Paul Turley

OCTOBER 10, 2020

Moving important business data into a data model for analytic reporting can often be a two-edge sword. But, data in the model may be one or two layers away from the original source data, making it more challenging to compare with familiar user reports. not exactly scientific. not exactly scientific.

Modeling 145

Modeling Dashboards Testing Visualization 145

Dataiku

MARCH 25, 2024

This scenario is not science fiction but a glimpse into the capabilities of Multimodal Large Language Models (M-LLMs), where the convergence of various modalities extends the landscape of AI. Moreover, M-LLMs adeptly answer questions about visual content, aiding in tasks like image recognition and scene understanding.

Visualization 132

Visualization Modeling Experimentation Testing 132

Paul Turley

OCTOBER 18, 2020

Moving important business data into a data model for analytic reporting can often be a two-edge sword. But, data in the model may be one or two layers away from the original source data, making it more challenging to compare with familiar user reports. not exactly scientific. not exactly scientific.

Modeling 143

Modeling Dashboards Testing Visualization 143

erwin

JANUARY 9, 2020

For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. So here’s why data modeling is so critical to data governance.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

DataRobot Blog

MAY 26, 2022

Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. In summary, to ensure that they have built a robust model, modelers must make certain that they have designed the model in a way that is backed by research and industry-adopted practices.

Risk 52

Risk Modeling Metrics Business Objectives 52

DataKitchen

JUNE 19, 2023

Our customers start looking at the data in dashboards and models and then find many issues. Using automated data validation tests, you can ensure that the data stored within your systems is accurate, complete, consistent, and relevant to the problem at hand. The image above shows an example ‘’data at rest’ test result.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

AWS Big Data

MARCH 27, 2023

In this post, we demonstrate how Amazon Athena , Amazon QuickSight , and Confluent work together to enable visualization of data streams in near-real time. Data visualization for Confluent data A frequent use case for enterprises is data visualization. In this post, we use QuickSight.

Visualization 72

Visualization Data Lake Interactive Data-driven 72

CIO Business Intelligence

OCTOBER 13, 2023

The data architect is responsible for visualizing and designing an organization’s enterprise data management framework. Application data architect: The application data architect designs and implements data models for specific software applications. In some ways, the data architect is an advanced data engineer.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

Decision Management Solutions

DECEMBER 17, 2021

In the recent McKinsey article discussing designing next-generation credit-decisioning models they outlined four best practices for automated credit-decisioning models for banks as they continue their digital transformations. Digital lending based on high-performance credit-decisioning models, says McKinsey, lead to: Increased revenue.

Modeling 52

Modeling Experimentation Visualization Risk 52

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. Organization: AWS Price: US$300 How to prepare: Amazon offers free exam guides, sample questions, practice tests, and digital training.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

DataKitchen

NOVEMBER 18, 2022

As he thinks through the various journeys that data take in his company, Jason sees that his dashboard idea would require extracting or testing for events along the way. Logs and storage for problem diagnosis and visualization of historical trends. Data and tool tests. Testing at Every Step. (Part 1) (Part 2).

Testing 130

Testing Statistics Measurement Metrics 130

CIO Business Intelligence

OCTOBER 26, 2023

Through use of data analytics, data visualization, and data modeling techniques and technologies, BI analysts can identify trends that can help other departments, managers, and executives make business decisions to modernize and improve processes in the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

CIO Business Intelligence

JANUARY 19, 2024

The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect. Candidates for the exam are tested on ML, AI solutions, NLP, computer vision, and predictive analytics.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

erwin

JULY 11, 2019

At a fundamental level, digital transformation is about further synthesizing an organization’s operations and technology, so involving business architecture and process modeling is a best practice organizations cannot ignore. Business Process Modeling: The First Step to Giving Customers What They Expect. Data usage.

Digital Transformation 106

Digital Transformation Modeling Data Governance Visualization 106

O'Reilly on Data

MARCH 26, 2024

TL;DR LLMs and other GenAI models can reproduce significant chunks of training data. Researchers are finding more and more ways to extract training data from ChatGPT and other models. And the space is moving quickly: SORA , OpenAI’s text-to-video model, is yet to be released and has already taken the world by storm.

Modeling 275

Modeling Machine Learning Risk Advertising 275

CIO Business Intelligence

APRIL 12, 2024

It can be useful for an array of AI-related tasks, including deep learning research, computer vision, natural language processing (NLP), model development, and model deployment. Torch enables fast and efficient GPU support, focusing on improving flexibility and speed when building complex algorithms.

Deep Learning 124

Deep Learning IT Machine Learning IoT 124

O'Reilly on Data

JULY 11, 2023

He’s asking whether large language models eliminate programming as we know it, and he’s excited that the answer is “yes”: eventually, if not in the immediate future. Testing and debugging—well, if you’ve played with ChatGPT much, you know that testing and debugging won’t disappear. But what does this mean in practice?

Testing 248

Testing Software Visualization Interactive 248

Ontotext

NOVEMBER 25, 2021

If you are already processing data to create a RDF model, you probably won’t need this. Imagine a scenario where you have a successful solution integrating data from many different drone models and offering analytics based on it. GraphDB Enterprise comes with a battle-tested cluster mode. Data virtualization with ONTOP.

