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

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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Data Quality Data Governance Data Architecture Government 245

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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Data Quality Digital Data Governance Government 246

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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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

APRIL 1, 2024

This reliance has spurred a significant shift across industries, driven by advancements in artificial intelligence (AI) and machine learning (ML), which thrive on comprehensive, high-quality data.

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Dataversity

JULY 12, 2024

At their core, LLMs are trained on large amounts of content and data, and the architecture […] The post RAG (Retrieval Augmented Generation) Architecture for Data Quality Assessment appeared first on DATAVERSITY. It is estimated that by 2025, 50% of digital work will be automated through these LLM models.

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Dataversity

FEBRUARY 14, 2023

Based on what we are seeing with our customers, we can expect a surge in the adoption of emerging technologies like generative artificial Intelligence as well as new software architectures that will transform markets, empower consumers, and deliver new personalized customer experiences. […] The post 2023: Generative AI, IoB-Informed Products, (..)

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Dataversity

AUGUST 1, 2024

Welcome to the latest edition of Mind the Gap, a monthly column exploring practical approaches for improving data understanding and data utilization (and whatever else seems interesting enough to share). Last month, we explored the rise of the data product. This month, we’ll look at data quality vs. data fitness.

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Dataversity

MAY 31, 2024

Data: Data is number, characters, images, audio, video, symbols, or any digital repository on which operations can be performed by a computer. Algorithm: An algorithm […] The post 12 Key AI Patterns for Improving Data Quality (DQ) appeared first on DATAVERSITY.

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Data Quality Digital Data Governance Government 147

Simplilearn

OCTOBER 28, 2021

Data saturates the modern world. Data is information, information is knowledge, and knowledge is power, so data has become a form of contemporary currency, a valued commodity exchanged between participating parties. By all accounts. Read More.

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Dataversity

SEPTEMBER 16, 2024

Public sector agencies increasingly see artificial intelligence as a way to reshape their operations and services, but first, they must have confidence in their data. Accurate information is crucial to delivering essential services, while poor data quality can have far-reaching and sometimes catastrophic consequences.

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Smart Data Collective

AUGUST 11, 2022

How Artificial Intelligence is Impacting Data Quality. Artificial intelligence has the potential to combat human error by taking up the tasking responsibilities associated with the analysis, drilling, and dissection of large volumes of data. Data quality is crucial in the age of artificial intelligence.

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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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Data Quality Data Governance Government 130

Timo Elliott

JANUARY 3, 2022

Other astronomers had collected similar data but had failed to recognize the full value of what they had observed – and today’s organizations are grappling with a similar dilemma. Opportunities for key insights are often buried in a vast universe of dormant information known as “dark data.”. Improving data quality.

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Timo Elliott

NOVEMBER 13, 2023

IT organizations have good excuses: it’s hard to build executive enthusiasm for something as seemingly plumbing-related as data quality. Generative AI increases the ROI you can get from clean data, and new Business Data Fabric approaches ( SAP Datasphere + strategic partnerships) are making it easier to achieve than ever.

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Data Quality 287

Smart Data Collective

FEBRUARY 23, 2021

To help you identify and resolve these mistakes, we’ve put together this guide on the various big data mistakes that marketers tend to make. Big Data Mistakes You Must Avoid. Here are some common big data mistakes you must avoid to ensure that your campaigns aren’t affected. Ignoring Data Quality.

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Smart Data Collective

JULY 15, 2021

A data catalog serves the same purpose. It organizes the information your company has on hand so you can find it easily. By using metadata (or short descriptions), data catalogs help companies gather, organize, retrieve, and manage information. It helps you locate and discover data that fit your search criteria.

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Smart Data Collective

DECEMBER 21, 2022

Big data technology has helped businesses make more informed decisions. A growing number of companies are developing sophisticated business intelligence models, which wouldn’t be possible without intricate data storage infrastructures. One of the biggest issues pertains to data quality.

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Smart Data Collective

SEPTEMBER 28, 2022

A data management solution helps your business run more efficiently by making sure that your data is reliable and secure. You can use information management software to improve your decision-making process and ensure that you’re compliant with the law. Data management helps you comply with the law.

