Rocket-Powered Data Science

MARCH 19, 2021

This article quotes an older market projection (from 2019) , which estimated “the global industrial IoT market could reach $14.2 Focus on specific data types: e.g., time series, video, audio, images, streaming text (such as social media or online chat channels), network logs, supply chain tracking (e.g., trillion by 2030.”.

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

TDAN

AUGUST 17, 2021

If you are planning on using predictive algorithms, such as machine learning or data mining, in your business, then you should be aware that the amount of data collected can grow exponentially over time.

Predictive Modeling 115

Predictive Modeling Modeling Data mining Big Data 115

O'Reilly on Data

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations.

Machine Learning 277

Machine Learning Risk Management Statistics 277

O'Reilly on Data

JANUARY 28, 2019

Almost everyone who reads this article has consented to some kind of medical procedure; did any of us have a real understanding of what the procedure was and what the risks were? The problems with consent to data collection are much deeper. Helen Nissenbaum, in an interview with Scott Berinato , articulates some of the problems.

Insurance 246

Insurance Metadata Data Collection Marketing 246

Analytics Vidhya

SEPTEMBER 13, 2022

This article was published as a part of the Data Science Blogathon. Introduction With technological evolution, data dependence is increasing much faster. Organizations are now employing data-driven approaches all over the world. One of the most widely used data applications […].

Predictive Analytics 291

Predictive Analytics Analytics Data-driven Data Science 291

O'Reilly on Data

JULY 20, 2021

In the first article of this series, we discussed communal computing devices and the problems they create–or, more precisely, the problems that arise because we don’t really understand what “communal” means. When we’re building shared devices with a user model, that model quickly runs into limitations.

Risk 335

Risk Software Interactive Modeling 335

Rocket-Powered Data Science

JUNE 17, 2022

Synthetic monitoring is essentially digital twinning of your network and IT environment, providing insights through simulated risks, attacks, and anomalies via predictive and prescriptive modeling. Disclaimer: I was compensated as an independent freelance media influencer for my participation at the conference and for this article.

Machine Learning 238

Machine Learning Recreation/Entertainment Risk Business Objectives 238

CIO Business Intelligence

JANUARY 14, 2025

They achieve this through models, patterns, and peer review taking complex challenges and breaking them down into understandable components that stakeholders can grasp and discuss. This comprehensive model helps architects become true enablers of organizational success. Most importantly, architects make difficult problems manageable.

Enterprise 119

Enterprise Technology Metrics Measurement 119

Smart Data Collective

MARCH 24, 2020

Big Data can be a powerful tool for transforming learning, rethinking approaches, narrowing longstanding gaps, and tailoring experience to increase the effectiveness of the educational system itself. Now it has become so popular that you can even get data structure assignment help from professionals. Data collection.

Big Data 120

Big Data Internet Publishing and Broadcasting Broadcasting Data Collection 120

CIO Business Intelligence

JULY 11, 2022

To meet the customer demands of a digital-first business model, retailers need to address their critical digital infrastructure and rethink network design and cybersecurity. This article outlines the major considerations and types of solutions retailers should consider to enable fast, reliable, and secure networks and digital business.

Modeling 98

Modeling IoT Cost-Benefit Management 98

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

Rocket-Powered Data Science

MAY 21, 2024

To see this, look no further than Pure Storage , whose core mission is to “ empower innovators by simplifying how people consume and interact with data.” See additional references and resources at the end of this article. In deep learning applications (including GenAI, LLMs, and computer vision), a data object (e.g.,

Cost-Benefit 239

Cost-Benefit Unstructured Data Enterprise Technology 239

CIO Business Intelligence

APRIL 29, 2022

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. About Andrew P.

Data Governance 145

Data Governance IT Risk Data Lake 145

Rocket-Powered Data Science

JULY 7, 2019

Autonomous Vehicles: Self-driving (guided without a human), informed by data streaming from many sensors (cameras, radar, LIDAR), and makes decisions and actions based on computer vision algorithms (ML and AI models for people, things, traffic signs,…). Examples: Cars, Trucks, Taxis. See [link]. 2) Connected cars. (3) 5) Industry 4.0.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

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.

