CIO
SEPTEMBER 14, 2023
What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.
CIO
AUGUST 9, 2022
What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. The data engineer role.
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Dzone - DevOps
JANUARY 23, 2024
Big data has become increasingly important in today's data-driven world. It refers to the massive amount of structured and unstructured data that is too large to be handled by traditional database systems. To efficiently process and analyze this vast amount of data, organizations need a robust and scalable architecture.
CIO
OCTOBER 13, 2023
Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architects are frequently part of a data science team and tasked with leading data system projects.
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Multi-tenant architecture allows software vendors to realize tremendous efficiencies by maintaining a single application stack instead of separate database instances while meeting data privacy needs. When you use a data warehouse to power your multi-tenant analytics, the proper approach is vital.
CIO
MAY 21, 2024
In the annual Porsche Carrera Cup Brasil, data is essential to keep drivers safe and sustain optimal performance of race cars. Until recently, getting at and analyzing that essential data was a laborious affair that could take hours, and only once the race was over. The process took between 30 minutes and two hours.
Cloudera
MAY 9, 2024
The Gartner Data and Analytics Summit in London is quickly approaching on May 13 th to 15 th , and the Cloudera team is ready to hit the show floor! With the rapid pace of AI innovations, today’s leaders must connect, share, and learn from each other on how to best leverage AI technology to effectively analyze data to our advantage.
Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri
Data teams in large enterprise organizations are facing greater demand for data to satisfy a wide range of analytic use cases. Yet they are continually challenged with providing access to all of their data across business units, regions, and cloud environments.
Speaker: Veena Vasudevan and Jason Hughes
With data stored in vendor-agnostic files and table formats like Apache Iceberg, the open lakehouse is the best architecture to enable data democratization. By moving analytic workloads to the data lakehouse you can save money, make more of your data accessible to consumers faster, and provide users a better experience.
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Data fuels the modern enterprise — today more than ever, businesses compete on their ability to turn big data into essential business insights. Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data.
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Every data-driven project calls for a review of your data architecture—and that includes embedded analytics. Before you add new dashboards and reports to your application, you need to evaluate your data architecture with analytics in mind.
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Data architectures to support reporting, business intelligence, and analytics have evolved dramatically over the past 10 years. Download this TDWI Checklist report to understand: How your organization can make this transition to a modernized data architecture. The decision making around this transition.
Speaker: speakers from Verizon, Snowflake, Affinity Federal Credit Union, EverQuote, and AtScale
Join this webinar panel for practical advice on how to build and foster a data literate, self-service analysis culture at scale using a semantic layer. In this webinar you will learn about: Making data accessible to everyone in your organization with their favorite tools. Driving a self-service analytics culture with a semantic layer.
Speaker: Ahmad Jubran, Cloud Product Innovation Consultant
Many do this by simply replicating their current architectures in the cloud. Those previous architectures, which were optimized for transactional systems, aren't well-suited for the new age of AI. In this webinar, you will learn how to: Take advantage of serverless application architecture. And much more!
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