While the field of data science is not tied directly to Big Data, advances in one tends to produce advances in the other. Big Data increases our ability to harvest and process data, while data science allows us to dig into it for insights.
It isn’t a surprise that the amount of data generated in the past few years is astounding—in fact, the data generated within the last two years is close to 90 percent of all data ever generated. However, 80 percent of all enterprise data is unstructured as the numbers continue to
Data science is one of the most recent buzzwords that is gaining popularity in tech circles. With the number of job advertisements on the rise, one may think that data science and their professionals, data scientists, would become one of the most sought-after professionals in the technology job market over
With the fast-growing interest in data lakes — a storage solution that allows structured and semi-structured data to live in the same place — attention is turning toward metadata as a way to organize large amounts of diverse enterprise data. Metadata is an ambiguous and generic term, but it most
During one of our data-munging sessions here at Coralogix, we found ourselves needing to assess the cardinality of large data sets. Getting the accurate result is seemingly trivial: you simply iterate over the data, and count the number of unique elements. In reality, however, the task is more troublesome, mainly
When both NASA and the Pope are speaking out about climate change, you know something is up. Yesterday the NASA Earth Exchange (NEX) unveiled a public data set showing how rainfall, temperature and CO2 levels will change over the next 85 years. The high-resolution data, which is as granular as
‘Streams in the Beginning, Graphs in the End’ is a three-part series by Dataconomy contributor and Senior Director of Product Management at Cray, Inc., Venkat Krishnamurthy – focusing on how big changes are afoot in data management, driven by a very different set of use cases around sensor data processing.
‘Streams in the Beginning, Graphs in the End’ — Part I: Data Management for the Internet of Everything
‘Streams in the Beginning, Graphs in the End’ is a three-part series by Dataconomy contributor and Senior Director of Product Management at Cray, Inc., Venkat Krishnamurthy – focusing on how big changes are afoot in data management, driven by a very different set of use cases around sensor data processing. In this first part, we’ll talk
“Important Questions About The Human Condition Should Be Addressed with Data Science”: An Interview with Data Scientist Thomas Levi.
Thomas Levi is a Data Scientist at Plenty of Fish (POF), a free online dating website based in Vancouver. Thomas has a background in theoretical physics and at one point worked in string theory. Much of his work has involved topic models and other cool algorithms Follow Peadar’s series of
The sheer volumes involved with Big Data can sometimes be staggering. So if you want to get value from the time and money you put into a data analysis project, a structured and strategic approach is very important. The phenomenon of Big Data is giving us ever-growing volume and variety
These days, every business is exploring ways to use data and new technologies to gain a competitive edge. While there’s no questioning the value to be found in big data analytics, organizations have had a low success rate to date when it comes to rolling out data initiatives. A recent