Dataversity

SEPTEMBER 27, 2021

Natural Language Processing (NLP) has been on the rise for several years, and for good reason. Click to learn more about author Ben Lorica. With the ability to identify new variants of COVID-19, improve customer service, and significantly refine search capabilities, use cases are expanding as the technology proliferates.

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Alation

APRIL 25, 2023

It’d be difficult to exaggerate the importance of data in today’s global marketplace, especially for firms which are going through digital transformation (DT). Using bad data, or the incorrect data can generate devastating results. What tools and processes will this plan require and who will establish them?

Data Governance 40

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Data Science Dojo

MARCH 8, 2024

Invasion of Privacy The data-centric nature of AI also presents significant privacy risks. Vast amounts of personal data are required to train systems in fields like facial recognition, natural language processing, and personalized recommendations.

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ODSC - Open Data Science

JANUARY 9, 2024

Data Engineering for Large Language Models LLMs are artificial intelligence models that are trained on massive datasets of text and code. They are used for a variety of tasks, such as natural language processing, machine translation, and summarization.

Data Engineer 97

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Dataconomy

SEPTEMBER 4, 2023

Text analytics: Text analytics, also known as text mining, deals with unstructured text data, such as customer reviews, social media comments, or documents. It uses natural language processing (NLP) techniques to extract valuable insights from textual data.

Analytics 203

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Smart Data Collective

NOVEMBER 24, 2020

Business intelligence software will be more geared towards working with Big Data. Data Governance. One issue that many people don’t understand is data governance. It is evident that challenges of data handling will be present in the future too. Natural Language Processing (NLP).

Business Intelligence 134

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Data Science Dojo

OCTOBER 10, 2023

Role of AI for leading professionals Here are some specific examples of how attending AI events and conferences can help individuals and organizations to learn and adapt to new technologies: A software engineer can gain knowledge about the latest advancements in natural language processing by attending an AI conference.

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Data Science Dojo

JANUARY 13, 2023

The conference features a wide range of topics within AI, including machine learning, natural language processing, computer vision, and robotics, as well as interdisciplinary areas such as AI and law, AI and education, and AI and the arts. It also includes tutorials, workshops, and invited talks by leading experts in the field.

Data Science 284

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IBM Journey to AI blog

AUGUST 15, 2023

A common phrase you’ll hear around AI is that artificial intelligence is only as good as the data foundation that shapes it. Therefore, a well-built AI for business program must also have a good data governance framework. Doing so allows your organization the ability to scale with trust and transparency.

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Precisely

MARCH 7, 2024

Insurance industry leaders are just beginning to understand the value that generative AI can bring to the claims management process. By harnessing the power of machine learning and natural language processing, sophisticated systems can analyze and prioritize claims with unprecedented efficiency and timeliness.

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AWS Machine Learning Blog

FEBRUARY 25, 2025

Using an Amazon Q Business custom data source connector , you can gain insights into your organizations third party applications with the integration of generative AI and natural language processing.

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AWS Machine Learning Blog

MARCH 4, 2024

However, when employing the use of traditional natural language processing (NLP) models, they found that these solutions struggled to fully understand the nuanced feedback found in open-ended survey responses. The following diagram illustrates the solution architecture and flow.

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Pickl AI

OCTOBER 18, 2023

Data Enrichment Services Enrichment tools augment existing data with additional information, such as demographics, geolocation, or social media profiles. This enhances the depth and usefulness of the data. It defines roles, responsibilities, and processes for data management.

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IBM Journey to AI blog

AUGUST 12, 2024

It helps companies streamline and automate the end-to-end ML lifecycle, which includes data collection, model creation (built on data sources from the software development lifecycle), model deployment, model orchestration, health monitoring and data governance processes.

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Alation

AUGUST 26, 2021

It asks much larger questions, which flesh out an organization’s relationship with data: Why do we have data? Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more.

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Pickl AI

OCTOBER 3, 2024

The process typically involves several key steps: Model Selection: Users choose from a library of pre-trained models tailored for specific applications such as Natural Language Processing (NLP), image recognition, or predictive analytics. Predictive Analytics : Models that forecast future events based on historical data.

Machine Learning 52

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AWS Machine Learning Blog

JANUARY 13, 2023

This iterative process of model training continues until the global model converges. Iterative process of model training. In recent years, this new learning paradigm has been successfully adopted to address the concern of data governance in training ML models.

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Precisely

JANUARY 22, 2024

In CX, generative AI applications can include language translation and localization, consumer research and behavioral analysis to deepen understanding, and helping customer service reps research answers to complex queries. It also enables organizations to track and be transparent about how they use customer data and ensure data privacy.

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Alation

OCTOBER 14, 2021

As pioneers in the Natural Language Processing (NLP) space, Lyngo has leveled the data playing field with tools that allow anyone to learn from data. Their product empowers users to take a truly data-driven approach for business-critical decisions. Watch the Alation Data Governance App video.

