Remove 2017 Remove Data Governance Remove Data Quality
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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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9 data governance strategies that will unlock the potential of your business data

IBM Journey to AI blog

The best way to build a strong foundation for data success is through effective data governance. Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success.

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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.

Analytics 203
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From the Boots of a Former CDO

Precisely

Jean-Paul sat down for an interview where we discussed his background as a former CDO, the challenges he faced, and how he developed his unique perspective and data governance expertise. It was at this point that I realized that BI initiatives were doomed to failure unless data quality management was taken in hand!

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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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What Is Data Intelligence?

Alation

It asks much larger questions, which flesh out an organization’s relationship with data: Why do we have data? Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more.

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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 […].