IBM Big Data Hub

FEBRUARY 8, 2024

1 Slowly but surely, institutional investors started to recognize that companies could potentially improve financial performance and risk management by focusing on ESG issues like greenhouse gas emissions. The last decade: an evolving landscape By 2015, the Sustainable Development Goals (SDGs) replaced the MDGs.

Measurement 79

Measurement Metrics Reporting Strategy 79

Smart Data Collective

JUNE 18, 2021

However, big data has also led to some concerns with racial profiling and other biases. Big data and machine learning technology are helping make it more equitable and reducing the burden on the prison system. Predictive Analytics and Big Data Assists with Criminal Justice Reform.

Predictive Analytics 67

Predictive Analytics Forecasting Analytics Big Data 67

Smart Data Collective

AUGUST 21, 2019

A 2015 paper by the World Economic Forum showed that big data might just be a fad. The article certainly raised a lot of controversy, considering the massive emphasis on the value of data technology. The article was not arguing that big data is going to go obsolete. This can lead to a number of problems.

Data Science 67

Data Science Big Data Data Strategy Risk 67

IBM Big Data Hub

FEBRUARY 7, 2024

Investors, regulators and stakeholders are increasingly demanding that companies disclose their exposure to climate-related risks , such as dependence on fossil fuels or vulnerability to weather events. Join the IBM Sustainability Community 1 Green transition creates $10.3T

Reporting 91

Reporting Internet of Things Cost-Benefit Data-driven 91

IBM Big Data Hub

FEBRUARY 22, 2024

Defense leaders focused on operationalizing the responsible curation of AI must first agree upon a shared vocabulary—a common culture that guides safe, responsible use of AI—before they implement technological solutions and guardrails that mitigate risk. Model output is based on the data it was trained on.

Metadata 94

Metadata Measurement Risk Modeling 94

AWS Big Data

MAY 16, 2024

You can now reduce your cluster’s storage and compute capacity by removing sets of brokers, with no availability impact, data durability risk, or disruption to your data streaming applications. MSK performs the necessary validations to safeguard against data durability risks and gracefully removes the brokers from the cluster.

Metrics 72

Metrics Optimization Data Processing Management 72

CIO Business Intelligence

JUNE 7, 2022

It is frequently used for risk analysis. Factor analysis: Factor analysis is a statistical method for taking a massive data set and reducing it to a smaller, more manageable one. Data analysts and others who work with analytics use a range of tools to aid them in their roles. Data analytics and data science are closely related.

Data Analytics 129

Data Analytics Diagnostic Analytics Management Analytics 129

Smart Data Collective

JULY 2, 2019

Big data is playing a surprisingly important role in the evolution of renewable energy. IBM recently published a fascinating paper on the applications of big data for solar and other green energy sources. Other researchers around the world are also talking about the role of data analytics in this dynamic, growing field.

Data Analytics 76

Data Analytics Internet of Things Analytics Big Data 76

Smart Data Collective

APRIL 13, 2021

In the modern world of business, data is one of the most important resources for any organization trying to thrive. Business data is highly valuable for cybercriminals. They even go after meta data. Big data can reveal trade secrets, financial information, as well as passwords or access keys to crucial enterprise resources.

Testing 122

Testing Behavioral Analytics Data-driven Big Data 122

AWS Big Data

NOVEMBER 17, 2023

Doing it before risks unnecessary aggregation overhead because each value is likely unique anyway and that step will not result in an earlier reduction in the amount of data transferred between intermediate stages. Grouping after joining means a large number of records have to participate the join before being aggregated.

Optimization 114

Optimization Statistics Metadata Data Lake 114

In(tegrate) the Clouds

DECEMBER 21, 2015

Merv Adrian (@merv) December 19, 2015. What is the most important news item about a software company that occurred in 2015 that belongs in the capsule, and why? The resurgence of Microsoft as a cloud company was big news in 2015. Who was the biggest tech disruptor in 2015? 2016 will be the year of the data lake.

Technology 45

Technology Internet of Things Digital Transformation Software 45

Smart Data Collective

SEPTEMBER 22, 2021

All blockchains, including Dogecoin are also at risk of a 51% attack. There hasn’t been any update or improvements made to Dogecoin since 2015 and because of that, there is a potential for a decline in it’s value. Of course, any cryptocurrency is going to carry risk. A potential decline.

Risk 115

Risk Marketing Measurement IT 115

datapine

DECEMBER 28, 2021

Drinking tea increases diabetes by 50%, and baldness raises the cardiovascular disease risk up to 70%! Did we forget to mention the amount of sugar put in the tea or the fact that baldness and old age are related – just like cardiovascular disease risks and old age? 29, 2015, Republicans from the U.S. They sure can.

Statistics 363

Statistics Advertising Visualization Data mining 363

IBM Big Data Hub

JUNE 30, 2023

. ​ Automotive supply chain facts Up to 50 percent of unscheduled downtime is due to a lack of spare parts or stockouts ( The Importance of Inventory Optimization in MRO, July 2015 , Aberdeen Group) Generally, 99% of [semiconductor] manufacturing foundries have no visibility where the part is going.

