This report from our friends over at Snowflake reveals the extent to which the data sharing economy is powering business growth and how organizations are leveraging data from a range of sources to drive innovation, create better customer experiences, and meet regulatory requirements.
NoSQL vs SQL: Key Differences
January 20, 2021 by Leave a Comment
In this contributed article, Alex Williams, Writer/Researcher at Hosting Data UK, indicates that NoSQL and SQL databases greatly differ on many points. One is not better than the other, but just like any technology, eventually, developers will have their preferences. Luckily, there are numerous options for database selection for both SQL and NoSQL databases.
The 6 Types of Data Everybody Should Know to Avoid Confusion
December 25, 2020 by 1 Comment
Everybody tosses the word “data,” but few actually know what it actually means and does. MountainTop Data CEO Sky Cassidy explains the 6 different kinds of data everyone should know something about in order to avoid confusion.
Data Platforms – A journey. The Yesteryears, Today, and What Lies Ahead
November 25, 2020 by Leave a Comment
In this contributed article, Darshan Rawal, Founder and CEO of Isima, explains how the data ecosystem has exploded in the last decade to deal with multi-structured data sources. But the fundamental architecture of using queues, caches, and batches to support Enterprise Data Warehousing and BI hasn’t. This article looks at the architectural styles of the three eras of data management – pre-big data, the open-source revolution, and the cloud-native version. It will be a dive into trade-offs of each and what lies ahead. You’ll get a techno-strategic best practices of architecting data platforms as they pave the path to recovery for your organization.
Analyze-then-Store: The Journey to Continuous Intelligence – Part 6
October 5, 2020 by Leave a Comment
This multi-part article series by our friends at Swim is intended for data architects and anyone else interested in learning how to design modern real-time data analytics solutions. It explores key principles and implications of event streaming and streaming analytics, and concludes that the biggest opportunity to derive meaningful value from data – and gain continuous intelligence about the state of things – lies in the ability to analyze, learn and predict from real-time events in concert with contextual, static and dynamic data. This article series places continuous intelligence in an architectural context, with reference to established technologies and use cases in place today.
Analyze-then-Store: The Journey to Continuous Intelligence – Part 5
September 21, 2020 by Leave a Comment
This multi-part article series by our friends at Swim is intended for data architects and anyone else interested in learning how to design modern real-time data analytics solutions. It explores key principles and implications of event streaming and streaming analytics, and concludes that the biggest opportunity to derive meaningful value from data – and gain continuous intelligence about the state of things – lies in the ability to analyze, learn and predict from real-time events in concert with contextual, static and dynamic data. This article series places continuous intelligence in an architectural context, with reference to established technologies and use cases in place today.
Analyze-then-Store: The Journey to Continuous Intelligence – Part 4
August 31, 2020 by Leave a Comment
This multi-part article series by our friends at Swim is intended for data architects and anyone else interested in learning how to design modern real-time data analytics solutions. It explores key principles and implications of event streaming and streaming analytics, and concludes that the biggest opportunity to derive meaningful value from data – and gain continuous intelligence about the state of things – lies in the ability to analyze, learn and predict from real-time events in concert with contextual, static and dynamic data. This article series places continuous intelligence in an architectural context, with reference to established technologies and use cases in place today.
Analyze-then-Store: The Journey to Continuous Intelligence – Part 3
August 17, 2020 by Leave a Comment
This multi-part article series by our friends at Swim is intended for data architects and anyone else interested in learning how to design modern real-time data analytics solutions. It explores key principles and implications of event streaming and streaming analytics, and concludes that the biggest opportunity to derive meaningful value from data – and gain continuous intelligence about the state of things – lies in the ability to analyze, learn and predict from real-time events in concert with contextual, static and dynamic data. This article series places continuous intelligence in an architectural context, with reference to established technologies and use cases in place today.
Interview: Global Technology Leader PNY
June 8, 2020 by Leave a Comment
We recently caught up with our friends over at PNY to discuss a variety of topics affecting data scientists conducting work on big data problem domains including how “Big Data” is becoming increasingly accessible with big clusters with disk-based databases, small clusters with in-memory data, single systems with in-CPU-memory data, and single systems with in-GPU-memory data. Answering our inquiries were: Bojan Tunguz, Senior System Software Engineer, NVIDIA and Carl Flygare, NVIDIA Quadro Product Marketing Manager, PNY.
Why Databases are Failing the Modern Economy
November 5, 2019 by 1 Comment
In this contributed article, industry luminary Andrew “Flip” Filipowski discusses the state of database technology in terms of how in spite of the massive increase in demand for data, the industry never underwent a complete overhaul of the way databases work. Instead, programmers have used patchwork retrofitting to adjust databases to modern-day needs, solving problems with countless point solutions instead of rethinking the way databases work from the ground up.
