Dataversity

JUNE 29, 2022

You want to rely on data integrity to ensure you avoid simple mistakes because of poor sourcing or data that may not be correctly organized and verified. The post Data Observability and Its Impact on the Data Operations Lifecycle appeared first on DATAVERSITY. That requires the […].

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Dataversity

AUGUST 15, 2022

If data is the new oil, then high-quality data is the new black gold. Just like with oil, if you don’t have good data quality, you will not get very far. So, what can you do to ensure your data is up to par and […]. You might not even make it out of the starting gate.

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Alation

JANUARY 20, 2022

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me. Step 2: Data Definitions.

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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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IBM Journey to AI blog

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

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Precisely

SEPTEMBER 9, 2024

Key Takeaways: • Implement effective data quality management (DQM) to support the data accuracy, trustworthiness, and reliability you need for stronger analytics and decision-making. Embrace automation to streamline data quality processes like profiling and standardization. What is Data Quality Management (DQM)?

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Precisely

SEPTEMBER 18, 2023

Author’s note: this article about data observability and its role in building trusted data has been adapted from an article originally published in Enterprise Management 360. Is your data ready to use? That’s what makes this a critical element of a robust data integrity strategy. What is Data Observability?

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Precisely

DECEMBER 12, 2023

quintillion exabytes of data every da y. That information resides in multiple systems, including legacy on-premises systems, cloud applications, and hybrid environments. It includes streaming data from smart devices and IoT sensors, mobile trace data, and more. Data is the fuel that feeds digital transformation.

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Data Science Dojo

OCTOBER 10, 2023

Link to event -> Generative AI and Data Storytelling Here are some of the key takeaways from the article: Generative AI is a type of artificial intelligence that can create new content, such as text, images, and music. Data storytelling is the process of using data to communicate a story in a way that is engaging and informative.

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Pickl AI

JULY 24, 2024

Summary: Data quality is a fundamental aspect of Machine Learning. Poor-quality data leads to biased and unreliable models, while high-quality data enables accurate predictions and insights. What is Data Quality in Machine Learning? Bias in data can result in unfair and discriminatory outcomes.

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Alation

DECEMBER 7, 2021

Alation and Bigeye have partnered to bring data observability and data quality monitoring into the data catalog. Read to learn how our newly combined capabilities put more trustworthy, quality data into the hands of those who are best equipped to leverage it. Extract data quality information.

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Precisely

NOVEMBER 18, 2024

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. Plan for data quality and governance of AI models from day one.

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DagsHub

AUGUST 23, 2024

As such, the quality of their data can make or break the success of the company. This article will guide you through the concept of a data quality framework, its essential components, and how to implement it effectively within your organization. What is a data quality framework?

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Alation

DECEMBER 7, 2021

Alation and Soda are excited to announce a new partnership, which will bring powerful data-quality capabilities into the data catalog. Soda’s data observability platform empowers data teams to discover and collaboratively resolve data issues quickly. Do we have end-to-end data pipeline control?

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Dataversity

APRIL 25, 2022

If data processes are not at peak performance and efficiency, businesses are just collecting massive stores of data for no reason. Data without insight is useless, and the energy spent collecting it, is wasted. The post Solving Three Data Problems with Data Observability appeared first on DATAVERSITY.

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Dataversity

JANUARY 19, 2024

Do you know the costs of poor data quality? Below, I explore the significance of data observability, how it can mitigate the risks of bad data, and ways to measure its ROI. Data has become […] The post Putting a Number on Bad Data appeared first on DATAVERSITY.

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Precisely

NOVEMBER 18, 2024

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. Plan for data quality and governance of AI models from day one.

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Smart Data Collective

JULY 15, 2021

A data catalog serves the same purpose. It organizes the information your company has on hand so you can find it easily. By using metadata (or short descriptions), data catalogs help companies gather, organize, retrieve, and manage information. It helps you locate and discover data that fit your search criteria.

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IBM Data Science in Practice

NOVEMBER 28, 2022

IBM Multicloud Data Integration helps organizations connect data from disparate sources, build data pipelines, remediate data issues, enrich data, and deliver integrated data to multicloud platforms where it can easily accessed by data consumers or built into a data product.

