Precisely

FEBRUARY 12, 2024

Read our eBook Data Governance 101 Read this eBook to learn about the challenges associated with data governance and how to operationalize solutions. Read Common Data Challenges in Telecommunications As natural innovators, telecommunications firms have been early adopters of advanced analytics.

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RandomTrees

SEPTEMBER 17, 2024

Understanding the Object Hierarchy in Metastore Identifying the Admin Roles in Unity Catalog Unveiling Data Lineage in Unity Catalog: Capture and Visualize Simplifying Data Access using Delta Sharing 1. Improved Data Discovery The tagging and documentation features in Unity Catalog facilitate better data discovery.

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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. With these goals in mind, access to accurate, consistent, and contextual information is critical. Clickstream analytics and mobile trace data offer consumer behavior insights.

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Precisely

SEPTEMBER 15, 2023

Data governance is no trivial undertaking. When executed correctly, data governance transitions businesses from guesswork to data-informed strategies. For those who follow the right roadmap on their data governance journey, the payoff can be enormous.

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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

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 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

JANUARY 9, 2023

As data initiatives become more sophisticated, organizations will uncover new data quality challenges. 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.

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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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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

JANUARY 5, 2023

To make a difference for your organization, your data strategy should address more than just raw data; it needs to lay out a roadmap for aligning the people, processes, and technology that can support a truly data-driven culture. Data governance plays a critical role in any effective data strategy.

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Databand.ai

AUGUST 30, 2023

Data Accuracy vs Data Integrity: Similarities and Differences Eric Jones August 30, 2023 What Is Data Accuracy? Data accuracy refers to the degree to which data is correct, precise, and free from errors. In other words, it measures the closeness of a piece of data to its true value.

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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

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

JULY 17, 2023

And trusted data needs data integrity – maximum accuracy, consistency, and context. Cleansing and enriching data due to inefficient cleansing processes, address data inconsistencies, and limited access to external datasets. That’s where the Precisely Data Integrity Suite comes in.

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Precisely

JULY 31, 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 integrity maturity, challenges, and priorities.

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Precisely

FEBRUARY 6, 2023

The success of all of those investments hinges on high levels of data integrity. Data infrastructure spending is expected to reach $200 billion in 2022, and 68% of Fortune 1000 businesses now have hired Chief Digital Officers, elevating data integrity to the level of the C-suite. What Is Data Integrity?

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Precisely

DECEMBER 13, 2023

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! Santa also needs to consider how to access each house. You guessed it….Santa

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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. However, they require a strong data foundation to be effective.

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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

MARCH 6, 2023

Read Financial Services ESG Reporting: The essential role of data Financial organizations are now assessing how they can derive more environmental, social and governance insights, while optimizing reporting through their existing infrastructure.

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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. Projections show that the data governance market will expand from $1.81

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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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Striim

AUGUST 31, 2023

Showing how Kappa unifies batch and streaming pipelines The development of Kappa architecture has revolutionized data processing by allowing users to quickly and cost-effectively reduce data integration costs. Stream processors, storage layers, message brokers, and databases make up the basic components of this architecture.

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Precisely

OCTOBER 14, 2024

Key Takeaways: Only 12% of organizations report their data is of sufficient quality and accessibility for AI. Data analysis (57%) is the top-cited reason organizations are considering the use of AI. The top data challenge inhibiting the progress of AI initiatives is data governance (62%). The results are in!

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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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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

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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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. However, they require a strong data foundation to be effective.

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Precisely

MARCH 14, 2023

First, private cloud infrastructure providers like Amazon (AWS), Microsoft (Azure), and Google (GCP) began by offering more cost-effective and elastic resources for fast access to infrastructure. Cloud-native data execution is just the beginning. How could streamlined access to quality data benefit your organization?

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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

APRIL 11, 2023

What existing data does the organization have to support my initiative? Where does that data live? Do I have access to the data? What do I need to do to access the data now and make it easy to find and access in the future? How can I ensure the data is up-to-date and issue-free moving forward?

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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. The impact?

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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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Databand.ai

JUNE 22, 2023

Ryan Yackel June 22, 2023 What Is Data Integrity? Data integrity is concerned with the accuracy, consistency, and reliability of data stored in databases or other data storage systems. Entity integrity: Ensures each row in a database table is uniquely identifiable.

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Snowflake

JANUARY 23, 2023

Marketing data integration is the process of combining marketing data from different sources to create a unified and consistent view. If you’re running marketing campaigns on multiple platforms—Facebook, Instagram, TikTok, email—you need marketing data integration. What Problems does Data Integration Solve?

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