CIO
SEPTEMBER 14, 2023
With this in mind, we embarked on a digital transformation that enables us to better meet customer needs now and in the future by adopting a lightweight, microservices architecture. We found that being architecturally led elevates the customer and their needs so we can design the right solution for the right problem.
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. Data engineers also need communication skills to work across departments and to understand what business leaders want to gain from the company’s large datasets.
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High Scalability
AUGUST 2, 2021
What would a totally new search engine architecture look like? Search engines, and more generally, information retrieval systems, play a central role in almost all of today’s technical stacks. After more than 30 years of evolution since TREC, search engines continue to grow and evolve, leading to new challenges.
CIO
NOVEMBER 23, 2022
Enterprise architecture definition Enterprise architecture (EA) is the practice of analyzing, designing, planning, and implementing enterprise analysis to successfully execute on business strategies. Making it easier to evaluate existing architecture against long-term goals.
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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. The primary architectural principles of a true cloud data lake, including a loosely coupled architecture and open file formats and table structures.
Xebia
JANUARY 19, 2023
The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.
TechCrunch
FEBRUARY 8, 2023
The rise of streaming architectures — frameworks of software components built to ingest and process large volumes of data from multiple sources — is driving the demand for better reliability and performance. Engineering teams often encode data to improve app performance by using what are known as “message envelopes.”
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However, they often struggle with increasingly larger data volumes, reverting back to bottlenecking data access to manage large numbers of data engineering requests and rising data warehousing costs. This new open data architecture is built to maximize data access with minimal data movement and no data copies.
Speaker: Daniel "spoons" Spoonhower, CTO and Co-Founder at Lightstep
Many engineering organizations have now adopted microservices or other loosely coupled architectures, often alongside DevOps practices. Prioritize engineering work by putting it in the context of end user experience. However, this increased velocity often comes at the cost of overall application performance or reliability.
Speaker: Prem Chandrasekaran
In his best-selling book Patterns of Enterprise Application Architecture, Martin Fowler famously coined the first law of distributed computing—"Don’t distribute your objects"—implying that working with this style of architecture can be challenging. How these strategies can be applied in different size engineering organizations.
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