Marketing Analytics 122

Marketing Analytics Marketing Data-driven Analytics 122

Smart Data Collective

MARCH 23, 2022

Well, if you are someone who has loads of data and aren’t using it for your surveys and you would love to learn more on how to use it, don’t go anywhere because, in this article, we will show you data mining tips you can use to leverage your surveys. 5 data mining tips for leveraging your surveys.

Data mining 133

Data mining Marketing Data Collection Insurance 133

datapine

JANUARY 6, 2022

Interval: a measurement scale where data is grouped into categories with orderly and equal distances between the categories. For a more in-depth review of scales of measurement, read our article on data analysis questions. Quantitative analysis refers to a set of processes by which numerical data is analyzed. Dependable.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

Smart Data Collective

NOVEMBER 14, 2019

They have refined their data decision-making approaches to include new predictive analytics models to forecast trends and adapt to evolving customer behavior. They have developed analytics models to address looming changes in the dynamic industry. Time series models that attempt to forecast future variable behavior.

Predictive Analytics 100

Predictive Analytics Analytics Forecasting Statistics 100

Smart Data Collective

OCTOBER 8, 2023

This article delves into the profound impact data analytics can have on fast food legal cases. The Power of Data Analytics: An Overview Data analytics, in its simplest form, is the process of inspecting, cleansing, transforming, and modeling data to unearth useful information, draw conclusions, and support decision-making.

Data Analytics 125

Data Analytics Analytics Statistics Data Collection 125

Smart Data Collective

NOVEMBER 24, 2020

In this article, you’ll discover: upcoming trends in business intelligence what benefits will BI provide for businesses in 2020 and on? The strategic decision-making in the future of business intelligence will be shaped by faster reports, deeper data insights, broader areas of data collection. Identify Opportunities.

Business Intelligence 134

Business Intelligence Visualization Dashboards Prescriptive Analytics 134

Smart Data Collective

MAY 28, 2021

Data security and data collection are both much more important than ever. Every organization needs to invest in the right big data tools to make sure that they collect the right data and protect it from cybercriminals. One tool that many data-driven organizations have started using is Microsoft Azure.

Data-driven 139

Data-driven Cost-Benefit Big Data Data Processing 139

Rocket-Powered Data Science

JULY 21, 2023

” Model-Assisted Threat Hunts , also known as Splunk M-ATH , is Splunk’s brand name for machine learning-assisted threat hunting and mitigation. search for deviations from normal behaviors through EDA: Exploratory Data Analysis), and (3) M-ATH (i.e., automation of the first two type of hunts, using AI and machine learning).

Machine Learning 190

Machine Learning Metrics Reporting Internet of Things 190

CIO Business Intelligence

MAY 29, 2024

Document processing, querying data, and making recommendations are just a few business cases where AI can streamline operations, enhance decision-making, and drive competitive advantage. This article will unpack what technical foundations are needed to get started using AI and how trained AI is a competitive differentiator.

Sales 102

Sales Machine Learning Modeling Data Collection 102

Cloudera

OCTOBER 11, 2022

A recent VentureBeat article , “4 AI trends: It’s all about scale in 2022 (so far),” highlighted the importance of scalability. The article goes on to share insights from experts at Gartner, PwC, John Deere, and Cloudera that shine a light on the critical role that data plays in scaling AI. . Data science needs analytics.

Data Science 94

Data Science Snapshot Data Warehouse Metadata 94

Smart Data Collective

MARCH 19, 2020

In this article, we will take a close look at 3 industries using AI in 2020, while trying to dive deep into the methods and reasons behind why these areas are so ahead of the pack in terms of tech. They pointed out that the industry is never going to be the same as AI is disrupting the business model.

