Precisely

JANUARY 17, 2023

Technology helped to bridge the gap, as AI, machine learning, and data analytics drove smarter decisions, and automation paved the way for greater efficiency. AI and machine learning initiatives play an increasingly important role. As they do so, access to traditional and modern data sources is required.

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AWS Machine Learning Blog

MARCH 15, 2024

Medical data restrictions You can use machine learning (ML) to assist doctors and researchers in diagnosis tasks, thereby speeding up the process. However, the datasets needed to build the ML models and give reliable results are sitting in silos across different healthcare systems and organizations.

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Alation

OCTOBER 5, 2021

Without a doubt, no company can achieve lasting profitability and sustainable growth with a poorly constructed data governance methodology. Today, all companies must pursue data analytics, Machine Learning & Artificial Intelligence (ML & AI) as an integral part of any standard business plan.

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Precisely

JUNE 26, 2023

They shore up privacy and security, embrace distributed workforce management, and innovate around artificial intelligence and machine learning-based automation. The key to success within all of these initiatives is high-integrity data. Only 46% of respondents rate their data quality as “high” or “very high.”

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Precisely

FEBRUARY 9, 2024

In 2024 organizations will increasingly turn to third-party data and spatial insights to augment their training and reference data for the most nuanced, coherent, and contextually relevant AI output. When it comes to AI outputs, results will only be as strong as the data that’s feeding them.

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Precisely

SEPTEMBER 26, 2024

Key Takeaways: Trusted AI requires data integrity. For AI-ready data, focus on comprehensive data integration, data quality and governance, and data enrichment. Building data literacy across your organization empowers teams to make better use of AI tools. The impact? The stakes are very high.

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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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Precisely

JUNE 2, 2023

Innovators in the industry understand that leading-edge technologies such as AI and machine learning will be a deciding factor in the quest for competitive advantage when moving to the cloud. To learn more, read our ebook. Insufficient skills, limited budgets, and poor data quality also present significant challenges.

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Women in Big Data

FEBRUARY 1, 2023

She started as a Web Analyst and Online Marketing Manager, and discovered her passion for data, Big Data, data science and machine learning. She goes on to explain the one of the most beneficial features of One Data’s enabling technology, One Data Cartography , is record linkage combined with data quality.

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Precisely

JANUARY 25, 2023

Financial institutions are using data in a myriad of different ways, from know-your-customer (KYC) compliance to marketing insights and channel optimization, from risk assessment and fraud detection to innovative AI and machine learning initiatives. This post examines the practical implications of poor data integrity.

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Precisely

MAY 16, 2024

You need to break down data silos and integrate critical data from all relevant sources into Amazon Web Services (AWS). Fuel your AI applications with trusted data to power reliable results. You’re not alone. This ensures your AI models can access a comprehensive dataset, minimizing bias and enhancing accuracy.

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Precisely

MARCH 4, 2024

While use cases may vary, each success story shares a common foundation: data integrity. Whether it’s making personalized recommendations, automating complex workflows, or training machine learning models, the accuracy, consistency, and context of your data determine the effectiveness of your AI solutions.

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Alation

MAY 31, 2023

How is the data architecture role evolving? As data governance gains importance, data architects must work with data stewards and owners to establish policies, develop governance frameworks, implement data quality programs, and provide guidance to other data professionals.

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Precisely

OCTOBER 12, 2023

Creating data observability routines to inform key users of any changes or exceptions that crop up within the data, enabling a more proactive approach to compliance. Doing so requires comprehensive data quality and data governance programs that help you clearly understand who you’re dealing with. Intelligence.

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Precisely

FEBRUARY 12, 2024

Here are some of the key trends and challenges facing telecommunications companies today: The growth of AI and machine learning: Telecom companies use artificial intelligence and machine learning (AI/ML) for predictive analytics and network troubleshooting.

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Pickl AI

DECEMBER 4, 2023

Imagine this: we collect loads of data, right? Data Intelligence takes that data, adds a touch of AI and Machine Learning magic, and turns it into insights. It’s not just about having data; it’s about turning that data into real wisdom for better products and services. These insights?

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Precisely

AUGUST 22, 2024

What is data fabric Data fabric is a data management architecture that allows you to break down data silos, improve efficiencies, and accelerate access for users. It provides a unified and consistent data infrastructure across distributed environments, accelerating analytics and decision-making.

