Smart Data Collective

JULY 15, 2021

It helps you locate and discover data that fit your search criteria. With data catalogs, you won’t have to waste time looking for information you think you have. Advanced data catalogs can update metadata based on the data’s origins. How Does a Data Catalog Impact Employees?

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The MLOps Blog

JUNE 27, 2023

User support arrangements Consider the availability and quality of support from the provider or vendor, including documentation, tutorials, forums, customer service, etc. Check out the Kubeflow documentation. Metaflow Metaflow helps data scientists and machine learning engineers build, manage, and deploy data science projects.

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Precisely

MARCH 7, 2024

Yet experts warn that without proactive attention to data quality and data governance, AI projects could face considerable roadblocks. Data Quality and Data Governance Insurance carriers cannot effectively leverage artificial intelligence without first having a clear data strategy in place.

AI 72

AI AI Data Governance Data Quality 72

phData

AUGUST 10, 2023

The implementation of a data vault architecture requires the integration of multiple technologies to effectively support the design principles and meet the organization’s requirements. Implement business rules and validations: Data Vault models often involve enforcing business rules and performing data quality checks.

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Precisely

SEPTEMBER 11, 2023

It provides a unique ability to automate or accelerate user tasks, resulting in benefits like: improved efficiency greater productivity reduced dependence on manual labor Let’s look at AI-enabled data quality solutions as an example. Problem: “We’re unsure about the quality of our existing data and how to improve it!”

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Precisely

OCTOBER 12, 2023

Documenting what data is most important , then understanding what policies apply, where that data is, and how it fits into the overall compliance picture for financial services. Doing so requires comprehensive data quality and data governance programs that help you clearly understand who you’re dealing with.

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Data Quality Data Governance ML ML 64

IBM Journey to AI blog

JULY 3, 2024

As data types and applications evolve, you might need specialized NoSQL databases to handle diverse data structures and specific application requirements. The consequences of using poor-quality data are far-reaching, including erosion of customer trust, regulatory noncompliance and financial and reputational damage.

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Precisely

APRIL 11, 2023

Let’s break it down: Step 1: Find the data and request access You can search previously cataloged datasets with key terms like “mailing address” to bring up a list of matching data using the data catalog. Easily search, explore, understand, and collaborate across your critical data assets.

Data Observability 52

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Pickl AI

JUNE 7, 2024

Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Introduction In today’s business landscape, data integration is vital. It is part of IBM’s Infosphere Information Server ecosystem.

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Precisely

OCTOBER 5, 2023

When we think about the big picture of data integrity – that’s data with maximum accuracy, consistency, and context – it becomes abundantly clear why data enrichment is one of its six key pillars (along with data integration, data observability, data quality, data governance, and location intelligence).

Data Quality 69

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phData

FEBRUARY 22, 2023

Data Quality Good testing is an essential part of ensuring the integrity and reliability of data. Without testing, it is difficult to know whether the data is accurate, complete, and free of errors. Below, we will walk through some baseline tests every team could and should run to ensure data quality.

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The MLOps Blog

AUGUST 3, 2023

You have the function docstring because with procedural code generally in script form, there is no place to stick documentation naturally. With Hamilton] you’re not overwhelmed, you have the docstring, a function for documentation, but then also everything’s unit testable by default – they didn’t have a good testing story.

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APRIL 15, 2025

And yet, many data leaders struggle to trust their AI-driven insights due to poor data observability. In fact, only 59% of organizations trust their AI/ML model inputs and outputs , according to the latest BARC Data Observability Survey: Observability for AI Innovation.

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FEBRUARY 28, 2025

Thats why you need trusted data and to trust your data, it must have data integrity. What exactly is data integrity? Many proposed definitions focus on data quality or its technical aspects, but you need to approach data integrity from a broader perspective. What is Data Integrity?

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Pickl AI

MARCH 19, 2025

It is widely used for storing and managing structured data, making it an essential tool for data engineers. MongoDB MongoDB is a NoSQL database that stores data in flexible, JSON-like documents. Apache Spark Apache Spark is a powerful data processing framework that efficiently handles Big Data.

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