Cloudera

DECEMBER 6, 2024

LLM precision is good, not great, right now Paul: I wanted to chat about this notion of precision data with you. And specifically, I was reading one of your blog posts recently that talked about the dark ages of data. Walk us through where we are with precision data today and how this relates to the dark ages of data.

Manufacturing 82

Manufacturing Forecasting Metadata Data Processing 82

IBM Big Data Hub

SEPTEMBER 7, 2023

Today we are announcing our latest addition: a new family of IBM-built foundation models which will be available in watsonx.ai , our studio for generative AI, foundation models and machine learning. Collectively named “Granite,” these multi-size foundation models apply generative AI to both language and code.

Modeling 101

Modeling Risk Unstructured Data Enterprise 101

IBM Big Data Hub

SEPTEMBER 12, 2023

The UK government’s Ecosystem of Trust is a potential future border model for frictionless trade, which the UK government committed to pilot testing from October 2022 to March 2023. The models also reduce private sector customs data collection costs by 40%.

Testing 83

Testing Modeling Cost-Benefit Consulting 83

Cloudera

APRIL 9, 2021

This is part 4 in this blog series. This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The second blog dealt with creating and managing Data Enrichment pipelines.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 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

Cloudera

FEBRUARY 8, 2021

This is part 2 in this blog series. You can read part 1, here: Digital Transformation is a Data Journey From Edge to Insight. The first blog introduced a mock connected vehicle manufacturing company, The Electric Car Company (ECC), to illustrate the manufacturing data path through the data lifecycle.

Manufacturing 118

Manufacturing Data Warehouse Sales Predictive Analytics 118

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

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

IBM Big Data Hub

DECEMBER 16, 2022

Over the last week, millions of people around the world have interacted with OpenAI’s ChatGPT, which represents a significant advance for generative artificial intelligence (AI) and the foundation models that underpin many of these use cases. How can we ensure that these models are being used responsibly?

Uncertainty 112

Uncertainty Metadata Modeling Data Collection 112

Cloudera

AUGUST 12, 2021

In my previous blog post, I shared examples of how data provides the foundation for a modern organization to understand and exceed customers’ expectations. Exploring new possibilities to develop intelligent connected devices and services is made easier by creating digital twins,accurate models to predict behaviour. Conclusion.

Data-driven 111

Data-driven Manufacturing Insurance Risk Management 111

datapine

SEPTEMBER 1, 2020

This simple yet effective visualization will allow you to understand not only how users see your product but also whether they prefer previous models or competitor versions. Combining all of it with the quantitative data collected will allow you for more successful product development. b) Purchase Intention.

Reporting 247

Reporting Marketing KPI Dashboards 247

datapine

JANUARY 6, 2022

Qualitative data, as it is widely open to interpretation, must be “coded” so as to facilitate the grouping and labeling of data into identifiable themes. There are few certainties when it comes to data analysis, but you can be sure that if the research you are engaging in has no numbers involved, it is not quantitative research.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

Domino Data Lab

MAY 15, 2019

Over the years, I have listened to data scientists and machine learning (ML) researchers relay various pain points and challenges that impede their work. This work includes model improvements as well as adding new signals and features into the model. Conclusion.

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111

Cloudera

FEBRUARY 8, 2021

The goal is to define, implement and offer a data lifecycle platform enabling and optimizing future connected and autonomous vehicle systems that would train connected vehicle AI/ML models faster with higher accuracy and delivering a lower cost.

Machine Learning 108

Machine Learning Manufacturing Unstructured Data Data Collection 108

Smart Data Collective

JUNE 10, 2019

People that know me are aware that I have a blog on sustainability, as well as Smart Data Collective. The truth is that big data offers a number of sustainable solutions, including: New data solutions make it easier for companies to move towards paperless business models. Attracting Prospective Investors.

Technology 111

Technology Data Analytics Big Data Analytics 111

datapine

MAY 2, 2023

Big data enables automated systems by intelligently routing many data sets and data streams. In a recent move towards a more autonomous logistical future, Amazon has launched an upgraded model of its highly-successful KIVA robots. Like many modern sectors, logistics processes involve large amounts of data collection.

Big Data 275

Big Data Internet of Things Cost-Benefit Optimization 275

erwin

JULY 17, 2019

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. Constructing A Digital Transformation Strategy: Data Enablement.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

datapine

JANUARY 31, 2022

To do so, the company started by defining the goals, and finding a way to translate employees’ behavior and experience into data, so as to model against actual outcomes. The gathered data includes everything from customers’ waiting times, peak demand hours, traffic for each city, a driver’s speed during a trip, and much more.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Cloudera

NOVEMBER 19, 2020

Some of these algorithms can be adaptive to quickly update the model to take into account new, previously unseen fraud tactics allowing for dynamic rule adjustment. This type of framework requires a streaming environment that provides continuous updates coupled with model performance monitoring to ensure consistent performance. .

Machine Learning 119

Machine Learning Data-driven Modeling Deep Learning 119

datapine

NOVEMBER 19, 2019

This feature hierarchy and the filters that model significance in the data, make it possible for the layers to learn from experience. Thus, deep nets can crunch unstructured data that was previously not available for unsupervised analysis.

Technology 279

Technology Internet of Things IT IoT 279

Cloudera

MAY 9, 2019

The report created a readiness model with five dimensions and various metrics under each dimension. The five dimensions of the readiness model are –. It addresses the key data management challenges with streaming and IoT data for all types of enterprises. Each metric is associated with one or more questions.