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Precisely

AUGUST 29, 2024

Key Takeaways Data quality ensures your data is accurate, complete, reliable, and up to date – powering AI conclusions that reduce costs and increase revenue and compliance. Data observability continuously monitors data pipelines and alerts you to errors and anomalies.

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Precisely

NOVEMBER 13, 2024

Challenges around data literacy, readiness, and risk exposure need to be addressed – otherwise they can hinder MDM’s success Businesses that excel with MDM and data integrity can trust their data to inform high-velocity decisions, and remain compliant with emerging regulations. Today, you have more data than ever.

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Precisely

SEPTEMBER 19, 2024

Key Takeaways: Data integrity is essential for AI success and reliability – helping you prevent harmful biases and inaccuracies in AI models. Robust data governance for AI ensures data privacy, compliance, and ethical AI use. Proactive data quality measures are critical, especially in AI applications.

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Precisely

MAY 8, 2023

Reduce errors, save time, and cut costs with a proactive approach You need to make decisions based on accurate, consistent, and complete data to achieve the best results for your business goals. That’s where the Data Quality service of the Precisely Data Integrity Suite can help. How does it work for real-world use cases?

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IBM Journey to AI blog

APRIL 10, 2023

Everyone would be using the same data set to make informed decisions which may range from goal setting to prioritizing investments in sustainability. Data fabric can help model, integrate and query data sources, build data pipelines, integrate data in near real-time, and run AI-driven applications.

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ODSC - Open Data Science

FEBRUARY 28, 2023

Making Data Observable Bigeye The quality of the data powering your machine learning algorithms should not be a mystery. Bigeye’s data observability platform helps data science teams “measure, improve, and communicate data quality at any scale.”

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The MLOps Blog

JUNE 27, 2023

Can you debug system information? Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Can you compare images?

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Precisely

MARCH 7, 2024

They can ingest information as soon as it becomes available, summarize lengthy narrative content, and offer guidance to employees who manage the claims process. Yet experts warn that without proactive attention to data quality and data governance, AI projects could face considerable roadblocks.

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Precisely

SEPTEMBER 14, 2023

We’ve identified six core pillars of sustainable compliance: A centralized knowledge repository – collecting information, democratizing it, and gaining a single source of truth. Identifying relevant, in-scope data for the compliance area at hand. Where in the organization does that data live? What does “good” look like?

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IBM Journey to AI blog

DECEMBER 16, 2022

So, instead of wandering the aisles in hopes you’ll stumble across the book, you can walk straight to it and get the information you want much faster. 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.

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Precisely

JUNE 5, 2023

As more organizations prioritize data-driven decision-making, the pressure mounts for data teams to provide the highest quality data possible for the business. Reach new levels of data quality and deeper analysis – faster So then, what are the options for data practitioners?

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Precisely

OCTOBER 10, 2024

Key Takeaways: Data democratization is about empowering employees to access and understand the data that informs better business decisions. The rapid advancement of analytical capabilities, capacity, and usability can make more information available to be analyzed. Attention to data quality.

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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

FEBRUARY 9, 2024

Data Integrity for Compliance Remains in the Spotlight Data privacy and security concerns remain top of mind for organizations across industries. As consumer standards for protecting their personal identifiable information (PII) grow, so do the consequences for organizations that don’t live up to those expectations.

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Precisely

MAY 18, 2023

Customer Voices from Trust ’23: the Precisely Data Integrity Summit Jean-Paul Otte from Degroof Petercam shares why data governance is essential to linking data to business value – and why improving data quality is the first step of any governance journey. What can data integrity help your business accomplish?

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Precisely

MAY 31, 2023

When attempting to build a data strategy, the primary obstacle organizations face is a lack of resources. Teams are building complex, hybrid, multi-cloud environments, moving critical data workloads to the cloud, and addressing data quality challenges. In many cases, data arrived too late to be useful.

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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. Business data vault: Data vault objects with soft business rules applied. Information Mart: A layer of consumer-oriented models.

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Precisely

OCTOBER 12, 2023

Six Principles of Proactive Data Programs Over decades of working with customers in financial services, our team at Precisely has identified six key pillars of proactive data programs. Monitoring and improving business quality rules and technical quality rules to define what “good” looks like. Privacy requirements.

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