Remove Data Integration Remove Data Processing Remove Data Quality
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The DataOps Vendor Landscape, 2021

DataKitchen

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Data breaks.

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Data Integrity, the Basis for Reliable Insights

Sisense

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is. What is data integrity?

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How to Deliver Data Quality with Data Governance: Ryan Doupe, CDO of American Fidelity, 9-Step Process

Alation

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me. Step 2: Data Definitions.

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The importance of data ingestion and integration for enterprise AI

IBM Big Data Hub

Data ingestion must be done properly from the start, as mishandling it can lead to a host of new issues. The groundwork of training data in an AI model is comparable to piloting an airplane. The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions.

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NLP Isn’t Enough. Leading Financial Services Companies Are Now Moving to Conversational AI.

CIO Business Intelligence

As with all financial services technologies, protecting customer data is extremely important. In some parts of the world, companies are required to host conversational AI applications and store the related data on self-managed servers rather than subscribing to a cloud-based service. Just starting out with analytics?

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Top 10 Data Lineage Podcasts, Blogs, and Magazines

Octopai

This podcast centers around data management and investigates a different aspect of this field each week. Within each episode, there are actionable insights that data teams can apply in their everyday tasks or projects. The host is Tobias Macey, an engineer with many years of experience. Agile Data.

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Why you should care about debugging machine learning models

O'Reilly on Data

Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes. Privacy harms : models can compromise individual privacy in a long (and growing) list of ways. [8]