article thumbnail

Data engineers vs. data scientists

O'Reilly Media - Data

It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.

article thumbnail

Monad emerges from stealth with $17M to solve the cybersecurity big data problem

TechCrunch

Once an organization has extracted data from their security tools, Monad’s Security Data Platform enables them to centralize that data within a data warehouse of choice, and normalize and enrich the data so that security teams have the insights they need to secure their systems and data effectively.

Big Data 246
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Tonic is betting that synthetic data is the new big data to solve scalability and security

TechCrunch

Big data is a sham. There is just one problem with big data though: it’s honking huge. Processing petabytes of data to generate business insights is expensive and time consuming. Processing petabytes of data to generate business insights is expensive and time consuming. What should a company do?

Big Data 267
article thumbnail

Identifying budding big data talent in your company

O'Reilly Media - Data

Big data is often called one of the most important skill sets in the 21st century, and it’s experiencing enormous demand in the job market. Hiring data scientists and other big data professionals is a major challenge for large enterprises, leading many to shift their efforts to training existing staff. Statistics.

Big Data 203
article thumbnail

Top Considerations for Building an Open Cloud Data Lake

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.

article thumbnail

It's time to establish big data standards

O'Reilly Media - Data

The deployment of big data tools is being held back by the lack of standards in a number of growth areas. Technologies for streaming, storing, and querying big data have matured to the point where the computer industry can usefully establish standards. Storage engine interfaces. Storage engine interfaces.

Big Data 193
article thumbnail

10 most in-demand enterprise IT skills

CIO

Its a versatile language used by a wide range of IT professionals such as software developers, web developers, data scientists, data analysts, machine learning engineers, cybersecurity analysts, cloud engineers, and more. Its widespread use in the enterprise makes it a steady entry on any in-demand skill list.

UI/UX 203
article thumbnail

12 Considerations When Evaluating Data Lake Engine Vendors for Analytics and BI

Businesses today compete on their ability to turn big data into essential business insights. To do so, modern enterprises leverage cloud data lakes as the platform used to store data for analytical purposes, combined with various compute engines for processing that data.