Uber AI

FEBRUARY 23, 2023

Data quality is of paramount importance at Uber, powering critical decisions and features. In this blog learn how we automated column-level drift detection in batch datasets at Uber scale, reducing the median time to detect issues in critical datasets by 5X.

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Data Drift Automation Data Quality AI 90

IBM Journey to AI blog

FEBRUARY 28, 2024

Here are four smart technologies modernizing strategic sourcing processes today: Automation Business process automation (also considered a type of business process outsourcing ) is pervasive across industries, minimizing manual tasks in accounting, human resources, IT and more. Blockchain Information is an invaluable business asset.

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Automation Big Data Artificial Intelligence Artificial Intelligence 299

AWS Machine Learning Blog

JULY 11, 2024

This allows customers to further pre-train selected models using their own proprietary data to tailor model responses to their business context. The quality of the custom model depends on multiple factors including the training data quality and hyperparameters used to customize the model. AWS Step Functions User Guide.

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Automation Large Language Models Data Quality Machine Learning 125

IBM Journey to AI blog

OCTOBER 21, 2024

million annually due to poor data quality. This is where data intelligence solutions prove their worth, by helping to ensure that data is not only abundant but also precise, accessible and governed by quality standards. However, diving into analytics without clear direction can lead to confusion and inefficiency.

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Data Quality Big Data Data Scientist Artificial Intelligence 233

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

Unite.AI

AUGUST 28, 2024

This blog will explore the five challenges in implementing AI in healthcare, their solutions, and their benefits. Challenges of Using AI in Healthcare Physicians, doctors, nurses, and other healthcare providers face many challenges integrating AI into their workflows, from displacement of human labor to data quality issues.

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IBM Journey to AI blog

MAY 9, 2024

At the same time, implementing a data governance framework poses some challenges, such as data quality issues, data silos security and privacy concerns. Data quality issues Positive business decisions and outcomes rely on trustworthy, high-quality data.

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ETL Data Quality Automation Metadata 229

Unite.AI

SEPTEMBER 16, 2024

Data integration tools can simplify this process, allowing businesses to streamline workflows and gain more actionable insights faster. This blog will explore the benefits of data integration tools, the different types available, and the best tools to consider in 2024. Fivetran also provides robust data security and governance.

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Unite.AI

SEPTEMBER 16, 2024

Data integration tools can simplify this process, allowing businesses to streamline workflows and gain more actionable insights faster. This blog will explore the benefits of data integration tools, the different types available, and the best tools to consider in 2024. Fivetran also provides robust data security and governance.

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Data Integration ETL Big Data Automation 173

IBM Journey to AI blog

JANUARY 15, 2024

This partnership establishes a benchmark for digital transformation in the insurance industry, promoting innovation and achieving cost efficiency through AI-powered business automation. The office sought a practical solution for process optimization and automation to address the aforementioned issues.

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Automation Robotics Artificial Intelligence Artificial Intelligence 229

DataRobot Blog

MAY 10, 2022

In this post, we will dive deeper into the first component of managing model risk, and look at opportunities at how automation provided by DataRobot brings about efficiencies in the development and implementation of models. . Developing Robust Machine Learning Models within a MRM Framework. To reference SR 11-7: .

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Automation Machine Learning Data Quality Algorithm 64

IBM Journey to AI blog

MAY 9, 2023

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. But we’ve faced a paradoxical challenge: automation is labor intensive. ” These large models have lowered the cost and labor involved in automation.

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Data Platform AI AI Automation 348

Chatbots Life

MAY 19, 2023

Automation rules today’s world. A chatbot is a technological genie that uses intelligent automation, ML, and NLP to automate tasks. It adds a digital flavor by automating your day-to-day IT tasks to help businesses work smarter. Modern service desks offer an automated ticketing system for staff.

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Chatbots Automation Auto-complete NLP 95

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

IBM Journey to AI blog

APRIL 20, 2023

Before a bank can start the process of certifying a risk model, they first need to understand what data is being used and how it changes as it moves from a database to a model. With an accurate view of the entire system, banks can more easily track down issues like missing or inconsistent data.

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ETL Data Discovery Automation Metadata 243

IBM Journey to AI blog

JULY 25, 2023

In reviewing IBM’s capabilities in ESG Reporting and Data Management, the Verdantix report notes that IBM has strengths in: Data quality control and enhancement, including “easy-to-understand reports to better analyze data quality.

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ESG Data Quality Machine Learning Automation 189

IBM Journey to AI blog

JANUARY 8, 2024

Event triggers are used to automate workflows or decisions, allowing businesses to generate notifications so appropriate actions can be taken as swiftly as situations are detected. Flexible and customizable Kafka configurations can be automated by using a simple user interface. Ready to take the next step?

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Automation Data Quality Explainability 277

IBM Journey to AI blog

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

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IBM Journey to AI blog

OCTOBER 14, 2024

Internally, we’ve implemented a marketing-automation use case where IBM’s brand guidelines and examples were ingested to generate new marketing content and curate it for consistent quality and tone. Similarly, the proliferation of agents will infuse data into an exploding volume and variety of automated workflows.

