CIO Business Intelligence

MAY 11, 2022

What mobile money licenses will provide to Nigeria is the ability for fintechs to move beyond the traditional model of a bank-provided account,” Straub says. According to a 2010 GSMA report , the growth of banks had stalled but mobile penetration was skyrocketing. But don’t expect to see staunch competition as yet, Straub says.

Marketing 111

Marketing Insurance Reporting Consulting 111

CIO Business Intelligence

MARCH 25, 2022

When Forrester coined the Zero Trust security model in 2010, they were looking to represent a methodology for how to transact business securely based on the principle of “never trust, always verify.” It was a data-centric model where you don’t trust anything going on inside or outside of the perimeter.

Software 52

Software Risk Strategy Reporting 52

Cloudera

AUGUST 17, 2020

This is opening up new revenue opportunities, use cases and even the possibility for different types of business models within the sector, changing the way that CSPs operate. . In many established markets, traditional sources of revenue are either plateauing or declining relatively rapidly. .

IoT 96

IoT Internet of Things B2B Data-driven 96

Smart Data Collective

AUGUST 30, 2020

One of the biggest changes of an age of technology, is the entrance of “big data” into the world, which got noticed, globally, around 2010. Meanwhile, traditional strategies and models are increasingly unlikely to lead to future market success.”. The report’s lead author, a Senior Fellow at the Center, James W.

Big Data 141

Big Data Data-driven Insurance Marketing 141

Jen Stirrup

FEBRUARY 1, 2023

The effects of AI will be magnified in the coming decade as manufacturing, retailing, transportation, finance, health care, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning.

Recreation/Entertainment 62

Recreation/Entertainment Testing Advertising Insurance 62

CIO Business Intelligence

FEBRUARY 14, 2024

That’s not just about the cost of preparing a larger data set than you need, which takes expertise that’s still uncommon and commands a high salary, but also what you’re teaching the model. The same issues were revealed when Microsoft launched Delve, and before that when the FAST integration brought powerful search to SharePoint in 2010.

IT 143

IT Metadata Data-driven Management 143

CIO Business Intelligence

APRIL 24, 2023

Generative AI (Artificial Intelligence) and its underlying foundation models represent a paradigm shift in innovation, significantly impacting enterprises exploring AI applications. These foundation models are trained on vast amounts of data. The model can then predict or classify new, previously unseen data.

Enterprise 52

Enterprise Deep Learning Modeling Machine Learning 52

DataRobot

JULY 6, 2021

The Behavioural Insights Team, also known unofficially as the “Nudge Unit,” was founded by the UK government in 2010 to use behavioral science to make public policies and services more effective. More recent research, “ Modeling Users’ Activity on Twitter Networks: Validation of Dunbar’s Number ,” has.

Marketing 105

Marketing Sales Data-driven Statistics 105

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. This is like a denial-of-service (DOS) attack on your model itself.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

Smart Data Collective

JANUARY 27, 2022

Did you know that big data consumption increased 5,000% between 2010 and 2020 ? A skilled professional has to know both the field for which the object is created and 3D modeling. This should come as no surprise. It is going to continue to change the workforce in the process.

Big Data 128

Big Data Advertising Internet of Things Marketing 128

Cloudera

SEPTEMBER 8, 2020

This is opening up new revenue opportunities, use cases, and even the possibility for different types of business models within the sector, changing the way that CSPs operate. . In many established markets, traditional sources of revenue are either plateauing or declining relatively rapidly. .

IoT 69

IoT Internet of Things B2B Data-driven 69

Domino Data Lab

AUGUST 5, 2019

As more companies become model-driven , data scientists are uniquely positioned to drive innovation and to help their companies remain economically strong. the model context ) when building and using models enable data scientists to directly impact business problems. data munging, building models, etc.).

Data Science 93

Data Science Data-driven Modeling Machine Learning 93

DataRobot Blog

AUGUST 23, 2019

We started with the result of every match (and set scores) for ATP and WTA tour matches from 2010 through 2018. Once we had built this prediction model , we could take the draw of any tournament and simulate the results 100,000 times to find out how often each player would win with that particular draw. Andrew received his Ph.D.

Predictive Modeling 52

Predictive Modeling Modeling Marketing Analytics Data Science 52

BizAcuity

FEBRUARY 15, 2019

Sales Analytics in simple terms can be defined as the process used to identify, understand, predict and model sales trends and sales results and in this process of understanding of these trends helps its users in finding improvement points.

Sales 67

Sales Analytics B2B ROI 67

Mark Raskino

FEBRUARY 25, 2019

By about 2010 or so – digital meant market facing technology, and “IT” meant back office and the internal efficiency use of technology. Digital equaled customer facing. So far, so good. But from there on a problem started to arise. Digital was more exciting. But it’s all digital now. So – is it R.I.P. IT?

IT 49

IT Marketing Technology Interactive 49

Domino Data Lab

APRIL 3, 2019

Instead, we must build robust ML models which take into account inherent limitations in our data and embrace the responsibility for the outcomes. As the story goes, the general history of DG is punctuated by four eras: “Application Era” (1960–1990) – some data modeling, ?though More Policies Emerged” (2010-2018).

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

FineReport

APRIL 26, 2023

For example, a computer manufacturing company could develop new models or add features to products that are in high demand. With Big Data Analytics, businesses can make better and quicker decisions, model and forecast future events, and enhance their Business Intelligence. How to Choose the Right Big Data Analytics Tools?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Timo Elliott

JANUARY 10, 2022

Most people rent skis rather than buying, because it’s easier and cheaper and more convenient — so why not apply that model to more things? I also loved the episode The Race to Zero: Regenerative Business Models for a Sustainable Future. I’ve been talking about them for a long time. with the CTO of SAP Fieldglass.

