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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Data Engineering Podcast

OCTOBER 5, 2020

Summary Analytical workloads require a well engineered and well maintained data integration process to ensure that your information is reliable and up to date. Building a real-time pipeline for your data lakes and data warehouses is a non-trivial effort, requiring a substantial investment of time and energy.

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Precisely

SEPTEMBER 18, 2024

This means it’s more important than ever to make data-driven decisions, cut costs, and improve efficiency. Get your copy of the full report for all the strategic insights you need to build a winning data strategy in 2025. What are the primary data challenges blocking the path to AI success? You’re not alone.

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Precisely

JANUARY 9, 2023

Requirements for data to be more easily accessible, at even faster rates, will continue to grow in 2023, and organizations will need to adapt their data quality practices to keep pace with the demand for new modern use cases. The post Top Data Integrity Trends Fueling Confident Business Decisions in 2023 appeared first on Precisely.

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Precisely

MAY 23, 2024

Key takeaways: Quickly adapt to market changes by easily adding new data sources and targets, ensuring your IT landscape evolves at the pace of your business. Gain a competitive edge with real-time data integration, crucial for time-sensitive decisions and actions in fraud detection and customer interactions.

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Precisely

DECEMBER 14, 2023

Data integrity empowers your businesses to make fast, confident decisions based on trusted data that has maximum accuracy, consistency, and context. As 2023 comes to an end we’re counting down the Top 5 Data Integrity blog posts of the year. #5. Read more > #2.

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phData: Data Engineering

NOVEMBER 1, 2024

In an effort to better understand where data governance is heading, we spoke with top executives from IT, healthcare, and finance to hear their thoughts on the biggest trends, key challenges, and what insights they would recommend. With that, let’s get into the governance trends for data leaders! No problem!

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Precisely

NOVEMBER 21, 2024

Key Takeaways: Harness automation and data integrity unlock the full potential of your data, powering sustainable digital transformation and growth. Data and processes are deeply interconnected. Today, automation and data integrity are increasingly at the core of successful digital transformation.

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Precisely

MAY 18, 2023

According to IDC , 50% of enterprises in the United States say that using data and intelligence strategically to create competitive differentiation is critical to running a successful digital business. Data governance has emerged as a key success factor for companies aiming to innovate, improve efficiency, and drive competitive advantage.

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Precisely

AUGUST 8, 2024

As your business applications grow, so do fragmented data silos that hold you back. How confident are you that your data management practices are up to the task of supporting your evolving objectives? MDM: The Answer to Data Chaos Imagine managing a sprawling organization where each department operates with its own datasets.

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Knowledge Hut

APRIL 20, 2023

Data governance refers to the set of policies, procedures, mix of people and standards that organisations put in place to manage their data assets. It involves establishing a framework for data management that ensures data quality, privacy, security, and compliance with regulatory requirements.

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Precisely

JULY 18, 2024

Key Takeaways Data Fabric is a modern data architecture that facilitates seamless data access, sharing, and management across an organization. Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata.

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Precisely

MARCH 23, 2023

Is your company making commitments to environmental, social, and governance (ESG) efforts? How are you quantifying those results, and can you make sure you have the most accurate and current data? In summary: your ESG data needs data integrity. Let’s examine that more. Have you cut down plastics by 25%?

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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. AI drives the demand for data integrity.

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Precisely

MAY 13, 2024

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. As enterprise technology landscapes grow more complex, the role of data integration is more critical than ever before.

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Precisely

MAY 23, 2024

Key takeaways: Quickly adapt to market changes by easily adding new data sources and targets, ensuring your IT landscape evolves at the pace of your business. Gain a competitive edge with real-time data integration, crucial for time-sensitive decisions and actions in fraud detection and customer interactions.

Data Integration 52

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Precisely

MAY 31, 2023

To innovate, compete, and grow in the current macroeconomic environment, enterprises must approach data strategically. A sound data strategy doesn’t happen by accident; it’s built on a foundation of data integrity , including accuracy, consistency, and rich context. Many organizations still struggle with data integrity.

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Precisely

JUNE 22, 2023

As the financial services landscape has become more complex and sophisticated, the concept of data quality has evolved to imply a holistic approach that encompasses the overall trustworthiness of data. They have found ways to curate and manage data to instill confidence among decision-makers.

