CIO Business Intelligence

MARCH 25, 2022

Two years of pandemic uncertainty and escalating business risk have sharpened the focus of corporate boards on a technology trend once dismissed as just another IT buzzword. We do this work because of those data benefits: the ability to apply AI or machine learning in ways that drive greater business insights.

Digital Transformation 113

Digital Transformation Uncertainty Machine Learning Strategy 113

Cloudera

MAY 15, 2018

Cloudera Enterprise is the market leader in this space and working closely with the wider open source community to integrate the latest innovations in machine learning and artificial intelligence (AI). Derman (2016), Cesa (2017) & Bouchard (2018)). Blog Post, Nov-2016. A Stylized History of Quantitative Finance”.

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

Smart Data Collective

FEBRUARY 23, 2023

Deep Learning is a concept that first arose in 2006, with Geoffrey Hinton’s DNNs (Deep Neural Networks) training concept. The learning potential of deep learning was further demonstrated by AlphaGo in 2016 and, today, it is used increasingly to create high level software engineering (SE) tools.

Deep Learning 94

Deep Learning Software Risk Testing 94

Occam's Razor

MARCH 30, 2017

While the phrase Artificial Intelligence has been around since the first human wondered if she could go further if she had access to entities with inorganic intelligence, it truly jumped the shark in 2016. Machine Learning | Marketing. Machine Learning | Analytics. trillion pictures in 2016. Google Photos.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Smart Data Collective

MAY 21, 2019

In 2016, cyber-attacks cost the United States economy between $57 billion and $109 billion. There are several ways that predictive analytics is helping organizations prepare for these challenges: Predictive analytics models are helping organizations develop risk scoring algorithms. Cybersecurity is becoming a greater concern than ever.

Big Data 77

Big Data Cost-Benefit Predictive Analytics Insurance 77

Smart Data Collective

JULY 8, 2019

between 2016 and 2017. Companies around the world are facing rising risks of accidents. New predictive analytics and machine learning technology should address these concerns. Accident data provides insight and valuable information that can be used to help improve safety in the future. increased by 5.3%

Big Data 77

Big Data Measurement Reporting Predictive Analytics 77

Cloudera

SEPTEMBER 20, 2022

It’s impossible to anticipate every risk or mode of misuse, but those below were suggested in my readings and by my colleagues. These risks don’t admit easy answers, but it’s important to have a clear-eyed perspective on how technology could be misused. Cham: Springer International Publishing, 2016. Misuse — what could go wrong?

Deep Learning 85

Deep Learning Cost-Benefit Risk Data-driven 85

Cloudera

SEPTEMBER 28, 2020

ACID transactions, ANSI 2016 SQL SupportMajor Performance improvements. Data Science and machine learning workloads using CDSW. In order to minimize risk and downtime, the upgrades were performed in that order and the learning from each upgrade was applied to the next upgraded environment. New Features CDH to CDP.

Testing 130

Testing Metadata Risk Data Science 130

Alation

FEBRUARY 13, 2020

In The Forrester Wave: Machine Learning Data Catalogs, 36% to 38% of global data and analytics decision makers reported that their structured, semi-structured, and unstructured data each totaled 1,000 TB or more in 2017, up from only 10% to 14% in 2016.

ROI 52

ROI Cost-Benefit Unstructured Data Data Lake 52

Jen Stirrup

OCTOBER 3, 2019

The future is likely to be even more defined by the technology that is currently evolving – and if companies neglect to take a practical, thoughtful and responsible approach to implementing and developing this software, they run the risk of not being able to catch up with the consequences. . Credit: Microsoft ( [link] ).

Technology 40

Technology Machine Learning Interactive Risk 40

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. Introduction Machine learning models often behave unpredictably, as data scientists would be the first to tell you. A more general approach is to learn a Generalized Additive Model (GAM).

