Dataversity

APRIL 18, 2022

Since the data from such processes is growing, data controls may not be strong enough to ensure the data is qualitative. That’s where Data Quality dimensions come into play. […]. The post Data Quality Dimensions Are Crucial for AI appeared first on DATAVERSITY.

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Dataversity

FEBRUARY 13, 2023

The key to being truly data-driven is having access to accurate, complete, and reliable data. In fact, Gartner recently found that organizations believe […] The post How to Assess Data Quality Readiness for Modern Data Pipelines appeared first on DATAVERSITY.

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Dataversity

AUGUST 10, 2023

We’ve all generally heard that data quality issues can be catastrophic. But what does that look like for data teams, in terms of dollars and cents? And who is responsible for dealing with data quality issues?

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Smart Data Collective

APRIL 20, 2022

Companies with an in-depth understanding of data analytics will have more successful Amazon PPC marketing strategies. However, it is important to make sure the data is reliable. However, data quality is again going to be very important. You must make sure the right sales page versions are stored in your database.

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Dataversity

FEBRUARY 10, 2021

In this blog, we will take a look at: The impact poor Data Quality has on organizations and practical advice for how to overcome this challenge through the use of feedback loops. Poor Data Quality can cost organizations millions each year. It can lead to incorrect decisions, […].

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Dataversity

JULY 3, 2023

What are the most common causes of Data Quality issues? The conventional answer to that question includes problems like inaccurate data, duplicate data, or data containing missing values.

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Dataversity

MARCH 30, 2023

These initiatives may provide companies with short-term reprieve during times of disruption, […] The post Optimizing Data Quality to Navigate Economic Turbulence appeared first on DATAVERSITY.

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Smart Data Collective

SEPTEMBER 29, 2022

The post Data-Driven Companies Leverage OCR for Optimal Data Quality appeared first on SmartData Collective. No more wasted time, employee frustration, or manual input errors: OCR is the solution you need to better process and manage your documents.

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Astera

APRIL 23, 2024

To do so, they need data quality metrics relevant to their specific needs. Organizations use data quality metrics, also called data quality measurement metrics, to assess the different aspects, or dimensions, of data quality within a data system and measure the data quality against predefined standards and requirements.

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Dataversity

DECEMBER 3, 2021

Three big shifts came this year, namely in the realms of consumer data privacy, the use of third-party cookies vs. first-party data, and the regulations and expectations […]. The post What to Expect in 2022: Data Privacy, Data Quality, and More appeared first on DATAVERSITY.

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Dataversity

FEBRUARY 15, 2023

Project Open Data is a place where fostering collaboration and promoting improvement in open data policy is intended. This […] The post How Can Project Open Data Improve Data Quality? appeared first on DATAVERSITY.

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Dataversity

JANUARY 13, 2023

When we talk to prospective customers, their first questions are usually around the fundamentals of data quality, including what it is, how we measure it, what happens when it goes south, and how data quality issues can be prevented.

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Dataversity

MARCH 14, 2022

The post When It Comes to Data Quality, Businesses Get Out What They Put In appeared first on DATAVERSITY. The stakes are high, so you search the web and find the most revered chicken parmesan recipe around. At the grocery store, it is immediately clear that some ingredients are much more […].

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Astera

APRIL 18, 2024

A strategic approach to data management is needed to meet these demands — particularly a greater focus on high data quality and robust governance to guarantee accuracy, security, and compliance. This monitoring helps ensure continuous enhancement of data quality and governance practices.

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Dataversity

MARCH 2, 2022

With the accelerating adoption of Snowflake as the cloud data warehouse of choice, the need for autonomously validating data has become critical. While existing Data Quality solutions provide the ability to validate Snowflake data, these solutions rely on a rule-based approach that is […].

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Dataversity

JANUARY 10, 2022

The road to better Data Quality is a path most data-driven organizations are already on. The path becomes bumpy for organizations when stakeholders are constantly dealing with data that is either incomplete or inaccurate. That scenario is far too familiar for most organizations and creates a lack of trust in Data Quality.

