In 1865, Richard Millar Devens presented the phrase “Business Intelligence” (BI) in the “Cyclopædia of Commercial and Business Anecdotes.” He used it to describe how Sir Henry Furnese, a banker, profited from information by gathering and acting on it before his competition. More recently, in 1958, an article was written by an IBM computer scientist […]
A Brief History of Data Silos
The original purpose of a data silo was to keep secrets. People have been keeping secrets for a long, long time. Prior to the written word, keeping a secret meant not sharing specific information with anyone else, verbally. And then came the written word. Secrets could be shared accidentally, or even stolen. Life became more […]
Is Lakehouse Architecture a Grand Unification in Data Analytics?
Click to learn more about author Arsalan Farooq. I do not think it is an exaggeration to say data analytics has come into its own over the past decade or so. What started out as an attempt to extract business insights from transactional data in the ’90s and early 2000s has now transformed into an […]
How to Avoid the Not So Mythical $50,000 Query in the Cloud
Click to learn more about author Chris Lynch. So, you’ve made the decision to go all-in on the cloud. (BTW, I don’t blame you — as a CEO, I’ve made the same choice myself, both for the company I run and the companies that I invest in.) Now your attention needs to focus on how […]
Hybrid Database Architectures Lead the Way
Hybrid databases have evolved in the last decade, with a focus on cloud environments. In 2013, Gartner created the term “Hybrid Transaction/Analytical Processing” (or HTAP), which is defined by Gartner as: “An emerging application architecture that ‘breaks the wall’ between transaction processing and analytics. It enables more informed and ‘in business real time’ decision making.” […]
Why You Should Learn PostgreSQL for Data Science
Click here to learn more about author Gilad David Maayan. Is SQL a requisite to be a data scientist? The answer is yes. Data Science has evolved, and while many data scientists still work with CSV files (text files with comma-separated values) these are not the best choice. The Python Panda library allows you to […]
The Power of OLAP and its Relevance in the Big Data Ecosystem
Click to learn more about author Brahmajeet Desai. With data flowing in from a countless array of applications and devices, extracting insights from the data lake and making them available to business users in an easily can be quite a daunting task. If you moved to a Hadoop or cloud-based Big Data platform with the […]
How to Become a Data-Driven Enterprise
Click to learn more about author Matthew Baird. Over the past few years, becoming “data-driven” has emerged as a popular objective for organizations across a variety of industries. Simply put, being data-driven involves leveraging existing operational and customer data as well as external data sources for both tactical and strategic decision-making. Such an approach complemented […]
Make the Most of Graph Databases Through Interactive Analytics
New Big Data systems and advanced technologies are revolutionizing how businesses analyze their data assets and discover new value and insights across their business practices. Barry Zane, Senior Vice President and John Rueter, Vice President of Marketing at Cambridge Semantics, both recently sat down with DATAVERSITY® to discuss how companies are implementing new technologies such […]
ScyllaDB Announces Release of Its NoSQL Database and Support for Concurrent OLTP and OLAP
A new press release states, “ScyllaDB, the real-time big data database company, kicked off its two-day Scylla Summit by announcing a major release of its database, Scylla Open Source 3.0. The company also previewed Scylla support for concurrent OLTP and OLAP, an industry first that enables simultaneous transactional and analytical processing. This release marks a […]