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Precisely

AUGUST 8, 2023

Data governance is rapidly shifting from a leading-edge practice to a must-have framework for today’s enterprises. Although the term has been around for several decades, it is only now emerging as a widespread practice, as organizations experience the pain and compliance challenges associated with ungoverned data.

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Data Engineering Podcast

FEBRUARY 19, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Hey there podcast listener, are you tired of dealing with the headache that is the 'Modern Data Stack'? It's supposed to make building smarter, faster, and more flexible data infrastructures a breeze.

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Precisely

JANUARY 5, 2023

For some companies that do have a formal strategy, that strategy may be little more than a technical exercise, the primary purpose of which is to lay out the nuts and bolts of data management, compliance, and similar baseline requirements. Data governance plays a critical role in any effective data strategy.

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Precisely

MAY 3, 2023

Learn more The countdown is on to Trust ’23: the Precisely Data Integrity Summit! We recently announced the details of our annual virtual event , and we’re thrilled to once again bring together thousands of data professionals worldwide for two days of knowledge, insights, and inspiration for your data integrity journey.

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Precisely

AUGUST 29, 2024

Data observability continuously monitors data pipelines and alerts you to errors and anomalies. Data governance ensures AI models have access to all necessary information and that the data is used responsibly in compliance with privacy, security, and other relevant policies. stored: where is it located?

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RandomTrees

SEPTEMBER 17, 2024

In the realm of big data and AI, managing and securing data assets efficiently is crucial. Databricks addresses this challenge with Unity Catalog, a comprehensive governance solution designed to streamline and secure data management across Databricks workspaces. What is Unity Catalog?

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Data Engineering Podcast

MAY 26, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Can you start by sharing some of your experiences with data migration projects? Closing Announcements Thank you for listening! Don't forget to check out our other shows.

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Precisely

SEPTEMBER 6, 2023

However, fewer than half of survey respondents rate their trust in data as “high” or “very high.” ” Poor data quality impedes the success of data programs, hampers data integration efforts, limits data integrity causing big data governance challenges.

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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.

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Monte Carlo

SEPTEMBER 10, 2024

This truth was hammered home recently when ride-hailing giant Uber found itself on the receiving end of a staggering €290 million ($324 million) fine from the Dutch Data Protection Authority. Poor data warehouse governance practices that led to the improper handling of sensitive European driver data. The reason?

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Databand.ai

JULY 6, 2023

Data Integrity Testing: Goals, Process, and Best Practices Niv Sluzki July 6, 2023 What Is Data Integrity Testing? Data integrity testing refers to the process of validating the accuracy, consistency, and reliability of data stored in databases, data warehouses, or other data storage systems.

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Precisely

SEPTEMBER 8, 2023

In the meantime, data quality and overall data integrity suffer from neglect. According to a recent report on data integrity trends from Drexel University’s LeBow College of Business , 41% reported that data governance was a top priority for their data programs.

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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. Typically, businesses generate data in siloed applications.

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Databand.ai

JUNE 21, 2023

Eric Jones June 21, 2023 What Are Data Integrity Tools? Data integrity tools are software applications or systems designed to ensure the accuracy, consistency, and reliability of data stored in databases, spreadsheets, or other data storage systems. In this article: Why Are Data Integrity Tools Important?

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Data Engineering Podcast

APRIL 22, 2018

Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline you’ll need somewhere to deploy it, so check out Linode. What is OctopAI and what was your motivation for founding it? Can you talk through the architecture of your platform?

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AltexSoft

OCTOBER 8, 2021

The good news is, businesses can choose the path of data integration to make the most out of the available information. The bad news is, integrating data can become a tedious task, especially when done manually. Data integration in a nutshell. Data integration process. That’s a lot of work.

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AltexSoft

MARCH 2, 2023

As the amount of enterprise data continues to surge, businesses are increasingly recognizing the importance of data governance — the framework for managing an organization’s data assets for accuracy, consistency, security, and effective use. What is data governance? billion in 2020 to $5.28

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Precisely

AUGUST 3, 2023

The 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, delivers groundbreaking insights into the importance of trusted data. Let’s explore more of the report’s findings around data program successes, challenges, influences, and more.

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Precisely

MARCH 14, 2023

Deploy, execute, and scale natively in modern cloud architectures To meet the need for data quality in the cloud head on, we’ve developed the Precisely Data Integrity Suite. The modules of the Data Integrity Suite seamlessly interoperate with one another to continuously build accuracy, consistency, and context in your data.

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