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Smart Data Collective

NOVEMBER 1, 2019

They can use big data and machine learning for multiple uses. Big Data Offers Powerful Solutions to Home Security Risks. Markets and Markets found that the home security market will be worth $113 billion by 2021 , which is a 50% increase from 2016. They can also use smart technology to control smart security tools.

Big Data 46

Big Data Marketing Risk Machine Learning 46

bridgei2i

MAY 26, 2020

It is even more essential now that supply chains are empowered with a high standard of data and analytics sophistication to be able to cost-effectively serve the company’s purpose and combat risks at the same time. You know, Chief Risk Officers, for example, will no longer be confined to the credit industry. Anushruti: Perfect.

Enterprise 131

Enterprise Management Forecasting Manufacturing 131

Smart Data Collective

MARCH 22, 2019

In 2016, household incomes rose enough for families to buy a home that was 1.5 New models use the latest geographic, economic and demographic data to minimize the risk of mistakes when analyzing properties. We can also better analyze the state of the market and the mortgage industry. times the median home price.

Big Data 66

Big Data Cost-Benefit Marketing Strategy 66

CIO Business Intelligence

MARCH 22, 2022

At Fractal, Tiwari will be responsible for the company’s digital transformation and overseeing IT operations, cybersecurity, and risk management. . In his 20 years’ experience in IT, Verma has led work on security, risk compliance, IoT, RPA, cloud, and business continuity planning. He was a recipient of a 2016 CIO100 India award.

Internet Publishing and Broadcasting 98

Internet Publishing and Broadcasting Digital Transformation Insurance Recreation/Entertainment 98

Smart Data Collective

JUNE 14, 2019

In 2016, this was demonstrated by IBM when they developed a new machine learning algorithm to edit the video footage for the trailer for the upcoming horror film Morgan. The machine learning algorithms were able to process the steps in a much more systematic way than a human editor would have been able to.

Risk 88

Risk Software Machine Learning Metrics 88

CIO Business Intelligence

APRIL 15, 2022

And 20% of IT leaders say machine learning/artificial intelligence will drive the most IT investment. Insights gained from analytics and actions driven by machine learning algorithms can give organizations a competitive advantage, but mistakes can be costly in terms of reputation, revenue, or even lives.

Analytics 145

Analytics Machine Learning Insurance Testing 145

Domino Data Lab

JANUARY 6, 2019

What are the projected risks for companies that fall behind for internal training in data science? Meanwhile, employers who are betting that their teams accomplish substantial projects in data science, machine learning, data engineering, artificial intelligence, etc., Hands-on Machine Learning with Scikit-Learn and TensorFlow.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

Insight

MARCH 18, 2019

Bias in Machine Learning Algorithms (Bottom Photos Source: ProPublica ; Top Photos Source: Pexels.com) Biases in predictive modeling are a widespread issue Machine learning and AI applications are used across industries, from recommendation engines to self-driving cars and more. 5 is labeled as low.

Machine Learning 77

Machine Learning Predictive Modeling Modeling Metrics 77

IBM Big Data Hub

NOVEMBER 10, 2023

By taking advantage of solutions like IBM Cloud® HPC , organizations can more effectively manage their peak workloads while mitigating the risk of downtime. The role of a hybrid cloud solution for HPC Cadence started its public cloud journey in 2016 and now operates with a hybrid, multicloud approach, which includes IBM.

Manufacturing 85

Manufacturing Cost-Benefit Optimization Software 85

Rita Sallam

JULY 22, 2016

Gartner revamped the BI and Analytics Magic Quadrant in 2016 to reflect the mainstreaming of this market disruption. The risk of switching existing system of record reporting that is working may be higher than the benefit, so the 45% of you maintaining these systems makes sense, but increasing users and content?

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

CIO Business Intelligence

JUNE 22, 2022

Around 2016, we started talking about data in motion within the context of an enterprise data platform. The financial services industry has had to dedicate more resources to personalisation, fighting fraud, and reducing cloud concentration risk. It can be “at rest”, “in use”, or “in motion”.

