Smart Data Collective

SEPTEMBER 29, 2022

Find out in this article how your company can benefit from the use of OCR. This article reveals all! The post Data-Driven Companies Leverage OCR for Optimal Data Quality appeared first on SmartData Collective. Even so, it takes time and can quickly become an obstacle to the smooth running of your business.

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TDAN

OCTOBER 18, 2022

Last week, we presented a webinar in our Data Governance — Best Practices series on data quality. Obviously, we’re a […].

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CIO Business Intelligence

AUGUST 2, 2022

Reyes accomplishments and success in the IT industry was acknowledged last year in an award-winning CIO.com article profiling Hispanic technology executives who have broken through barriers to rise to the top of the IT industry, paving a path for others to follow. The second is the data quality in our legacy systems. That’s one.

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TDAN

NOVEMBER 14, 2023

Data empowers businesses to gain valuable insights into industry trends and fosters profitable decision-making for long-term growth. No wonder businesses of all sizes are switching to data-driven culture from conventional practices.

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TDAN

DECEMBER 2, 2020

Ensuring data quality is an important aspect of data management and these days, DBAs are increasingly being called upon to deal with the quality of the data in their database systems more than ever before. The importance of quality data cannot be overstated.

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TDAN

MAY 1, 2024

If you look at Google Trends, you’ll see that the explosion of searches for generative AI (GenAI) and large language models correlates with the introduction of ChatGPT back in November 2022.

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TDAN

DECEMBER 19, 2023

One of the reasons why there’s always excess production in the textile sector is the stringent requirement of meeting set quality standards. As far as healthcare is concerned, surprisingly, only two out of five health executives believe they receive healthy data through […]

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TDAN

AUGUST 31, 2021

Data is everywhere! But can you find the data you need? What can be done to ensure the quality of the data? How can you show the value of investing in data? Can you trust it when you get it? These are not new questions, but many people still do not know how to practically […].

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Anmut

JULY 12, 2021

Data without context is just meaningless noise, and any effort to improve or extract value from your data without considering the larger business context is doomed to fall short.? Unfortunately, traditional approaches to data remediation often focus on technical data quality in isolation from the broader data and business ecosystem.

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TDAN

OCTOBER 3, 2023

My recent columns have focused on actionable initiatives that can both deliver business value, providing a tangible achievement, and raise the profile of the data management organization data management organization (DMO).(For In that light, let’s […]

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Analytics Vidhya

DECEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. Introduction In machine learning, the data is an essential part of the training of machine learning algorithms. The amount of data and the data quality highly affect the results from the machine learning algorithms.

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TDAN

APRIL 5, 2022

Regardless of how accurate a data system is, it yields poor results if the quality of data is bad. As part of their data strategy, a number of companies have begun to deploy machine learning solutions. In a recent study, AI and machine learning were named as the top data priorities for 2021, by 61% […].

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TDAN

OCTOBER 17, 2023

Where exactly within an organization does the primary responsibility lie for ensuring that a data pipeline project generates data of high quality, and who exactly holds that responsibility? Who is accountable for ensuring that the data is accurate? Is it the data engineers? The data scientists?

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TDAN

JUNE 1, 2021

“Quality is never an accident. ” John Ruskin, prominent Victorian era social thinker Data-driven decision-making is fast becoming a critical business strategy for organizations in every sector. However, if the data used to make these decisions is not high-quality, it can’t be trusted.

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Analytics Vidhya

DECEMBER 28, 2022

This article was published as a part of the Data Science Blogathon. Choosing the best appropriate activation function can help one get better results with even reduced data quality; hence, […].

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TDAN

OCTOBER 5, 2022

Fortune 1000 organizations spend approximately $5 billion in total each year to improve the trustworthiness of data. Yet, only 42% of the executives trust their data. According to multiple surveys, executives across industries do not completely trust the data in their organization for accurate, timely business-critical decision-making.

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TDAN

DECEMBER 14, 2021

The Data Ethics Conundrum The recent DAMA EMEA conference was a valiant effort to connect the DAMA membership in the EMEA region through an innovative virtual conference format. One of these polls asked, “Are Data Ethics Principles Universal?” During the conference, various polls were run.

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Dataiku

AUGUST 2, 2023

This is a guest article from our friends at Starburst. Starburst is a full-featured data lakes platform that includes all the capabilities needed to discover, organize and consume data without the need for time-consuming and costly data migrations.