B2B 63

B2B Manufacturing Consulting Forecasting 63

Sisense

FEBRUARY 24, 2021

In fact, in a 2019 edition of Industrial Management & Data Systems, a research team led by Yu Nie noted that prior to the year 2000, there were only six chief data officers in the world. But that number rose sharply afterwards, with the team noting there were over 1,000 people in this role by 2015.

Data Warehouse 69

Data Warehouse Big Data Metrics Visualization 69

IBM Big Data Hub

MARCH 29, 2024

GraphQL GraphQL is a query language and API runtime that Facebook developed internally in 2012 before it became open source in 2015. Each schema specifies the types of data the user can query or modify, and the relationships between the types. GraphQL is defined by API schema written in the GraphQL schema definition language.

Interactive 74

Interactive Digital Transformation Management Optimization 74

Alation

FEBRUARY 20, 2020

With the year coming to a close, many look back at the headlines that made major waves in technology and big data – from Spark to Hadoop to trends in data science – the list could go on and on. The logical data warehouse will mean self-service analytics at a much faster pace. Subscribe to Alation's Blog.

Data Warehouse 52

Data Warehouse Visualization Enterprise Data Science 52

Smart Data Collective

JUNE 26, 2019

More specifically, having an excessive amount of dark data could mean you spend more time searching for data than analyzing it. Or, dark data could open your company to regulatory risks if you cannot retrieve requested information during an audit. Pay Attention to Data Stored on Mobiles and in the Public Cloud.

ROI 102

ROI Statistics Machine Learning Measurement 102

datapine

MAY 9, 2019

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. In a world dominated by data, it’s more important than ever for businesses to understand how to extract every drop of value from the raft of digital insights available at their fingertips.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

Cloudera

AUGUST 6, 2018

For example, Crisis Text Line , which provides online support to people in crisis, received a total of 8 m illion text messages in the first two years of its existence between 2013 and 2015. Indeed, as Stefaan Verhulst, co-founder of GovLab, says : “An increased use of data is not risk-free.

Machine Learning 50

Machine Learning Internet of Things Cost-Benefit Data-driven 50

Cloudera

MAY 16, 2018

This approach also relates to monitoring internal fiduciary risk by tying separate events together, such as a large position (relative to historic norms) being taken immediately after the risk model that would have flagged it was modified in a separate system. Market data: Coordinated trading among multiple parties.

Data Lake 42

Data Lake Risk Visualization Unstructured Data 42

datapine

MARCH 31, 2022

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. The Bureau of Labor Statistics also states that in 2015, the annual median salary for BI analysts was $81,320.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

IBM Big Data Hub

AUGUST 11, 2023

The term was originally coined in 2015 in a published research paper called, “Hidden Technical Debts in the Machine Learning System,” which highlighted common problems that arose when using machine learning for business applications. Reduced risk—Machine learning models need review and scrutiny.

Data Science 54

Data Science Machine Learning Cost-Benefit Deep Learning 54

AWS Big Data

JANUARY 24, 2023

For this post, we copy the New York Taxi Data 2015 dataset from a public S3 bucket. In this solution, the SQL queries preexist in your AWS environment and are DQL statements (they don’t alter the data or structure). However, as you develop this application to fit your business, you should evaluate these areas of risk.

Analytics 59

Analytics Data-driven Management Reporting 59

Rita Sallam

JULY 22, 2016

These intentions are also reflected in Gartner’s previous webinar poll results in March and in our 2015 market share results, which show a 63% growth in Modern BI market growth versus a 1.7% decline in traditional BI ( See: Market Share Analysis: Business Intelligence and Analytics Software, 2015 ).

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

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. Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Cloudera

SEPTEMBER 4, 2018

In 2015, it was reported that the former Malaysian Prime Minister funneled nearly 700 million dollars from 1MDB into his personal account. The third installment introduces an approach that carries AML into the future. Part I: The case for agility.

Reporting 43

Reporting Finance Sales Marketing 43

Occam's Razor

MARCH 30, 2017

Yes, a silo but so much better than 2015. Sidebar: If you don’t know these three phrases, please watch my short talk: A Big Data Imperative: Driving Big Action.]. Insane as it seems like, data collection should get sorted out in the next few years. Not perfect, but so incredible even today. 415 million (!)

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Occam's Razor

AUGUST 28, 2017

415 million diabetic patients worldwide are at risk of Diabetic Retinopathy (DR) – the fastest growing cause of blindness. Literally millions upon millions of people at risk of blindness will have access to AI-Powered technology that can create a different outcome for their life – and their families. An example I love.

Deep Learning 139

Deep Learning Machine Learning Marketing Strategy 139

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. As the article explains, data science is set apart from other business functions by two fundamental aspects: Relatively low costs for exploration. Friction ensued.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Occam's Razor

JANUARY 31, 2017

The reasons are that we all like complexity, it gives us energy :), we tend to be logical, and we often treat data output as the end when in reality the data output is just the start of the process that results in actions that deliver business impact. I'm doing it to have the ability to simplify things, and take risks.

Visualization 148

Visualization IT Strategy Key Performance Indicator 148