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. What does “quality” data mean, exactly?

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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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Pickl AI

OCTOBER 10, 2023

In this blog, we are going to unfold the two key aspects of data management that is Data Observability and Data Quality. Data is the lifeblood of the digital age. Today, every organization tries to explore the significant aspects of data and its applications. What is Data Observability and its Significance?

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IBM Journey to AI blog

AUGUST 23, 2023

Because of this, when we look to manage and govern the deployment of AI models, we must first focus on governing the data that the AI models are trained on. This data governance requires us to understand the origin, sensitivity, and lifecycle of all the data that we use. LLMs are a bit different.

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Precisely

MAY 4, 2023

quintillion exabytes of data every day. 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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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

AUGUST 15, 2022

So, what can you do to ensure your data is up to par and […]. The post Data Trustability: The Bridge Between Data Quality and Data Observability appeared first on DATAVERSITY. You might not even make it out of the starting gate.

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IBM Data Science in Practice

NOVEMBER 28, 2022

These matters make it difficult to capture and manage citizen information accurately. The AVI solution offers government agencies rich capabilities to create and monitor data quality and supports the capture, verification and maintenance of customer location data, while helping government gains maximum value from their information assets.

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Precisely

JULY 12, 2024

Data integrity is based on four main pillars: Data integration : Regardless of its original source, on legacy systems, relational databases, or cloud data warehouses, data must be seamlessly integrated in order to gain visibility into all your data in a timely fashion.

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IBM Journey to AI blog

APRIL 10, 2023

To further the above, organizations should have the right foundation that consists of a modern data governance approach and data architecture. Everyone would be using the same data set to make informed decisions which may range from goal setting to prioritizing investments in sustainability.

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IBM Journey to AI blog

FEBRUARY 26, 2024

The financial services industry has been in the process of modernizing its data governance for more than a decade. But as we inch closer to global economic downturn, the need for top-notch governance has become increasingly urgent. Data lineage helps during these investigations. How will one decision affect customers?

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Precisely

MAY 8, 2023

Once you’ve connected key business goals and initiatives, it’s time to establish policies and procedures, including defining data ownership, establishing access controls, and managing data retention and deletion. Learn more Now, let’s talk about monitoring your data. How does it work for real-world use cases?

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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

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

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. Leverage AI to enhance governance. Take a proactive approach.

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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.

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Dataversity

DECEMBER 14, 2021

Watching closely the evolution of metadata platforms (later rechristened as Data Governance platforms due to their focus), as somebody who has implemented and built Data Governance solutions on top of these platforms, I see a significant evolution in their architecture as well as the use cases they support.

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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. Leverage AI to enhance governance. Take a proactive approach.

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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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IBM Journey to AI blog

JULY 13, 2023

This is the practice of creating, updating and consistently enforcing the processes, rules and standards that prevent errors, data loss, data corruption, mishandling of sensitive or regulated data, and data breaches. Completeness: Does the data comprise all relevant and available information?

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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 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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DagsHub

AUGUST 23, 2024

As a result, Gartner estimates that poor data quality costs organizations an average of $13 million annually. High-quality data significantly reduces the risk of costly errors, and the resulting penalties or legal issues. Data Governance Data governance is the foundation of any data quality framework.

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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

MAY 31, 2023

Business and IT teams need a simple, seamless data integrity solution that enables them to: Collaborate on making data accessible Ensure and maintain its quality Enrich the data with third-party context Real-time Access to Data In the past, businesses struggled to get timely access to data for both analytical and operational use cases.

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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. grant everyone self-service access to data.

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Precisely

JULY 18, 2024

While data fabric is not a standalone solution, critical capabilities that you can address today to prepare for a data fabric include automated data integration, metadata management, centralized data governance, and self-service access by consumers.

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Precisely

SEPTEMBER 11, 2023

By 2025, 50% of data and analytics leaders will be using augmented MDM and active metadata to enhance their capabilities – demonstrating that beyond data quality, automation is also in demand for data governance, data catalog, and security solutions. User interface assistants: Find the information you need, faster.

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Precisely

MARCH 2, 2023

To achieve true data integrity, organizations must attend to data integration, data governance, data quality, and context with data enrichment. Presumably, all of that information can come from your organization’s internal data. Competitive disadvantage.

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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).

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Dataversity

JUNE 26, 2023

Today, businesses and individuals expect instant access to information and swift delivery of services. The same expectation applies to data, […] The post Leveraging Data Pipelines to Meet the Needs of the Business: Why the Speed of Data Matters appeared first on DATAVERSITY.

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Pickl AI

JULY 24, 2024

Missing Data Incomplete datasets with missing values can distort the training process and lead to inaccurate models. Missing data can occur due to various reasons, such as data entry errors, loss of information, or non-responses in surveys. Bias in data can result in unfair and discriminatory outcomes.

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Precisely

MAY 3, 2023

On May 17, we have three great keynote sessions in store – all around the topic of Building a Data-Driven Culture to Drive Better Customer Experiences and Higher Business Value. Not to worry – all session recordings will be available to you after the event. Here’s our agenda for May 17: 10:30–11:15 a.m.

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ODSC - Open Data Science

DECEMBER 3, 2024

Understanding data mesh Data mesh is a decentralized architecture type that allows different departments to access data independently. It’s different from traditional data architecture, which usually has dedicated data engineering teams that provide access to information after other departments request it.

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Alation

FEBRUARY 8, 2022

Making the experts responsible for service streamlines the data-request pipeline, delivering higher quality data into the hands of those who need it more rapidly. Some argue that data governance and quality practices may vary between domains. Are there reviews or useful details that inform your decision?

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Precisely

JUNE 5, 2023

With the Data Enrichment service of the Suite, you can add rich, valuable context for analysis by attaching attributes from hundreds of our curated, up-to-date datasets. And when you search for enriched values using the PreciselyID, you can find the most relevant information – and make better, smarter decisions – faster.

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