AI News

SEPTEMBER 27, 2024

What we are seeing in the Data world in general is continued investment in data and analytics software. Analysts estimate that the spend on Data and Analytics software last year was in the $100 billion plus range. Second, is data quality and accessibility, the quality of the data is critical.

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AI Strategy Automation Data Quality Big Data 308

AI News

SEPTEMBER 24, 2024

The success of this AI-powered underwater vehicle at Seagreen wind farm not only demonstrates the potential of autonomous technology in offshore wind inspections but also sets a new standard for safety, efficiency, and data quality in the industry. Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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Robotics Big Data AI AI 339

ODSC - Open Data Science

JUNE 19, 2023

With the advent of big data in the modern world, RTOS is becoming increasingly important. As software expert Tim Mangan explains, a purpose-built real-time OS is more suitable for apps that involve tons of data processing. The Big Data and RTOS connection IoT and embedded devices are among the biggest sources of big data.

Big Data 96

Big Data ETL Data Science Artificial Intelligence 96

IBM Journey to AI blog

FEBRUARY 28, 2024

Sourcing teams are automating processes like data analysis as well as supplier relationship management and transaction management. This helps reduce errors to improve data quality and response times to questions, which improves customer and supplier satisfaction.

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Automation Big Data Data Quality Data Analysis 291

IBM Journey to AI blog

OCTOBER 21, 2024

These platforms function as sophisticated ecosystems, facilitating the collection, analysis, interpretation and actionable implementation of insights from diverse data sources. Companies are investing heavily in big data and artificial intelligence (AI) to unlock these benefits.

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Data Quality Data Scientist Big Data Artificial Intelligence 218

Marktechpost

NOVEMBER 5, 2023

In this study, researchers from the Allen Institute for AI, the University of Washington and the University of California propose to use a collection of tools called WIMBD: WHAT’S IN MY BIG DATA, which helps practitioners rapidly examine massive language datasets to research the content of large text corpora. Data quality (e.g.,

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Big Data Machine Learning Data Quality AI Research 132

Unite.AI

DECEMBER 23, 2023

Breakthroughs in technologies like Artificial Intelligence (AI) are changing how we think about operations management. As organizations move from a reactive approach to a proactive one, they can use technologies like the Industrial Internet of Things ( IIoT ), cloud, AI, and analytics to gain real-time data, actionable insight, etc.,

Data Quality 182

Data Quality Big Data Artificial Intelligence Artificial Intelligence 182

Unite.AI

SEPTEMBER 22, 2023

Jay Mishra is the Chief Operating Officer (COO) at Astera Software , a rapidly-growing provider of enterprise-ready data solutions. That has been one of the key trends and one most recent ones is the addition of artificial intelligence to use AI, specifically generative AI to make automation even better.

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Large Language Models Automation Artificial Intelligence Artificial Intelligence 278

Unite.AI

DECEMBER 5, 2023

In this digital economy, data is paramount. Today, all sectors, from private enterprises to public entities, use big data to make critical business decisions. However, the data ecosystem faces numerous challenges regarding large data volume, variety, and velocity. Enter data warehousing!

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Metadata Big Data ETL Data Mining 162

Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

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Pickl AI

JANUARY 12, 2025

Introduction Are you struggling to decide between data-driven practices and AI-driven strategies for your business? Besides, there is a balance between the precision of traditional data analysis and the innovative potential of explainable artificial intelligence. These changes assure faster deliveries and lower costs.

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IBM Journey to AI blog

SEPTEMBER 5, 2024

Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success. Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality.

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Metadata Data Quality Auto-classification DevOps 188

Pickl AI

DECEMBER 2, 2024

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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Big Data Data Quality Data Analysis NLP 52

ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out her talk, “ Power trusted AI/ML Outcomes with Data Integrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.

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IBM Journey to AI blog

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way.

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Pickl AI

FEBRUARY 17, 2025

Introduction: The Reality of Machine Learning Consider a healthcare organisation that implemented a Machine Learning model to predict patient outcomes based on historical data. However, once deployed in a real-world setting, its performance plummeted due to data quality issues and unforeseen biases.

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Machine Learning Algorithm Explainability Data Quality 52

Marktechpost

JUNE 5, 2024

In addition, organizations that rely on data must prioritize data quality review. Data profiling is a crucial tool. For evaluating data quality. Data profiling gives your company the tools to spot patterns, anticipate consumer actions, and create a solid data governance plan.

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AWS Machine Learning Blog

DECEMBER 4, 2024

This framework creates a central hub for feature management and governance with enterprise feature store capabilities, making it straightforward to observe the data lineage for each feature pipeline, monitor data quality , and reuse features across multiple models and teams.

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Marktechpost

APRIL 1, 2024

Existing research emphasizes the significance of distributed processing and data quality control for enhancing LLMs. Utilizing frameworks like Slurm and Spark enables efficient big data management, while data quality improvements through deduplication, decontamination, and sentence length adjustments refine training datasets.

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Large Language Models ETL Data Ingestion Data Quality 110

ODSC - Open Data Science

NOVEMBER 29, 2024

Artificial Intelligence (AI) stands at the forefront of transforming data governance strategies, offering innovative solutions that enhance data integrity and security. With AI, data quality checks happen in real time. He enjoys writing about SaaS, AI, machine learning, analytics, and Big Data.

