Using DataOps for Data Pipeline Engineering Quality

Data pipelines facilitate information flows and data exchange for a growing number of operational scenarios, including data extraction, transformation, and loading ETL into data warehouses and data marts, data migrations, production of BI reports, and application interoperability. When data engineers develop data pipelines, they may devise a collection of tests to guide the development process, but ongoing tests are not often put in place once those pipelines are put into production.
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Transform Retail with IBM Big Data Solutions

TechD

New technologies have permanently transformed how customers communicate, interact, research and shop for goods and services. Retail data paired with retail analytics, can assist retailers in understanding and responding with actionable retail insights to the disrupted landscape and changing customer expectations.
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Data Privacy in Analytics

Data Protection and Privacy Compliance are becoming more ubiquitous and gaining in importance. In recent years, legislation has reacted by introducing e.g. the GDPR, the UK Data Protection Law or the California Consumer Privacy Act and associated regulations (“CCPA”). European Regulators especially have been clear that they take data privacy of their citizens very seriously, as shown in the January 2022 ruling of the Austrian courts against a website that was using Google Analytics.
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Designing a Successful Governed Citizen Data Science Strategy

datarobot

To compete in today’s digital economy, enterprises require new ways to expand AI across their entire organization. Nearly all firms want to do more with data science, but they don’t know where to begin or how to properly empower citizen data scientists to avoid common AI gone wrong accidents. In this session, we will discuss how to approach your journey into citizen data science with existing analytics talent. Proven best practices and lessons learned from successful early adopters of augmented data science will be shared. We will walk through example initiative roadmaps, recommended staffing, upskilling, mentoring and ongoing governance.
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Strategic Imperative – The Enterprise Data Model

IDERA

With today’s increasingly complex data ecosystems, the Enterprise Data Model (EDM) is a strategic imperative that every organization should adopt. An Enterprise Data Model provides context and consistency for all organizational data assets, as well as a classification framework for data governance. Enterprise modeling is also totally consistent with agile workflows, evolving incrementally to keep pace with changing organizational factors. In this session, IDERA’s Ron Huizenga will discuss the increasing importance of the EDM, how it serves as a framework for all enterprise data assets, and provides a foundation for data governance.
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