AI News

SEPTEMBER 17, 2024

The survey uncovers a troubling lack of trust in data quality—a cornerstone of successful AI implementation. Only 38% of respondents consider themselves ‘very trusting’ of the data quality and training used in AI systems. Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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Data Quality Big Data AI AI 273

Flipboard

JUNE 5, 2023

True data quality simplification requires transformation of both code and data, because the two are inextricably linked. Code sprawl and data siloing both imply bad habits that should be the exception, rather than the norm.

Data Quality 121

Data Quality Big Data Data Science Machine Learning 121

Flipboard

MARCH 13, 2023

Presented by BMC Poor data quality costs organizations an average $12.9 Organizations are beginning to recognize that not only does it have a direct impact on revenue over the long term, but poor data quality also increases the complexity of data ecosystems, and directly impacts the … million a year.

Data Quality 123

Data Quality Big Data Machine Learning 123

AI News

MAY 3, 2024

Ahead of AI & Big Data Expo North America – where the company will showcase its expertise – Chuck Ros , Industry Success Director at SoftServe, provided valuable insights into the company’s AI initiatives, the challenges faced, and its future strategy for leveraging this powerful technology. .”

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Big Data Generative AI Explainability AI 268

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 133

Pickl AI

OCTOBER 10, 2023

In this blog, we are going to unfold the two key aspects of data management that is Data Observability and Data Quality. Data is the lifeblood of the digital age. Today, every organization tries to explore the significant aspects of data and its applications.

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Data Quality Machine Learning Data Science Data Integration 52

AI News

DECEMBER 13, 2023

Phi-2’s achievements are underpinned by two key aspects: Training data quality: Microsoft emphasises the critical role of training data quality in model performance. Phi-2 leverages “textbook-quality” data, focusing on synthetic datasets designed to impart common sense reasoning and general knowledge.

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Big Data Data Quality AI AI 284

Flipboard

JUNE 15, 2023

Data Engineers: We look into Data Engineering, which combines three core practices around Data Management, Software Engineering, and I&O. This focuses …

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Data Quality Software Engineer Big Data Machine Learning 147

AI News

OCTOBER 17, 2024

Data integrity and security emerged as the biggest deterrents to implementing new AI solutions. Executives also reported encountering various AI performance issues, including: Data quality issues (e.g., Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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Big Data AI AI Data Quality 244

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.

Robotics 286

Robotics Big Data AI AI 286

AI News

SEPTEMBER 27, 2024

First is clear alignment of the data strategy with the business goals, making sure the technology teams are working on what matters the most to the business. Second, is data quality and accessibility, the quality of the data is critical. Poor data quality will lead to inaccurate insights.

AI Strategy 239

AI Strategy Automation Data Quality Big Data 239

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. million annually due to poor data quality.

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Data Quality Big Data Data Scientist Artificial Intelligence 233

AI News

NOVEMBER 21, 2023

Addressing this gap will require a multi-faceted approach including grappling with issues related to data quality and ensuring that AI systems are built on reliable, unbiased, and representative datasets. Companies have struggled with data quality and data hygiene.

Big Data 262

Big Data Data Quality Generative AI Explainability 262

Unite.AI

SEPTEMBER 16, 2024

It offers both open-source and enterprise/paid versions and facilitates big data management. Key Features: Seamless integration with cloud and on-premise environments, extensive data quality, and governance tools. Pros: Scalable, strong data governance features, support for big data.

Data Integration 173

Data Integration ETL Big Data Automation 173

Unite.AI

SEPTEMBER 16, 2024

It offers both open-source and enterprise/paid versions and facilitates big data management. Key Features: Seamless integration with cloud and on-premise environments, extensive data quality, and governance tools. Pros: Scalable, strong data governance features, support for big data.

Data Integration 173

Data Integration ETL Big Data Automation 173

Unite.AI

DECEMBER 23, 2023

Some of the APM strategies employed for this include: Predictive Maintenance: By using modern AI/ML capabilities to analyze big data , this strategy can monitor an asset’s health and forecast maintenance. Root Cause Analysis (RCA): This strategy emphasizes understanding the root causes of asset failures in a structured manner.