IoT 96

IoT IT Manufacturing Internet of Things 96

Cloudera

APRIL 27, 2022

Around 2016, we started talking about data in motion within the context of an enterprise data platform. The financial services industry has had to dedicate more resources to personalisation, fighting fraud, and reducing cloud concentration risk. It can be “at rest”, “in use”, or “in motion”.

IoT 94

IoT IT Manufacturing Internet of Things 94

Domino Data Lab

AUGUST 8, 2019

Having participated in several Foo Camps—and even co-chaired the Ed Foo series in 2016-17— most definitely, a Foo will turn your head around. Latest in machine learning research centers rapidly expanding in Africa? then building machine learning models to recommend methods and potential collaborators to scientists.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

CIO Business Intelligence

JULY 20, 2023

Like with any powerful new technology (think: the internet, the printing press, nuclear power), there are great risks to consider. There is a risk if we don’t clarify machine learning, deep learning, and generative AI – plus when you would use one versus the other.” Artificial Intelligence, Machine Learning

Risk 40

Risk Machine Learning Deep Learning Interactive 40

Smart Data Collective

DECEMBER 19, 2019

According to GlobeNewswire , over 61% of business professionals agree that AI and Machine Learning are the most significant data initiative in their organizations. Different machine learning and AI systems consume a massive amount of data. Thus, AI learns to provide perfect predictions on the next possible step.

Machine Learning 61

Machine Learning Reporting Testing Marketing 61

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. An ML-related topic, “models,” was No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

datapine

AUGUST 29, 2022

James Warren, on the other part, is a successful analytics architect with a background in machine learning and scientific computing. The book has three main ideas: The biggest risk your company faces is investing a lot of time and resources into building something that the market doesn’t want.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

The Unofficial Google Data Science Blog

APRIL 23, 2024

Risk and Robustness Our estimates $widehat{beta}$ of the "true'' coefficients $beta$ of our model (1) depend on the random data we observe in experiments, and they are therefore random or uncertain. 17:263-287, 2016. [10] Controlling Risks under Different Loss Functions: The Compromise Decision Problem. Domahidi, E. Chu, and S.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

The Data Visualisation Catalogue

FEBRUARY 16, 2023

However, the fear is that if AI tools continue to develop in the direction it’s currently going in, a lot of white-collar workers will be at risk of losing their job. By utilising automation and machine learning algorithms, analysing massive datasets could be made a lot easier.

Dashboards 122

Dashboards Consulting Machine Learning Technology 122

Cloudera

JANUARY 22, 2019

Big Data Fabric supports a variety of use cases ranging from real-time insights and machine learning to streaming and advanced analytics. Source: Big Data Fabric Drives Innovation And Growth, Noel Yuhanna, March 8 2016. What Use Cases does Big Data Fabric support? Shared Data Catalog to preserve context and enforce Governance.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. 2016) for an example of this technique (LIME).

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Alation

FEBRUARY 1, 2022

Most traditional governance methods involve cumbersome manual processes; spreadsheets and human-led documentation of policies in numerous patchwork systems translate to a lot more searching, manual updating, and the risk of exposing one’s data. Between 2016 and 2019, robot-vacuum cleaner sales jumped by 13% year over year.

Data Lake 52

Data Lake Data Governance ROI Cost-Benefit 52

Smart Data Collective

MAY 18, 2021

A lot of investors are using AI to boost the performance of their portfolios and find the right level of risk. Kerry, who also signed the Paris Climate Accord on behalf of the US in 2016, has also spoken at length about how big banks and financial institutions are continuing to invest heavily in green business. How is AI used by Tesla?

Marketing 73

Marketing Big Data Deep Learning Machine Learning 73

O'Reilly on Data

MAY 11, 2020

Television only lacked the immediate feedback that comes with clicks, tracking cookies, tracking pixels, online experimentation, machine learning, and “agile” product cycles. That loop isn’t new, of course; it was well-known to TV network executives. Does “The Entertainment” show people what they want to see?

Modeling 190

Modeling Advertising Recreation/Entertainment Metrics 190