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Data Integration Automation Machine Learning AI 40

AWS Machine Learning Blog

FEBRUARY 18, 2025

The following sections further explain the main components of the solution: ETL pipelines to transform the log data, agentic RAG implementation, and the chat application. Creating ETL pipelines to transform log data Preparing your data to provide quality results is the first step in an AI project.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Rajesh Nedunuri is a Senior Data Engineer within the Amazon Worldwide Returns and ReCommerce Data Services team. He specializes in designing, building, and optimizing large-scale data solutions.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

It includes processes for monitoring model performance, managing risks, ensuring data quality, and maintaining transparency and accountability throughout the model’s lifecycle. By establishing robust oversight, organizations can build trust, meet regulatory requirements, and help ensure ethical use of AI technologies.

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ODSC - Open Data Science

SEPTEMBER 27, 2023

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. Unlike traditional data warehouses or relational databases, data lakes accept data from a variety of sources, without the need for prior data transformation or schema definition.

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AWS Machine Learning Blog

JUNE 3, 2024

In a single visual interface, you can complete each step of a data preparation workflow: data selection, cleansing, exploration, visualization, and processing. Custom Spark commands can also expand the over 300 built-in data transformations. Other analyses are also available to help you visualize and understand your data.

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Pickl AI

OCTOBER 9, 2023

Understanding Machine Learning Algorithms Machine Learning , a subset of Artificial Intelligence , has become increasingly relevant in retail demand forecasting due to its ability to analyze and interpret vast amounts of data to make accurate predictions. Retailers must ensure data is clean, consistent, and free from anomalies.

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Machine Learning Algorithm ML Data Quality 98

AWS Machine Learning Blog

AUGUST 21, 2024

A new data flow is created on the Data Wrangler console. Choose Get data insights to identify potential data quality issues and get recommendations. In the Create analysis pane, provide the following information: For Analysis type , choose Data Quality And Insights Report. For Target column , enter y.

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Machine Learning Data Scientist ML Data Quality 111

Pickl AI

OCTOBER 10, 2024

Summary: Data transformation tools streamline data processing by automating the conversion of raw data into usable formats. These tools enhance efficiency, improve data quality, and support Advanced Analytics like Machine Learning. The right tool can significantly enhance efficiency, scalability, and data quality.

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ETL Data Quality Machine Learning Business Intelligence 52

Flipboard

MARCH 22, 2023

We also detail the steps that data scientists can take to configure the data flow, analyze the data quality, and add data transformations. Finally, we show how to export the data flow and train a model using SageMaker Autopilot. Data Wrangler creates the report from the sampled data.

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IDP Data Scientist Categorization Data Quality 123

ODSC - Open Data Science

FEBRUARY 28, 2023

Going from Data to Insights LexisNexis At HPCC Systems® from LexisNexis® Risk Solutions you’ll find “a consistent data-centric programming language, two processing platforms, and a single, complete end-to-end architecture for efficient processing.” These tools are designed to help companies derive insights from big data.

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ODSC - Open Data Science

OCTOBER 18, 2024

The advent of big data, affordable computing power, and advanced machine learning algorithms has fueled explosive growth in data science across industries. However, research shows that up to 85% of data science projects fail to move beyond proofs of concept to full-scale deployment.

Data Science 52

Data Science ETL Data Scientist Data Quality 52

TransOrg Analytics

AUGUST 7, 2024

Challenges in Credit Risk Modeling Despite its importance, credit risk modelling faces several challenges: Data Quality and Availability: Accurate credit risk modelling relies on high-quality, comprehensive data. Only complete or updated data can lead to reliable predictions and informed decision-making.

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Neural Network Big Data Deep Learning Machine Learning 52

TransOrg Analytics

AUGUST 9, 2024

Cons: Complexity: Managing and securing a data lake involves intricate tasks that require careful planning and execution. Data Quality: Without proper governance, data quality can become an issue. Performance: Query performance can be slower compared to optimized data stores.

Machine Learning 52

Machine Learning ETL Big Data Data Quality 52

AWS Machine Learning Blog

AUGUST 29, 2023

The batch inference pipeline includes steps for checking data quality against a baseline created by the training pipeline, as well as model quality (model performance) if ground truth labels are available. If the batch inference pipeline discovers data quality issues, it will notify the responsible data scientist via Amazon SNS.

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Data Scientist Data Quality Python ML 84

Heartbeat

OCTOBER 23, 2023

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

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Pickl AI

OCTOBER 15, 2024

Artificial Intelligence (AI) and Machine Learning Artificial Intelligence (AI) and Machine Learning are at the forefront of enhancing analytical capabilities. These technologies enable organisations to analyse vast amounts of data quickly and accurately.

Machine Learning 52

Machine Learning Big Data Artificial Intelligence Artificial Intelligence 52

Pickl AI

OCTOBER 7, 2024

Summary: Artificial Intelligence is revolutionising operations management in the water industry by addressing challenges such as aging infrastructure, water scarcity, and regulatory compliance. Introduction Artificial Intelligence (AI) is transforming various sectors, and the water industry is no exception.

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