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Alation

MARCH 21, 2023

While this industry has used data and analytics for a long time, many large travel organizations still struggle with data silos , which prevent them from gaining the most value from their data. What is big data in the travel and tourism industry?

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Alation

JULY 6, 2021

Modern data governance relies on automation, which reduces costs. Automated tools make data governance processes very cost-effective. Machine learning plays a key role, as it can increase the speed and accuracy of metadata capture and categorization. This empowers leaders to see and refine human processes around data.

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Precisely

FEBRUARY 2, 2023

This requires access to data from across business systems when they need it. Data silos and slow batch delivery of data will not do. Stale data and inconsistencies can distort the perception of what is really happening in the business leading to uncertainty and delay.

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Precisely

JULY 18, 2024

Ensures consistent, high-quality data is readily available to foster innovation and enable you to drive competitive advantage in your markets through advanced analytics and machine learning. You must be able to continuously catalog, profile, and identify the most frequently used data. Increase metadata maturity.

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The MLOps Blog

MAY 17, 2023

Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. We also discuss different types of ETL pipelines for ML use cases and provide real-world examples of their use to help data engineers choose the right one. fillna( iris_transform_df[cols].mean())

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ODSC - Open Data Science

JULY 13, 2023

Insights Gathering insight from consumer information is one of the top data challenges modern retailers face. Around 90% of all data is unstructured. While tools like machine learning technology can process it, visualizing it can still be complex. It’s generally more challenging to manage with traditional approaches.

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Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

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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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Alation

JANUARY 27, 2022

Data now comes from so many sources that integrating, cleaning, and transforming it across systems is difficult. Data quality problems cause low productivity, inefficiency, high costs, and errors in decision-making. Many organizations are turning to active data governance to minimize the burden of governance tasks.

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Alation

OCTOBER 12, 2021

In the past, businesses would collect data, run analytics, and extract insights, which would inform strategy and decision-making. Nowadays, machine learning , AI, and augmented reality analytics are speeding up this process, so that collection and analysis are always on. Evaluate and monitor data quality.

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Pickl AI

JULY 16, 2024

Summary: AIOps leverages AI and Machine Learning to automate IT tasks, identify anomalies, and predict problems. Learn how to implement AIOps in your organization! It utilizes Machine Learning (ML) and other AI techniques to streamline IT processes, improve efficiency, and free up valuable time for IT professionals.

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Heartbeat

DECEMBER 7, 2023

What is Data Mesh? Data Mesh is a new data set that enables units or cross-functional teams to decentralize and manage their data domains while collaborating to maintain data quality and consistency across the organization — architecture and governance approach. We can call fabric texture or actual fabric.

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phData

JUNE 20, 2024

Data as the foundation of what the business does is great – but how do you support that? What technology or platform can meet the needs of the business, from basic report creation to complex document analysis to machine learning workflows? The Snowflake AI Data Cloud is the platform that will support that and much more!

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Pickl AI

NOVEMBER 15, 2023

This centralization streamlines data access, facilitating more efficient analysis and reducing the challenges associated with siloed information. With all data in one place, businesses can break down data silos and gain holistic insights.

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phData

NOVEMBER 13, 2023

Enhanced Collaboration: dbt Mesh fosters a collaborative environment by using cross-project references, making it easy for teams to share, reference, and build upon each other’s work, eliminating the risk of data silos. The semantic models are defined in the model’s.yml configuration file.

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phData

SEPTEMBER 27, 2024

Looking to build a machine-learning model for churn prediction? The atomic data provides a perfect input, capturing the full richness of customer behavior over time. Data Quality Management : Persistent staging provides a clear demarcation between raw and processed customer data. Just plug it in!

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Flipboard

MARCH 21, 2025

Through this unified query capability, you can create comprehensive insights into customer transaction patterns and purchase behavior for active products without the traditional barriers of data silos or the need to copy data between systems. He loves spending time with his family and friends.

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Dataconomy

MARCH 18, 2025

Continuous intelligence is the real-time analysis and processing of data streams to enable automated decision-making and insights. It integrates artificial intelligence, machine learning, and analytics to provide dynamic responses, often used in fraud detection, IoT monitoring, and operational optimization.

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Pickl AI

DECEMBER 3, 2024

By leveraging GenAI, businesses can personalize customer experiences and improve data quality while maintaining privacy and compliance. Introduction Generative AI (GenAI) is transforming Data Analytics by enabling organisations to extract deeper insights and make more informed decisions.

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