Visualization 98

Visualization Interactive Data-driven Enterprise 98

CIO Business Intelligence

JULY 5, 2022

Research firm Gartner defines business analytics as “solutions used to build analysis models and simulations to create scenarios, understand realities, and predict future states.”. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 135

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 135

IBM Big Data Hub

NOVEMBER 24, 2023

Subsequent phases are build and test and deploy to production. Generative AI also helps generate target design for specific cloud service provider framework through tuning the models based on a set of standardized patterns (ingress/egress, application services, data services, composite patterns, etc.).

Cost-Benefit 98

Cost-Benefit Testing Data-driven Enterprise 98

CIO Business Intelligence

MARCH 18, 2024

Developers of risky generative AI models are now free to release them without government approval, but are being encouraged to self-regulate by adding labels to the output of their models warning of their potential unreliability. Akshara Bassi, senior analyst at Counterpoint, weighed in on the implications for AI model developers.

Metadata 82

Metadata Visualization Modeling Risk 82

CIO Business Intelligence

JUNE 7, 2022

To ensure robust analysis, data analytics teams leverage a range of data management techniques, including data mining, data cleansing, data transformation, data modeling, and more. What are the four types of data analytics? In business, predictive analytics uses machine learning, business rules, and algorithms.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

datapine

JANUARY 6, 2022

Through the art of streamlined visual communication, data dashboards permit businesses to engage in real-time and informed decision-making and are key instruments in data interpretation. More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. agree, strongly agree, disagree, etc.).

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

Domino Data Lab

MARCH 3, 2021

It’s often stated that nothing changes inside an enterprise because you’ve built a model. In some cases, data science does generate models directly to revenue, such as a contextual deal engine that targets people with offers that they can instantly redeem. But what about good decisions?

Metrics 93

Metrics Modeling Sales Data Science 93

DataKitchen

JANUARY 3, 2022

Business analysts sometimes perform data science, but usually, they integrate and visualize data and create reports and dashboards from data supplied by other groups. Business analytic teams have ongoing deliverables – a dashboard, a PowerPoint, or a model that they refresh and renew. Business Analytic Challenges.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

IBM Big Data Hub

SEPTEMBER 19, 2023

Generative AI for coding is possible because of recent breakthroughs in large language model (LLM) technologies and natural language processing (NLP). Some generative AI for code tools automatically create unit tests to help with this. Generative AI can quickly and efficiently test and debug computer code.

Software 87

Software IT Visualization Deep Learning 87

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. According to Gartner, the goal is to design, model, align, execute, monitor, and tune decision models and processes. Model-driven DSS. They emphasize access to and manipulation of a model.

Data mining 141

Data mining Data-driven Statistics OLAP 141

Domino Data Lab

NOVEMBER 14, 2019

Model interpretability continues to spark public discourse among industry. We have covered model interpretability previously, including a proposed definition of machine learning (ML) interpretability. Yet there are tradeoffs to consider when selecting a model. Errors like these may occur when the model is being constructed.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

CIO Business Intelligence

FEBRUARY 20, 2024

Others are weighing the advantages of subscription-based business models where industrial equipment, automation, and processes are delivered as a service. Siemens is integrating its Teamcenter software for product lifecycle management with Microsoft Teams and Copilot AI-powered problem reporting and visual quality inspection.

Manufacturing 96

Manufacturing Sales Risk Management Forecasting 96

CIO Business Intelligence

SEPTEMBER 29, 2023

These skills include expertise in areas such as text preprocessing, tokenization, topic modeling, stop word removal, text classification, keyword extraction, speech tagging, sentiment analysis, text generation, emotion analysis, language modeling, and much more.

Deep Learning 143

Deep Learning Machine Learning Modeling Consulting 143

datapine

MAY 2, 2023

Using the right dashboard and data visualizations, it’s possible to hone in on any trends or patterns that uncover inefficiencies within your processes. Your Chance: Want to test a professional logistics analytics software? Your Chance: Want to test a professional logistics analytics software?

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

Cloudera

JUNE 26, 2023

For data engineering and data science teams, CDSW is highly effective as a comprehensive platform that trains, develops, and deploys machine learning models. It can provide a complete solution for data exploration, data analysis, data visualization, viz applications, and model deployment at scale.

Testing 76

Testing Data Processing Visualization Data Science 76

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 83

Data Science Data Analytics Prescriptive Analytics Analytics 83

The Unofficial Google Data Science Blog

JANUARY 16, 2018

We present data from Google Cloud Platform (GCP) as an example of how we use A/B testing when users are connected. Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. Figure 4 is a visual representation of these steps.

Testing 58

Testing Experimentation Measurement Modeling 58

AWS Big Data

JULY 26, 2023

The following are common asks from our customers: Is it possible to develop and test AWS Glue data integration jobs on my local laptop? The software development lifecycle on AWS defines the following six phases: Plan, Design, Implement, Test, Deploy, and Maintain. Test In the testing phase, you check the implementation for bugs.

Data Integration 69

Data Integration Snapshot Testing Visualization 69

erwin

JULY 30, 2020

ArchiMate is an enterprise architecture (EA) modeling language from The Open Group and used to communicate an organization’s enterprise architecture. Pronounced “ AR-ki-mayt” , the modeling language’s name comes from a compounding of “ archi tecture” and “ani mate.” The idea being that this makes the standard easier to learn and apply.

Enterprise 138

Enterprise Visualization Modeling Testing 138

Cloudera

JUNE 3, 2022

Data scientists and machine learning engineers in enterprise organizations need to fully understand their data in order to properly analyze it, build models, and power machine learning use cases across their business. Data scientists are likely to use a variety of different tools to move through their processes.

Dashboards 90

Dashboards Visualization Machine Learning Data Science 90