services like Apache Hive , Apache Impala, Apache Spark, and Apache Nifi, as well as in Private Cloud experiences like Cloudera Machine Learning (CML) and Data Warehousing Experience (DWX). label="uncertainty"). model = fbprophet.Prophet(). Trim down columns.

Data Science 113

Data Science Forecasting Metadata Machine Learning 113

IBM Big Data Hub

FEBRUARY 21, 2022

But amidst all this uncertainty just what trends should business leaders be focused on? Strikingly, 36% of Gen Z consumers — so-called “digital natives” — prefer this hybrid model of shopping: the largest share of any age cohort. The rise of hybrid shopping experiences. Future proofing retail through AI. Want to learn more?

Digital Transformation 76

Digital Transformation Data-driven Uncertainty Strategy 76

IBM Big Data Hub

MARCH 8, 2024

The ecosystem has become more complex as business models advance and new ecommerce trends appear. In recent years, for instance, ecommerce companies based on a subscription model—like Blue Apron and BarkBox— have grown over 1,000%. The ecommerce market has grown exponentially over the last decade.

Consulting 80

Consulting Marketing Sales Data Processing 80

IBM Big Data Hub

OCTOBER 18, 2022

Most admit uncertainty around ROI and nearly half struggle with adequate insights from their data. Learn how CEOs inspire new partnership models to turn sustainability goals into action. Nearly half of CEOs think that sustainability will accelerate business growth.

Uncertainty 52

Uncertainty Strategy Measurement ROI 52

datapine

MAY 31, 2022

More and more CRM, marketing, and finance-related tools use SaaS business intelligence and technology, and even Adobe’s Creative Suite has adopted the model. Businesses can instead access extra processing through pay-as-you-go models from public providers. It is evident that the cloud is expanding.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

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

JULY 22, 2020

For this reason we don’t report uncertainty measures or statistical significance in the results of the simulation. In practice, one may want to use more complex models to make these estimates. For example, one may want to use a model that can pool the epoch estimates with each other via hierarchical modeling (a.k.a.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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. While it is quite clear that statistical data has the potential to be misused, it can also ethically drive market value in the digital world.

Statistics 363

Statistics Advertising Visualization Data mining 363

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

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. It’s harder for many folks in this role who don’t have any data or machine learning background and are thrown or thrust into shipping something like this.

Management 110

Management Machine Learning Experimentation Metrics 110

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. The term “ML” is No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Occam's Razor

APRIL 8, 2013

Let's listen in as Alistair discusses the lean analytics model… The Lean Analytics Cycle is a simple, four-step process that shows you how to improve a part of your business. Another way to find the metric you want to change is to look at your business model. The business model also tells you what the metric should be.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Smart Data Collective

AUGUST 9, 2021

Big data is becoming increasingly important in the cybersecurity profession. A number of IT security professionals are using big data and AI technology to create more robust cybersecurity solutions. As cybersecurity threats become more serious, the demand for data-savvy cybersecurity experts will continue to rise.

Big Data 126

Big Data Consulting Uncertainty IoT 126

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). A model may for example spit out a figure like £12.4 The model is not saying that £12.4

Metrics 49

Metrics Statistics Data Quality Measurement 49

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

The result is that experimenters can’t afford to be sloppy about quantifying uncertainty. These typically result in smaller estimation uncertainty and tighter interval estimates. Rare binary event example In the previous post , we discussed how rare binary events can be fundamental to the LSOS business model.

Experimentation 40

Experimentation Metrics Statistics Measurement 40

Smart Data Collective

APRIL 18, 2019

There’s no question that the term is popping up everywhere as enterprises yearn to turn big data into a competitive edge. While the shared security model is taking some security pressure off the SOC, enterprises who have migrated infrastructure, platforms, and apps do not shed all security responsibilities.

Behavioral Analytics 78

Behavioral Analytics Advertising Uncertainty Machine Learning 78

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.” IBM’s Planning Analytics powerful engine ( TM1 ) allows the use of multiple data cubes to operate in one application.

Analytics 88

Analytics Manufacturing Uncertainty Machine Learning 88

IBM Big Data Hub

MAY 10, 2023

There’s a great deal of uncertainty throughout the business world, but we believe IBM Think offers a moment for our collective industries to come together and discuss solutions. Where more are needed, foundation models within Watson Orchestrate can be used to import existing automations and turn them into skills in minutes.

Enterprise 81

Enterprise Uncertainty ROI Digital Transformation 81