Hello from the CEO
While Data Science gets the headlines, Data Engineering is working hard behind the scenes to make the Data Science magic possible. And by working hard, I mean that Data Engineering typically accounts for 70-80% of the total effort a firm spends on making use of data. Data Science and the unique insights it delivers are business differentiators, but most firms spend a minority of the time on them.
That’s why forward-looking companies increasingly turn to a partner like Crux. By offloading their Data Engineering work, these companies give more time and energy to Data Science and move much more quickly to produce valuable new insights that power their businesses.
Crux brings laser focus, deep expertise, operational oversight, and a valuable network of data suppliers to help you orchestrate, implement, and operate your information supply chain.
At Crux, we make data delightful.
Crux Insights Blog
Five in 5 with Head of Data Engineering Andrew Clark
At Crux, being a data engineer means handling the tough work that makes data more actionable for our clients, and designing the tools that make our clients’ lives easier over time. Data engineers sit on the “data wrangling” side of the pipeline, meaning we are the folks who handle the hard work of figuring out where certain elements of the dataset live, slicing and dicing data, and repackaging it for distribution.
Today, the folks managing information supply chains are embracing the fact that the whole process does not need to exist on-premises anymore. While firms used to believe their data engineering was their “secret sauce”, today they realize it’s the insights they can glean that are more important. Using experts like Crux to remove as much of the tedious, upfront work as possible is now the preferred model.
Is it difficult to get access to useable data? Let Crux experts engineer your data to make it ready to use. Our data engineers take on your data challenges so that you can spend your time finding signals. Click HERE to chat with our team of experts.
Have data to share? Our data supplier community is growing by leaps and bounds. Our diverse datasets range from stock quotes to corporate trends to transportation data and more. No data is irrelevant. Create a Crux login HERE to browse our network and become a supplier.
Out and About
We’ve been building our community. In the past month, we’ve met with hundreds of suppliers and buyers of alternative data.
Quandl Alternative Data Conference | January 18, 2018
New York, NY
Battlefin Discovery Day Miami | January 30-31, 2018
Outsell Data Money | February 1, 2018
New York, NY
AI in Fintech Forum | February 8, 2018
Stanford University, Stanford, CA
Originally published November 8, 2017 at Inside Market Data
Author: Max Bowie
Originally published November 8, 2017 at Reuters
Author: Anna Irrera
Crux’s platform processes the data for financial firms, including banks, hedge funds, private equity groups and insurers, so they can focus resources on carrying out more differentiating tasks such as building artificial intelligence algorithms to extract value from the information.
This removes the biggest pain point, or “crux” of data analytics in finance, said Philip Brittan, chief executive of Crux.
“Everyone is looking at how to get more data and how to get more value out of the data that they have,” Brittan said in an interview. But “firms spend the majority of their data time on stuff that is not differentiated,” he added.
Crux does not sell or resell the data, but has established a network of information suppliers to help clients discover new sources.
Originally published November 8, 2017 at Silicon Angle
Author: Eric David
The San Francisco-based company calls itself a “data engineering concierge service,” allowing businesses to extract value from their unstructured data quickly and efficiently. Rather than doing the data analysis itself, which is generally left up to specialized artificial intelligence programs, Crux instead extracts and organizes companies’ data to make it more digestible. The company specializes in financial data for banks, hedge funds, financial firms and so on, which is what drew Goldman Sachs to the startup.
Originally published November 8, 2017 at American Banker
Author: Penny Crosman
It’s a given that banks, hedge funds, insurance companies, research firms and others have an insatiable need for data to make decisions – where to place bets, what companies to buy or fund, to whom to extend credit, and so forth.
Finding the right data from new sources, including data aggregators, alternative credit bureaus and satellite imagery, and making it readable to existing programs is a huge chore.