Data Processing 121

Data Processing Manufacturing Machine Learning Technology 121

O'Reilly on Data

SEPTEMBER 19, 2023

Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools. While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.” And it was good.

Machine Learning 247

Machine Learning Testing Modeling Cost-Benefit 247

Paul DeBeasi

JANUARY 27, 2011

In 2010, the Federal Communications Commission (FCC) released America’s first national broadband plan (see [link] ). In that plan, they stressed the need to (a) make 500 MHz of new spectrum available, and (b) expand opportunities for innovative spectrum access models.

Reporting 40

Reporting Data Processing Enterprise Management 40

CIO Business Intelligence

FEBRUARY 26, 2024

Organizations have implemented a variety of workforce models over the last two decades or so, but each has eventually proved to leave them with more questions than answers. Fast forward to today.

Cost-Benefit 98

Cost-Benefit Measurement Modeling Strategy 98

CIO Business Intelligence

NOVEMBER 20, 2023

The emergence of Siri in 2010 ushered in a new era of conversational assistants. These small language models (SLMs) require much less data for training and less complexity. By 2027, Gartner projects that 1 in 4 organizations will rely on bots as their primary customer support channels. CEO Robb Wilson.

Machine Learning 123

Machine Learning Data-driven Software Interactive 123

Occam's Razor

JANUARY 6, 2010

Before all the excitement of the new year wears out, here are five simple things I would love for you to try so that your company will have a glorious truly data driven 2010! #1: You don't have to be armed with the knowledge of how to create various models or be able to jump into SAS and get naked with it. 1: Don't suck.

Analytics 99

Analytics IT Statistics Metrics 99

CIO Business Intelligence

JUNE 13, 2023

As chief digital officer of Kotak Mahindra Bank, Deepak Sharma has been instrumental in driving the bank’s digital transformation, future-ready initiatives, and business model innovation strategies. As I was setting up the NRI banking and remittance platform in 2010, I started getting involved with technology.

IT 105

IT Digital Transformation Uncertainty Risk Management 105

BizAcuity

MAY 10, 2022

Amazon strategically went with the pricing model of ‘on-demand’, allowing developers to pay only as-per their computational needs. The platform was acquired by Salesforce in 2010 for over USD $200 million. 2010: Windows Azure is now Microsoft Azure (IaaS) aggressively trying to penetrate into the cloud market with a redefined strategy.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

bridgei2i

AUGUST 11, 2020

You know that, when we went through the last business downturn, 2008 in 2009, funny thing happened in 2010 turnover went up dramatically in sales and because companies started hiring again. There’s also going to be challenges and we have no idea how to model this. And so you’ve got to ask yourself a question.

Sales 98

Sales Enterprise B2B Digital Transformation 98

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. This post describes the bsts software package, which makes it easy to fit some fairly sophisticated time series models with just a few lines of R code. by STEVEN L. Forecasting (e.g.

Forecasting 64

Forecasting Statistics Modeling Software 64

CIO Business Intelligence

MAY 9, 2022

By 2010, Netflix had grabbed a 20% share of North American viewership while Blockbuster was delisted from the New York Stock Exchange and filed for bankruptcy. Business leaders must be aware of this disruption and how it might impact business models and customers. Blockbuster, then valued at US$4.8 It was ironic.

Digital Transformation 98

Digital Transformation Insurance Interactive Risk Management 98

O'Reilly on Data

JULY 20, 2021

When we’re building shared devices with a user model, that model quickly runs into limitations. That model doesn’t fit reality: the identity of a communal device isn’t a single person, but everyone who can interact with it. With enough data, models can be created to “read between the lines” in both helpful and dangerous ways.

Risk 304

Risk Software Interactive Modeling 304

Smart Data Collective

JANUARY 13, 2021

A Gallup poll conducted back in 2010 found that most Internet users were willing to pay for online privacy. They have discovered that their Internet commerce models are particularly dependent on advances in machine learning. However, these data driven strategies require them to collect as much data on their customers as possible.

Big Data 87

Big Data Machine Learning Data-driven Manufacturing 87

CIO Business Intelligence

AUGUST 29, 2023

Since 2010, TeraSky has provided end-to-end solutions to enable customers to handle data center modernization and hybrid and multi-cloud implementation. First, they transitioned to a SaaS business model while tripling their workforce—all during the pandemic.

Digital Transformation 52

Digital Transformation Optimization Data-driven Management 52

Ontotext

DECEMBER 30, 2022

We have exciting success stories, including the first and popular mission critical implementation of knowledge graphs – BBC’s website for the FIFA world cup in 2010. However, developing these models from scratch for each and every solution can be slow, expensive and risky.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

Ontotext

DECEMBER 30, 2022

We have exciting success stories, including the first and popular mission critical implementation of knowledge graphs – BBC’s website for the FIFA world cup in 2010. However, developing these conceptual models for better data interpretation from scratch for each solution can be slow, expensive and risky.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

Octopai

JUNE 16, 2021

Basel III was drafted in 2010, with finalization and implementation set to take place over the next several years. IRB (internal-ratings based) models were absolutely fine under Basel II. That left plenty of room open for banks to choose the internal models that proved that they didn’t need all that much capital.

Management 52

Management Risk Management Risk Visualization 52

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

The Unofficial Google Data Science Blog

JULY 22, 2020

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. These MAB algorithms are great at maximizing reward when the models are perfectly specified and probabilities are accurate.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Ontotext

JULY 29, 2021

One of its pillars are ontologies that represent explicit formal conceptual models, used to describe semantically both unstructured content and databases. And while not all knowledge graphs (see Adoption of Knowledge Graphs, late 2019 ) are built the semantic modelling way , they all have benefited from the Semantic Web.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124