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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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

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. Data integrity trends for 2023 promise to be an important year for all aspects of data management. Read The Corinium report to learn more.

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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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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

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

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. The right data integration solution helps you streamline operations, enhance data quality, reduce costs, and make better data-driven decisions.

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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

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

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

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

OCTOBER 23, 2023

When most people think of master data management, they first think of customers and products. But master data encompasses so much more than data about customers and products. Challenges of Master Data Management A decade ago, master data management (MDM) was a much simpler proposition than it is today.

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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

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

JULY 19, 2023

Data governance is fast becoming a business imperative. Many top executives and line-of-business managers lack a clear understanding of the benefits of data governance. Data governance plays a critical role in risk management and compliance as well. How can you within your organization?

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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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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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Data Engineering Podcast

NOVEMBER 30, 2020

Summary The first stage of every good pipeline is to perform data integration. With the increasing pace of change and the need for up to date analytics the need to integrate that data in near real time is growing. Immuta is an automated data governance solution that enables safe and easy data analytics in the cloud.

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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

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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Precisely

DECEMBER 13, 2023

It’s a logistical and data management nightmare! Using data quality and address validation tools, Santa’s team can cleanse, standardize and dedupe the data to ensure it has maximum accuracy and integrity, so that every child gets a suitable gift and they are delivered to the correct house! Think about it.

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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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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

MARCH 23, 2023

You need a flexible framework to efficiently identify, understand, and link the underlying data elements required for accurate, consistent, and contextualized ESG reporting. In summary: your ESG data needs data integrity. The post Why You Need Data Integrity for ESG Reporting appeared first on Precisely.

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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 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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The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. Potential downsides of data lakes include governance and integration challenges.

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The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. Potential downsides of data lakes include governance and integration challenges.

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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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The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. Potential downsides of data lakes include governance and integration challenges.

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The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

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The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

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The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

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Monte Carlo

JUNE 16, 2023

Data integrity and quality may seem similar at first glance, and they are sometimes used interchangeably in everyday life, but they play unique roles in successful data management. You can have data quality, without data integrity.

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Precisely

AUGUST 22, 2024

Key Takeaways Data fabric and data mesh are modern data management architectures that allow organizations to more easily understand, create, and manage data for more timely, accurate, consistent, and contextual data analytics and operations. The choice between the two depends on your business needs.

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Databand.ai

JUNE 20, 2023

Niv Sluzki June 20, 2023 What Is Data Integrity? Data integrity refers to the overall accuracy, consistency, and reliability of data stored in a database, data warehouse, or any other information storage system.

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