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IBM Journey to AI blog

DECEMBER 16, 2022

And because data assets within the catalog have quality scores and social recommendations, Alex has greater trust and confidence in the data she’s using for her decision-making recommendations. This is especially helpful when handling massive amounts of big data. Protected and compliant data.

Data Quality 52

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Pickl AI

DECEMBER 2, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Analytics tools help convert raw data into actionable insights for businesses. Strong data governance ensures accuracy, security, and compliance in data management. What is Big Data?

Big Data 52

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Pickl AI

NOVEMBER 25, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Analytics tools help convert raw data into actionable insights for businesses. Strong data governance ensures accuracy, security, and compliance in data management. What is Big Data?

Big Data 52

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Dataconomy

MAY 17, 2023

These intelligent virtual assistants can understand customer inquiries, provide instant responses, and even handle complex interactions through natural language processing ( NLP ) capabilities.

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DagsHub

FEBRUARY 29, 2024

Data preparation involves multiple processes, such as setting up the overall data ecosystem, including a data lake and feature store, data acquisition and procurement as required, data annotation, data cleaning, data feature processing and data governance.

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Heartbeat

MAY 29, 2023

LLMs are one of the most exciting advancements in natural language processing (NLP). We will explore how to better understand the data that these models are trained on, and how to evaluate and optimize them for real-world use.

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IBM Journey to AI blog

DECEMBER 20, 2023

Steps for building a successful AI strategy The following steps are commonly used to help craft an effective artificial intelligence strategy: Explore the technology Gain an understanding of various AI technologies, including generative AI , machine learning (ML), natural language processing, computer vision, etc.

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phData

MAY 28, 2024

Cortex offers a collection of ready-to-use models for common use cases, with capabilities broken into two categories: Cortex LLM functions provide Generative AI capabilities for natural language processing, including completion (prompting) , translation, summarization, sentiment analysis , and vector embeddings.

Machine Learning 52

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Pickl AI

SEPTEMBER 17, 2024

Summary : AI is transforming the cybersecurity landscape by enabling advanced threat detection, automating security processes, and adapting to new threats. It leverages Machine Learning, natural language processing, and predictive analytics to identify malicious activities, streamline incident response, and optimise security measures.

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Pickl AI

JUNE 18, 2024

Power BI can analyse transaction data to identify suspicious activities and ensure compliance with these regulations. Data governance and compliance are critical aspects of Data Analysis. Frequently Asked Questions What Are Some Benefits of Using Advanced Data Visualization in Power BI Projects?

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Heartbeat

OCTOBER 23, 2023

Natural Language Processing (NLP) and Text Mining: Healthcare data includes vast amounts of unstructured information in clinical notes, research articles, and patient narratives. Data scientists and machine learning engineers employ NLP techniques and text-mining algorithms to process and analyze this textual data.

Machine Learning 52

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Alation

FEBRUARY 20, 2020

After investing in self-service analytic tooling, organizations are now turning their attention to linking infrastructure and tooling to data-driven decisions. But as the category gains greater recognition, more companies are building data catalog solutions. Here’s why your organization should catch the Wave.

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Pickl AI

DECEMBER 4, 2023

Exploring technologies like Data visualization tools and predictive modeling becomes our compass in this intricate landscape. Data governance and security Like a fortress protecting its treasures, data governance, and security form the stronghold of practical Data Intelligence.

Data Analysis 52

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IBM Journey to AI blog

OCTOBER 20, 2023

These development platforms support collaboration between data science and engineering teams, which decreases costs by reducing redundant efforts and automating routine tasks, such as data duplication or extraction. What types of features do AI platforms offer?

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Pickl AI

DECEMBER 10, 2024

Businesses handling cross-border analytics must adopt adaptable governance structures to simultaneously ensure compliance with multiple jurisdictions. Trends in Global Data Governance Frameworks Unified data governance frameworks are becoming crucial for organisations managing complex multi-cloud environments.

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Women in Big Data

DECEMBER 9, 2024

Its drag-and-drop functionality simplifies the process of creating reports and dashboards. Its natural language processing (NLP) feature allows users to generate insights through conversational queries. Its costs are associated with its enterprise-focused features and advanced data modeling capabilities.

Big Data 52

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Pickl AI

APRIL 2, 2024

How Do I Prepare My Business for Data Science? Assess Your Data Landscape: Evaluate the data you currently collect, its quality, and accessibility. Develop a Data Governance Strategy: Establish clear guidelines for data ownership, access, and security to ensure responsible data use.

Data Science 52

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The Data Administration Newsletter

AUGUST 7, 2024

My column today is a follow-up to my article “The Challenge of Data Consistency,” published in the May 2023 issue of this newsletter. In that article, I discussed how semantic encoding (also called concept encoding) is the go-to solution for consistently representing master data entities such as customers and products.

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