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The Data Administration Newsletter

MARCH 6, 2024

Data quality is measured across dimensions, but why? Data quality metrics exist to support the business. The value of a data quality program resides in the ability to take action to improve data to make it more correct and therefore more valuable.

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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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Dataversity

MARCH 3, 2021

The post Being Data-Driven Means Embracing Data Quality and Consistency Through Data Governance appeared first on DATAVERSITY. They want to improve their decision making, shifting the process to be more quantitative and less based on gut and experience.

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Dataversity

AUGUST 2, 2022

Unfortunately, most organizations – across all industries – have Data Quality problems that are directly impacting their company’s performance. The post Why Data Quality Problems Plague Most Organizations (and What to Do About It) appeared first on DATAVERSITY.

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Dataversity

FEBRUARY 4, 2022

I suspect the failure rates are even higher, as more and more organizations today are trying to utilize the power of data to improve their services or create new revenue streams. Not having the “right” data continues to prevent […]. The post Why Synthetic Data Still Has a Data Quality Problem appeared first on DATAVERSITY.

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GAVS Technology

APRIL 9, 2024

As part of a migration project, the customer wanted data validation and cleansing to ensure high data quality. Since data cleansing requires the validation of all migrated data between the source and target databases, manual validation based on random sampling techniques would not have sufficed.

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Dataversity

DECEMBER 20, 2022

The post Data Quality Best Practices to Discover the Hidden Potential of Dirty Data in Health Care appeared first on DATAVERSITY. Health plans will […].

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Dataversity

JANUARY 24, 2022

Business users want to know where that data lives, understand if people are accessing the right data at the right time, and be assured that the data is of high quality. But they are not always out shopping for Data Quality […].

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The Data Administration Newsletter

MAY 4, 2022

Getting to great data quality need not be a blood sport! This article aims to provide some practical insights gained from enterprise master data quality projects undertaken within the past […].

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Dataversity

JANUARY 8, 2021

The post Good AI in 2021 Starts with Great Data Quality appeared first on DATAVERSITY. Achieving good AI is a whole other story. AI initiatives can take a lot of time and effort to get up and running, often exceeding initial budget and […].

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ElegantJ BI

DECEMBER 11, 2019

Data Quality vs. Data Agility – A Balanced Approach! If you want to create an environment with a culture and processes that are balanced to accommodate data agility and data quality, you can start here: Benefits of Augmented Analytics Balance Original Post: Data Quality and Data Agility are Both Important to Success!

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ElegantJ BI

DECEMBER 11, 2019

Data Quality vs. Data Agility – A Balanced Approach! If you want to create an environment with a culture and processes that are balanced to accommodate data agility and data quality, you can start here: Benefits of Augmented Analytics Balance Original Post: Data Quality and Data Agility are Both Important to Success!

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ElegantJ BI

DECEMBER 11, 2019

Data Quality vs. Data Agility – A Balanced Approach! If you want to create an environment with a culture and processes that are balanced to accommodate data agility and data quality, you can start here: Benefits of Augmented Analytics Balance.

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Data Pine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

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The Data Administration Newsletter

MARCH 15, 2022

1 In this article, I will apply it to the topic of data quality. I will do so by comparing two butterflies, each that represent a common use of data quality: firstly and most commonly in situ for existing systems, and secondly for use […]. We know the phrase, “Beauty is in the eye of the beholder.”1

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Simplilearn

JUNE 30, 2021

Data is at the heart of everything important for businesses these days. Whether it’s customer data, sales forecasts, supply chain scheduling, or any other critical process, data drives most business operations. That’s why the field of data quality management (DQM) has become so vital, especially in the booming era of big data.

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Astera

AUGUST 3, 2023

Data quality stands at the very core of effective B2B EDI. According to Dun and Bradstreet’s recent report , 100% of the B2B companies that invested in data quality witnessed significant performance gains, highlighting the importance of accurate and reliable information.

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