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Analytics Vidhya

SEPTEMBER 2, 2021

This article was published as a part of the Data Science Blogathon Overview Running data projects takes a lot of time. Poor data results in poor judgments. Running unit tests in data science and data engineering projects assures data quality. You know your code does what you want it to do.

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Dataiku

SEPTEMBER 7, 2023

This article was written by our friends at Databricks. Databricks is the Data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, and over 50% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI.

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TDAN

MARCH 5, 2019

You know you can rule the quality of your data. Read on to learn simple but effective tips on how to make superb data quality possible. The bad news is: Low-quality data costs companies about $15 million per year, according to Gartner’s Data Quality Market Survey. So why don’t you?

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TDAN

MARCH 1, 2022

This article is the third in a series taking a deep dive on how to do a current state analysis on your data. This article focuses on data culture, what it is, why it is important, and what questions to ask to determine its current state. The first two articles focused on data quality and data […].

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DataKitchen

AUGUST 8, 2023

On 20 July 2023, Gartner released the article “ Innovation Insight: Data Observability Enables Proactive Data Quality ” by Melody Chien. It alerts data and analytics leaders to issues with their data before they multiply. It alerts data and analytics leaders to issues with their data before they multiply.

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TDAN

FEBRUARY 21, 2024

Many Data Governance or Data Quality programs focus on “critical data elements,” but what are they and what are some key features to document for them? A critical data element is any data element in your organization that has a high impact on your organization’s ability to execute its business strategy.

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DataKitchen

FEBRUARY 23, 2024

Webinar: Beyond Data Observability: Personalization DataKitchen DataOps Observability Problem Statement White Paper: ‘Taming Chaos’ Technical Product Overview Four-minute online demo Detailed Product: Documentation Webinar: Data Observability Demo Day DataKitchen DataOps TestGen Problem Statement White Paper: ‘Mystery Box Full Of Data Errors’ (..)

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datapine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

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TDAN

SEPTEMBER 7, 2022

Fit for Purpose data has been a foundational concept of Data Governance for as long as I’ve been in the field…so that’s 10-15 years now. Most data quality definitions take Fit-for-Purpose as a given.

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DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It also addresses the unique demands of specialized Data Consumers who require personalized data tracking.

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O'Reilly on Data

JUNE 18, 2019

As model building become easier, the problem of high-quality data becomes more evident than ever. Even with advances in building robust models, the reality is that noisy data and incomplete data remain the biggest hurdles to effective end-to-end solutions. Data integration and cleaning.

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TDAN

MARCH 20, 2024

In the realm of big data, ensuring the reliability and accuracy of data is crucial for making well-informed decisions and actionable insights. Data cleansing, the process of detecting and correcting errors and inconsistencies in datasets, is critical to maintaining data quality.

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Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. In this article, we will explore the significance of ETL and how it plays a vital role in enabling effective decision making within businesses. Both approaches aim to improve data quality and enable accurate analysis.

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DataKitchen

OCTOBER 20, 2023

While this is a technically demanding task, the advent of ‘Payload’ Data Journeys (DJs) offers a targeted approach to meet the increasingly specific demands of Data Consumers. Deploying a Data Journey Instance unique to each customer’s payload is vital to fill this gap.

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TDAN

FEBRUARY 7, 2024

However, when it comes to data curation and data quality management, there seems to […] By now, it is clear to everyone that AI, especially generative AI, is the only topic you’re allowed to write about. It seems to have impacted every area of information technology, so, I will try my best to do my part.

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TDAN

MAY 16, 2023

Data quality management (DQM) has advanced considerably over the years. The full extent of the problem was first recognized during the data warehouse movement in the 1980s.

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Smart Data Collective

APRIL 5, 2022

Drone surveyors must also know how to gather and use data properly. They will need to be aware of the potential that data can bring to entities using drones. Indiana Lee discussed these benefits in an article for Drone Blog. You will also want to know how to harvest the data that you get.

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Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Databricks – providing the complete business context across the evolved Data Warehouse Cloud – the new Data Lakehouse platform.

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CIO Business Intelligence

MAY 8, 2024

Of late, innovative data integration tools are revolutionising how organisations approach data management, unlocking new opportunities for growth, efficiency, and strategic decision-making by leveraging technical advancements in Artificial Intelligence, Machine Learning, and Natural Language Processing.

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