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Data Quality Big Data Artificial Intelligence Artificial Intelligence 182

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.

ETL 52

ETL Data Quality Business Intelligence Big Data 52

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.

Automation 299

Automation Big Data Artificial Intelligence Artificial Intelligence 299

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!

Metadata 162

Metadata Big Data ETL Data Mining 162

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 189

IBM Journey to AI blog

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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Metadata Data Quality Data Discovery Data Scientist 130

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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Data Quality Metadata Data Integration ETL 113

Pickl AI

NOVEMBER 4, 2024

Introduction Data Engineering is the backbone of the data-driven world, transforming raw data into actionable insights. As organisations increasingly rely on data to drive decision-making, understanding the fundamentals of Data Engineering becomes essential. ETL is vital for ensuring data quality and integrity.

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Data Quality ETL Data Integration Machine Learning 52

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.

Large Language Models 106

Large Language Models ETL Data Ingestion Data Quality 106

Pickl AI

JULY 29, 2024

It utilises the Hadoop Distributed File System (HDFS) and MapReduce for efficient data management, enabling organisations to perform big data analytics and gain valuable insights from their data. In a Hadoop cluster, data stored in the Hadoop Distributed File System (HDFS), which spreads the data across the nodes.

Big Data 52

Big Data Metadata Data Quality Machine Learning 52

ODSC - Open Data Science

APRIL 28, 2023

But before AI/ML can contribute to enterprise-level transformation, organizations must first address the problems with the integrity of the data driving AI/ML outcomes. The truth is, companies need trusted data, not just big data. That’s why any discussion about AI/ML is also a discussion about data integrity.

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Data Integration ML ESG Big Data 98

Pickl AI

JUNE 18, 2023

Hadoop has become a highly familiar term because of the advent of big data in the digital world and establishing its position successfully. The technological development through Big Data has been able to change the approach of data analysis vehemently. It offers several advantages for handling big data effectively.

Big Data 52

Big Data Machine Learning Data Analysis Data Quality 52

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

Pickl AI

OCTOBER 6, 2024

This phase is crucial for enhancing data quality and preparing it for analysis. Transformation involves various activities that help convert raw data into a format suitable for reporting and analytics. Normalisation: Standardising data formats and structures, ensuring consistency across various data sources.

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ETL Data Quality Data Integration Big Data 52

AWS Machine Learning Blog

NOVEMBER 29, 2023

To quickly explore the loan data, choose Get data insights and select the loan_status target column and Classification problem type. The generated Data Quality and Insight report provides key statistics, visualizations, and feature importance analyses. Now you have a balanced target column. Huong Nguyen is a Sr.

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ML Data Quality Automation Machine Learning 126

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 Analysis 52

Bugra Akyildiz

JUNE 29, 2024

This week, I will cover why I think data janitor work is dying and companies that are built in on top of data janitor work could be ripe for disruption through LLMs and what to do about it. A data janitor is a person who works to take big data and condense it into useful amounts of information. No, not really.

LLM 40

LLM Big Data Data Quality ETL 40

Pickl AI

JUNE 4, 2024

Big Data Analytics This involves analyzing massive datasets that are too large and complex for traditional data analysis methods. Big Data Analytics is used in healthcare to improve operational efficiency, identify fraud, and conduct large-scale population health studies.

Data Science 52

Data Science Data Scientist Big Data Machine Learning 52

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.

Big Data 98

Big Data Metadata ETL Business Intelligence 98

Pickl AI

AUGUST 1, 2023

Data Processing: Performing computations, aggregations, and other data operations to generate valuable insights from the data. Data Integration: Combining data from multiple sources to create a unified view for analysis and decision-making.

Big Data 52

Big Data Data Analysis Data Scientist Data Ingestion 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

Pickl AI

OCTOBER 11, 2024

This process is essential in today’s data-driven environment, where vast amounts of data are generated daily. Here are the key reasons why data transformation is important: Enhancing Data Quality Data transformation improves the quality of data by addressing issues such as missing values, duplicates, and inconsistent formats.

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Data Quality Data Integration Business Intelligence Artificial Intelligence 52