Big Data 128

Big Data Marketing Data-driven Risk 128

Smart Data Collective

APRIL 10, 2020

At Smart Data Collective, we have discussed many of the ways that AI and machine learning have changed the face of performance marketing. Mostafa Elbermawy, an author with Single Grain, wrote a very interesting article on the importance of AI in branding. However, brand marketing is also evolving with new technological advances.

Machine Learning 107

Machine Learning Testing Marketing Strategy 107

CIO Business Intelligence

JANUARY 3, 2024

According to Martin Rapos, CEO of AR/VR platform Akular, which converts 3D models into digital twins, the impact of every dollar spent early is an order of magnitude higher than if you spend it five years down the road as a follower. The most effective way to get results quickly is to work with a platform that enables multiple use cases.

Cost-Benefit 136

Cost-Benefit ROI Manufacturing Optimization 136

Cloudera

AUGUST 17, 2020

One of the primary sources of that knowledge comes from our Knowledge Articles. These Knowledge Articles have proven to be invaluable to our Support Staff over the years. To that end, we have been working on improving the way our customers discover the collection of knowledge available in our Knowledge Articles.

Testing 88

Testing Machine Learning Interactive Metrics 88

Cloudera

AUGUST 12, 2021

The report classified employees’ reasons for leaving into six broad categories such as growth opportunity and job security, demonstrating the importance of using performance data, data collected from voluntary departures and historical data to reduce attrition for strong performers and enhance employees’ well-being.

Data-driven 111

Data-driven Manufacturing Insurance Risk Management 111

datapine

APRIL 21, 2022

For instance, when it comes to Human Resources, a digital transformation entails streamlining operations and digitizing personnel data. An accounting department may consider leveraging electronic contracts, data collecting, and reporting as a part of the digital transition. Approach To Digital Marketing.

Digital Transformation 206

Digital Transformation Marketing Advertising Scorecard 206

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. Plus, it uses LLMs like GPT-4 to generate natural language insights from data using AI techniques like natural language processing and generation.

Digital Transformation 119

Digital Transformation Dashboards Data Science Reporting 119

Smart Data Collective

APRIL 23, 2022

In simple terms, big data is a term used to describe large volumes of data that are difficult to manage. This data may overwhelm businesses every day in structured or unstructured forms. Smart organizations use this data to improve their business models and make life better through analysis.

Analytics Technologies 128

Analytics Technologies Broadcasting Data Analytics Technology 128

CIO Business Intelligence

MARCH 19, 2025

However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive. Developers, data architects and data engineers can initiate change at the grassroots level from integrating sustainability metrics into data models to ensuring ESG data integrity and fostering collaboration with sustainability teams.

IT 59

IT Data Governance Data-driven Metrics 59

datapine

JANUARY 31, 2022

Experts say that BI and data analytics makes the decision-making process 5x times faster for businesses. Renowned author Bernard Marr wrote an insightful article about Shell’s journey to become a fully data-driven company. Let’s look at our first use case.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

datapine

MAY 2, 2023

The future is bright for logistics companies that are willing to take advantage of big data. In this article, we’re going to examine examples and benefits of big data in logistics industry to fuel your imagination and get you thinking outside of the box.

Big Data 275

Big Data Internet of Things Cost-Benefit Optimization 275

Smart Data Collective

FEBRUARY 28, 2023

Here at Smart Data Collective, we have blogged extensively about the changes brought on by AI technology. You can find a discussion on the benefits of machine learning for risk parity at the end of this article. However, finetuning these models is a big part of the process. What is risk parity?

Machine Learning 117

Machine Learning Risk Cost-Benefit Marketing 117

Smart Data Collective

MAY 17, 2021

For example, when you’re reading a physical newspaper or a magazine, it’s impossible for the media company that owns the newspaper or magazine to monitor which pages you spent the most time reading and what type of articles you prefer. We, the consumers, don’t gain much from this massive data collection and profiling.

Cost-Benefit 104

Cost-Benefit Advertising Data Collection Data-driven 104