IoT 56

IoT Modeling Metrics Measurement 56

Cloudera

DECEMBER 8, 2020

Federated Learning is a paradigm in which machine learning models are trained on decentralized data. Instead of collecting data on a single server or data lake, it remains in place — on smartphones, industrial sensing equipment, and other edge devices — and models are trained on-device.

Machine Learning 85

Machine Learning Data Lake Reporting Data Collection 85

Smart Data Collective

FEBRUARY 28, 2023

Here at Smart Data Collective, we have blogged extensively about the changes brought on by AI technology. Over the past few months, many others have started talking about some of the changes that we blogged about for years. However, finetuning these models is a big part of the process.

Machine Learning 117

Machine Learning Risk Cost-Benefit Marketing 117

Alation

MARCH 24, 2021

There are clearly some hurdles companies face in deploying AI, with data quality being a major concern, as 87% of respondents report being at least somewhat concerned about data quality impacting the success of their AI implementations. Worries of Data Bias Creating Discriminatory AI Results. Subscribe to Alation's Blog.

Reporting 105

Reporting Data Quality Business Driver Enterprise 105

DataRobot Blog

MARCH 8, 2023

Every modern enterprise has a unique set of business data collected as part of their sales, operations, and management processes. Additionally, DataRobot data scientists and support teams have a proven record of success working with thousands of customers on tens of thousands of AI use cases across a wide range of industries.

Enterprise 105

Enterprise Experimentation Machine Learning Data Science 105

Smart Data Collective

MAY 1, 2022

Multiple emails, social media posts, blogs, articles, and other text forms are generated daily. Moreover, the data collected is not free from error or biases if humans handle it. Businesses are including more of it in their companies and adopting methods like AI text analysis. . What is text analysis?

Unstructured Data 132

Unstructured Data Cost-Benefit Machine Learning Marketing 132

Domino Data Lab

AUGUST 12, 2021

For data, this refinement includes doing some cleaning and manipulations that provide a better understanding of the information that we are dealing with. In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. Results become the basis for understanding the solution space (or, ‘the realm of the possible’) for a given modeling task. ref: [link].

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

Cloudera

MARCH 29, 2022

Hybrid cloud is the Model of Choice. They want the computing power, cost efficiencies, and other advantages of public cloud – while retaining the flexibility, control, and security of private cloud and on-premises data centers. . What makes (or breaks) a hybrid data cloud?

Cost-Benefit 97

Cost-Benefit Strategy Data Science Data Processing 97

Smart Data Collective

JUNE 28, 2021

E-commerce companies use data stored on their data centers in highly effective ways, such as improving their machine learning capabilities to assist customers. Kayla Mathews addressed this trend in a blog post last year : “Walmart is one of the major e-commerce brands contributing to the data center boom.

Management 96

Management Big Data Advertising Data Processing 96

Cloudera

OCTOBER 11, 2022

The takeaway – businesses need control over all their data in order to achieve AI at scale and digital business transformation. The challenge for AI is how to do data in all its complexity – volume, variety, velocity. Because that is how models learn. But it isn’t just aggregating data for models.

Data Science 94

Data Science Snapshot Data Warehouse Metadata 94

Smart Data Collective

AUGUST 31, 2020

At Smart Data Collective, we have talked extensively about the benefits of big data in digital marketing. We have focused a lot on using data analytics for SEO. However, there are a lot of other benefits of using big data in marketing. You shouldn’t limit yourself to using data analytics in your SEO strategy.

Data-driven 105

Data-driven Marketing Big Data Broadcasting 105

IBM Big Data Hub

MAY 17, 2023

They use drones for tasks as simple as aerial photography or as complex as sophisticated data collection and processing. It can offer data on demand to different business units within an organization, with the help of various sensors and payloads. The global commercial drone market is projected to grow from USD 8.15

Data Collection 76

Data Collection Visualization Data-driven Unstructured Data 76

BizAcuity

JANUARY 21, 2019

And that is what today’s blog is about – Customer Behaviour Analysis. Leveraging upon the data collected by casinos from their various data touch points, the casino operators can create an elaborate profile for each customer. For that to happen, it is important to put the right segregation models in place.

Recreation/Entertainment 75

Recreation/Entertainment Data Collection Modeling Customer Analytics 75

DataRobot Blog

APRIL 7, 2022

The Data Race. Rule changes have upended data collection for F1 teams, leaving them all in the same spot with minimal historical data and many questions to be answered. With such a wealth of data collected, how do you find the signal in the noise?

Strategy 105

Strategy Data Collection Consulting Modeling 105

datapine

JUNE 4, 2020

CTO reporting delivers a presentational focus on relevant data that CTOs need to collect to be able to generate actionable insights and improve the company’s technological bottom line. Focus on the goal and audience. Another critical point to consider is the end-goal.

Dashboards 130

Dashboards Reporting Metrics Visualization 130

IBM Big Data Hub

NOVEMBER 14, 2023

But few organizations have made the strategic shift to managing “data as a product.” ” This data management means applying product development practices to data. Each data product has its own lifecycle environment where its data and AI assets are managed in their product-specific data lakehouse.

Strategy 103

Strategy Data-driven Cost-Benefit Measurement 103