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Augmented analytics

Dataconomy

On the other hand, natural language processing facilitates interactions with data through familiar language, making it easier for users without extensive technical backgrounds to engage with complex datasets. Key features of augmented analytics A variety of features distinguish augmented analytics from traditional data analytics models.

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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Downtime, like the AWS outage in 2017 that affected several high-profile websites, can disrupt business operations. Understand what insights you need to gain from your data to drive business growth and strategy. Cost overruns : While the pay-as-you-go model is cost-effective, it can lead to unexpected costs if not managed carefully.

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9 data governance strategies that will unlock the potential of your business data

IBM Journey to AI blog

Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success. Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality.

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10 Years Later: Who’s the GOAT of Data Catalogs?

Alation

May 2016: Alation named a Gartner Cool Vendor in their Data Integration and Data Quality, 2016 report. January 2017: MercadoLibre signs on as the first LATAM customer. June 2017: Dresner Advisory Services names Alation the #1 data catalog in its inaugural Data Catalog End-User Market Study.

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Messy Data Shouldn’t Stop Machine Learning in Its Tracks

Dataversity

Businesses are creating data at an incredible pace that will only accelerate. In fact, data storage company Seagate predicts it will pass a yearly rate of “163 zettabytes (ZB) by 2025. That’s ten times the amount of data produced in 2017.” Moore’s Law – the principle that […].

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Lack of Data Integrity in Financial Institutions: How Much Is It Really Costing You?

Precisely

Data Integrity checks and best practices support data management as both strategic and tactical processes that enable companies to improve compliance, reduce costs, transform their customer relationships, and stay on the leading edge of innovation. This post examines the practical implications of poor data integrity.

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From the Boots of a Former CDO

Precisely

It was at this point that I realized that BI initiatives were doomed to failure unless data quality management was taken in hand! Improving data quality, as a key element of any data strategy initiative, was therefore a subject that appealed to me, and one that would be important in the years to come.