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IBM Journey to AI blog

AUGUST 12, 2024

The integration of generative AI, particularly LLMs, offers transformative potential to automate compliance processes, detect anomalies, and provide comprehensive insights into regulatory requirements. RAG implementations involve combining LLMs with external data sources to enhance their knowledge and decision-making capabilities.

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Automation Generative AI AI AI 162

IBM Journey to AI blog

JUNE 20, 2024

It provides seamless workflows that automate risk assessments and model approval processes, simplifying regulatory compliance. It automates compliance checks and maintains audit trails, enhancing regulatory adherence. Data security and privacy Ensuring the security and privacy of data used in AI models is crucial.

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IBM Journey to AI blog

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture.

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IBM Journey to AI blog

JULY 3, 2024

Align your data strategy to a go-forward architecture, with considerations for existing technology investments, governance and autonomous management built in. Look to AI to help automate tasks such as data onboarding, data classification, organization and tagging.

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Metadata Data Quality AI AI 113

IBM Journey to AI blog

JANUARY 25, 2024

Generative AI has the potential to deliver powerful support in key data areas: Master data cleansing to reduce duplications and flag outliers. Master data enrichment to enhance categorization and materials attributes. Master data quality to improve scoring, prioritization and automated validation of data.

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Algorithm Categorization Artificial Intelligence Artificial Intelligence 278

IBM Journey to AI blog

SEPTEMBER 15, 2023

Key challenges in meeting Sustainability disclosure requirements For most companies today, meeting this wide range of requirements will force accelerating the maturity level of ESG data quality, data management, and governance controls, as well as streamlining the ESG reporting processes to ensure auditability.

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IBM Journey to AI blog

NOVEMBER 24, 2023

Many enterprises are realizing that moving to cloud is not giving them the desired value nor agility/speed beyond basic platform-level automation. Generative AI-based Solution Approach : The Mule API to Java Spring boot modernization was significantly automated via a Generative AI-based accelerator we built.

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IBM Journey to AI blog

APRIL 25, 2024

.” Shantha Farris, Global Digital Commerce Strategy and Offering Leader at IBM iX The vast amounts of data businesses collect, combined with external data sources, can be used to present cross-selling and upselling opportunities that genuinely appeal to customers.

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IBM Journey to AI blog

SEPTEMBER 23, 2024

Gutowska elaborates on the role of AI agents in enhancing productivity: “AI agents can automate complex tasks that would otherwise require human resources, leading to greater productivity and efficiency. Hay predicts that the success of these AI initiatives will depend on data quality and accessibility. ” he noted.

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Explainability AI AI Data Quality 100

ODSC - Open Data Science

NOVEMBER 20, 2024

The Role of Creativity and Critical Thinking in Generative AI Generative AI, a powerful tool for automating and augmenting tasks, still requires a nuanced, human touch to deliver effective results. Yves Mulkers stressed the need for clean, reliable data as a foundation for AI success.

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IBM Journey to AI blog

DECEMBER 7, 2023

Automated data preparation and cleansing : AI-powered data preparation tools will automate data cleaning, transformation and normalization, reducing the time and effort required for manual data preparation and improving data quality.

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Data Analysis AI AI Automation 218

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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DataRobot Blog

MAY 26, 2022

In addition, by providing a host of model performance metrics and lift charts, the validator can be rest assured that the model is able to handle a wide range of data inputs appropriately and satisfy the business requirements for which it was created. The Framework for ML Governance. Download now.

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Automation Machine Learning ML Explainability 52

Pickl AI

OCTOBER 11, 2023

Data Observability and Data Quality are two key aspects of data management. The focus of this blog is going to be on Data Observability tools and their key framework. The growing landscape of technology has motivated organizations to adopt newer ways to harness the power of data.

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Data Quality Metadata Automation Data Science 52

Pickl AI

AUGUST 30, 2024

Introduction It is a critical process in the digital landscape, enabling organisations to transfer data between systems, formats, or storage solutions. As businesses evolve, the need for efficient data management becomes paramount. Explore More: Cloud Migration: Strategy and Tools What is Data Migration?

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Data Quality Data Integration Automation Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Summary: This comprehensive guide explores data standardization, covering its key concepts, benefits, challenges, best practices, real-world applications, and future trends. By understanding the importance of consistent data formats, organizations can improve data quality, enable collaborative research, and make more informed decisions.

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Data Quality Machine Learning Automation Artificial Intelligence 52

John Snow Labs

SEPTEMBER 4, 2023

In this blog post, we will be testing the robustness of the NERPipeline model, which is good in the f1 score, and evaluating its performance. With a high-quality dataset, you can build a great model. This technique helps to produce high-quality and accurate results for machine learning, predictive modeling, and decision-making.

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NLP Automation Natural Language Processing Large Language Models 52

AWS Machine Learning Blog

FEBRUARY 27, 2024

Automation of building new projects based on the template is streamlined through AWS Service Catalog , where a portfolio is created, serving as an abstraction for multiple products. Monitoring – Continuous surveillance completes checks for drifts related to data quality, model quality, and feature attribution.

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Machine Learning DevOps Data Scientist Data Quality 133