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Smart Data Collective

APRIL 5, 2022

Agriculture, real estate, construction, and highway safety are some of the industries analyzing this data. You will also want to know how to harvest the data that you get. Do an Overcast Survey to Ensure You Get Reliable Data. We have talked extensively about the importance of both data quality and data quantity.

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Analysts Corner

AUGUST 15, 2022

Addresses are incorrect, duplicates abound, or product information is inaccurate. The data keeps getting dirtier no matter how much we try to clean it up. And you, as a BA, must now come up with workarounds and stopgap solutions to make up for the deficiencies in the data quality to deliver the solution your stakeholders seek.

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Smart Data Collective

OCTOBER 4, 2021

Unfortunately, big data is only as useful as it is accurate. Data quality issues can cause serious problems in your big data strategy. Customers won’t always directly tell you the information your company needs to provide better products or services. It relies on data to drive its AI algorithms.

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Smart Data Collective

JULY 9, 2023

By understanding the power of ETL, organisations can harness the potential of their data and gain valuable insights that drive informed choices. ETL is a three-step process that involves extracting data from various sources, transforming it into a consistent format, and loading it into a target database or data warehouse.

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Dataversity

SEPTEMBER 10, 2024

Companies increasingly know the need to protect their sensitive information and continue investing heavily in cybersecurity measures. However, this approach has a critical oversight: The assumption that […] The post The Role of Data Security in Protecting Sensitive Information Across Verticals appeared first on DATAVERSITY.

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Dataversity

NOVEMBER 7, 2022

Data quality issues have been a long-standing challenge for data-driven organizations. Even with significant investments, the trustworthiness of data in most organizations is questionable at best. Gartner reports that companies lose an average of $14 million per year due to poor data quality.

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Timo Elliott

MAY 19, 2023

Mastering Data Hygiene Reliable data is at the core of all digital transformation. Here’s a great example of how technology can help make sure that you have a solid information foundation for innovative new business processes. It’s always about people!

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Dataversity

SEPTEMBER 25, 2023

In an era where large language models (LLMs) are redefining AI digital interactions, the criticality of accurate, high-quality, and pertinent data labeling emerges as paramount. That means data labelers and the vendors overseeing them must seamlessly blend data quality with human expertise and ethical work practices.

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Smart Data Collective

OCTOBER 13, 2021

In the era of Big Data, the Web, the Cloud and the huge explosion in data volume and diversity, companies cannot afford to store and replicate all the information they need for their business. Data Virtualization allows accessing them from a single point, replicating them only when strictly necessary.

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Smart Data Collective

FEBRUARY 15, 2022

Begin by identifying data sets that you need and then start collecting this vital information. You also need to make sure that you have the right technology to handle these data sets. One of the best ways to get information is to survey people to get their input. Use the important information and discard the rest.

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Dataversity

OCTOBER 25, 2021

It’s common for enterprises to run into challenges such as lack of data visibility, problems with data security, and low Data Quality. But despite the dangers of poor data ethics and management, many enterprises are failing to take the steps they need to ensure quality Data Governance.

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Dataversity

DECEMBER 24, 2020

.” The series covers some of the most prominent questions in Data Management such as Master Data, the difference between Master Data and MDM, “truth” versus “meaning” in data, Data Quality, and so much […].

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Dataversity

JUNE 21, 2021

Building an accurate, fast, and performant model founded upon strong Data Quality standards is no easy task. Click to learn more about author Scott Reed. Taking the model into production with governance workflows and monitoring for sustainability is even more challenging.

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Timo Elliott

JANUARY 6, 2022

The point of finding your dark data is to generate insight from it. To this end, SAP offers a wide range of tools that support the following capabilities: Data orchestration. Information landscapes are complex. It also helps you fix data quality problems so that you can separate the signal from the noise.

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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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Data Quality Data Governance Government 182

Timo Elliott

JANUARY 4, 2021

Ferrara candy used analytics and dashboards during a recent big acquisition and they were able to get all the information they needed to run the business in real-time, literally at their fingertips. Ultimately, though, success with dashboards and data storytelling isn’t about technology. Inertia is a huge problem. The key takeaways.

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