O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. Machine learning adds uncertainty.

Management 333

Management Machine Learning Experimentation Metrics 333

CIO Business Intelligence

MAY 29, 2024

For example, a traditional search engine would have a difficult time finding the correct material number for the query “2-inch steel pipe 5 feet” if the long description in the SAP material data is “5ft. other material descriptions including fractions, units of measure, units of sale, etc. DIA steel pipe”.

Sales 100

Sales Modeling Machine Learning Measurement 100

CIO Business Intelligence

OCTOBER 24, 2023

With AI systems often reliant on vast amounts of data, ensuring this data remains private is a significant concern. AI can steal your IP—and generate new IP for you to protect Machine learning algorithms can be trained to reverse-engineer patented technologies. This raises legal and ethical implications.

Risk 124

Risk Recreation/Entertainment Data Collection Data Processing 124

DataRobot

AUGUST 25, 2021

In a recent blog, we talked about how, at DataRobot , we organize trust in an AI system into three main categories: trust in the performance in your AI/machine learning model , trust in the operations of your AI system, and trust in the ethics of your modelling workflow, both to design the AI system and to integrate it with your business process.

Metrics 98

Metrics Measurement Machine Learning Data Collection 98

Smart Data Collective

MARCH 29, 2021

Asset data collection. Data has become a crucial organizational asset. Companies need to make the most out of their data resources, which includes collecting and processing them correctly. Data collection and processing methods are predicted to optimize the allocation of various resources for MRO functions.

Big Data 137

Big Data Management Cost-Benefit Internet of Things 137

Rocket-Powered Data Science

JULY 7, 2019

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Examples: (1-3) All those applications shown in the definition of Machine Learning. (4)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. These measures are commonly referred to as guardrail metrics , and they ensure that the product analytics aren’t giving decision-makers the wrong signal about what’s actually important to the business.

Marketing 362

Marketing Experimentation Metrics Testing 362

Smart Data Collective

MAY 29, 2023

To help you better understand what machine learning biases are, we have listed some of the biases that machine translation companies encounter that affect the performance of their translation system. AI translation models must collect and annotate data fairly.

Metrics 68

Metrics Measurement Data Collection Strategy 68

Smart Data Collective

DECEMBER 17, 2021

The process of Marketing Analytics consists of data collection, data analysis, and action plan development. Understanding your marketing data to make more informed and successful marketing strategy decisions is a systematic process. Types of Data Used in Marketing Analytics. Preparing the Data for Analysis.

Marketing Analytics 93

Marketing Analytics Marketing Data-driven Analytics 93

CIO Business Intelligence

JULY 5, 2022

Business analytics can help you improve operational efficiency, better understand your customers, project future outcomes, glean insights to aid in decision-making, measure performance, drive growth, discover hidden trends, generate leads, and scale your business in the right direction, according to digital skills training company Simplilearn.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Smart Data Collective

OCTOBER 16, 2023

Examples include CCTV records, automated vacuum cleaners, weather station data, and other sensor-generated data. All in all, big data refers to massive data collections obtained from various sources. Big data can also be utilized to improve security measures.

Big Data 101

Big Data IoT Cost-Benefit Advertising 101

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. Alex Ratner on “Creating large training data sets quickly”.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

datapine

JANUARY 6, 2022

Yet, before any serious data interpretation inquiry can begin, it should be understood that visual presentations of data findings are irrelevant unless a sound decision is made regarding scales of measurement. For a more in-depth review of scales of measurement, read our article on data analysis questions.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

CIO Business Intelligence

JANUARY 17, 2024

The first was becoming one of the first research companies to move its panels and surveys online, reducing costs and increasing the speed and scope of data collection. According to Mohammed, the results of this digital transformation journey are measurable and impressive.

Digital Transformation 118

Digital Transformation Dashboards Reporting Data Science 118

CIO Business Intelligence

MARCH 30, 2022

For organizations looking to move beyond stale reports, decision intelligence holds promise, giving them the ability to process large amounts of data with a sophisticated mix of tools such as artificial intelligence and machine learning to transform data dashboards and business analytics into more comprehensive decision support platforms.

Machine Learning 144

Machine Learning Testing Risk Data-driven 144

Smart Data Collective

JULY 9, 2023

Collecting Relevant Data for Conversion Rate Optimization Here is some vital data that e-commerce businesses need to collect to improve their conversion rates. Identifying Key Metrics for Conversion Rate Optimization Data collection and analysis are both essential processes for optimizing your conversion rate.

Optimization 73

Optimization Data Analytics Analytics Data-driven 73

CIO Business Intelligence

AUGUST 25, 2023

Hot Melt Optimization employs a proprietary data collection method using proprietary sensors on the assembly line, which, when combined with Microsoft’s predictive analytics and Azure cloud for manufacturing, enables P&G to produce perfect diapers by reducing loss due to damage during the manufacturing process.

Predictive Analytics 98

Predictive Analytics IoT Manufacturing Analytics 98

CIO Business Intelligence

APRIL 14, 2022

The ability to provide transparent, data-driven insights and measure progress toward ESG commitments makes the technology leader critical to the success of any ESG strategy. Smarter operations through integrated data and analytics. After understanding the current state, think about which goals the technology function can drive.

Strategy 110

Strategy Digital Transformation IoT Measurement 110

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data Science 53

Data Science Machine Learning Cost-Benefit Deep Learning 53

Decision Management Solutions

JUNE 8, 2023

Do you have a business problem that would benefit from advanced decision automation and machine learning? This project is a beautiful example of combining a wide variety of technology to answer complicated questions. This project is a beautiful example of combining a wide variety of technology to answer complicated questions.

Machine Learning 40

Machine Learning Measurement Data Collection Management 40

IBM Big Data Hub

SEPTEMBER 6, 2023

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?

Marketing 79

Marketing Technology Advertising ROI 79

IBM Big Data Hub

FEBRUARY 7, 2024

This can be quantified by measuring metrics like tree cover, habitat integrity and number of species, and is guided by sustainable development principles. .” Similar to “carbon neutral” in the context of emissions, nature positive refers to stopping, avoiding and reversing environmental destruction.

Reporting 90

Reporting Internet of Things Cost-Benefit Data-driven 90

BizAcuity

JULY 7, 2020

With respect to developments or changes in inbound markets, gaming data, player statistics, economic recovery speed, and more, adjust and reiterate core strategies. A crucial part of business recovery is to show and reassure people that all the precautionary measures are being taken to ensure safety. This too shall pass.

Revenue Optimization 98

Revenue Optimization Measurement Interactive Marketing 98

Decision Management Solutions

FEBRUARY 8, 2021

As you’ll see, the development of this amazing, one-of-a-kind vessel led to a conclusion that we at Decision Management Solutions see every day in our client work: It’s never enough to just rely on artificial intelligence (AI)/machine learning (ML) to do all the decision-making.

Machine Learning 93

Machine Learning Testing Deep Learning Optimization 93

CIO Business Intelligence

SEPTEMBER 2, 2022

In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems. Back-end software engineer.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems. Back-end software engineer.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

NOVEMBER 22, 2022

“Failing to meet these needs means getting left behind and missing out on the many opportunities made possible by advances in data analytics.” The next step in every organization’s data strategy, Guan says, should be investing in and leveraging artificial intelligence and machine learning to unlock more value out of their data.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

IBM Big Data Hub

SEPTEMBER 27, 2022

This includes data collection, instrumenting processes and transparent reporting to make needed information available for all the stakeholders. The chief data officer saw that it was essential for the company to have a holistic framework, which would work with the models built across the company, using all these diverse tools.

Consulting 52

Consulting Machine Learning Modeling Strategy 52

Sisense

OCTOBER 29, 2020

“Data is a critical factor in getting to where we need to be,” explained Ramsey. AVs are the most advanced version of artificial intelligence (AI) that we are working on right now and require an enormous amount of data to do machine learning to improve the computer’s ability to understand the world and make decisions.

Machine Learning 90

Machine Learning Data Collection Cost-Benefit Advertising 90

FineReport

AUGUST 4, 2021

Provide a new way of data discovery. New data collection technologies like devices for Internet of Things (IoT) are providing companies with massive amounts of real-time data. This is different from any previous ways of collecting data. In this information age, data is a valuable asset for any business.

Business Intelligence 98

Business Intelligence Data-driven Dashboards Internet of Things 98

Cloudera

AUGUST 6, 2021

This data needs to be harmonized in a way that presents a unified view of the customer journey and ideally a real-time view of their propensity to perform certain actions, with suggested options to increase or decrease that propensity. Strategy and culture are core components of a data driven organization .

Data-driven 105

Data-driven B2B Data Strategy Strategy 105

Domino Data Lab

OCTOBER 2, 2019

This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications by Andrew Kelleher and Adam Kelleher. You’ll measure this effect by looking at a quantity called the average treatment effect (ATE).

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

Jet Global

SEPTEMBER 29, 2021

Data-driven Finance leaders use metrics to look at what the business should do next, rather than only look back at how well they performed in the past. They use data and software with machine learning (artificial intelligence) to model and compare ‘what-if’ scenarios to grow the business. Provide Access to Quality Data.

Data-driven 52

Data-driven Finance Data Collection Metrics 52

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Alation

JANUARY 26, 2023

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. This is “table stakes” for any data governance program!).

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

CIO Business Intelligence

AUGUST 1, 2023

Data collection on tribal languages has been undertaken for decades, but in 2012, those working at the Myaamia Center and the National Breath of Life Archival Institute for Indigenous Languages realized that technology had advanced in a way that could better move the process along.

Risk 98

Risk IT Software Digital Transformation 98

IBM Big Data Hub

FEBRUARY 23, 2024

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. Marketing and sales: Conversational AI has become an invaluable tool for data collection. It assists customers and gathers crucial customer data during interactions to convert potential customers into active ones.

Enterprise 96

Enterprise Interactive Data-driven Key Performance Indicator 96