Is data better off in the cloud, or better off remaining on premises?
Lyft's "Amundsen" metadata system is an example of how knowledge graphs are spreading throughout companies with grass-roots projects. It's all part of winning hearts and minds, in the view of Neo4j, the San Francisco startup spreading the religion of graphs.
The fully-managed service provides an immutable, cryptographically verifiable ledger for applications that need a central, trusted authority.
The country's Ministry of Justice argues the firm is collecting data belonging to underage users for targeted ads.
Promised with its roadmap for InfluxDB 2.0, the managed cloud service is being released today. As a major change from the existing platform, it will be the linchpin for building a new user base for the 2.0 edition.
Cloudera's initial release of the Cloudera Data Platform appears to have led to less uncertainty in the second quarter. Separately, Cloudera acquired Arcadia Data to fill in some analytics gaps.
Survey shows that cloud helps accelerate data modernization and transformation efforts. But it needs to be undertaken gradually, with an eye to security and performance.
A proof of concept has been built to remove the need to manually archive catalogues -- a process that has been used for over the last 20 years.
Consumers will soon be able to easily compare and switch energy service providers.
Syncsort’s just-announced intent to buy of Pitney Bowes Software solutions business, following its SQData acquisition, are aimed at bulking up mainframe connectivity and addressing gaps in data enrichment.
After complaints about a plan to score students on their socioeconomic challenges or privilege, College Board revamps its data strategy with a tool called Landscape that will offer context on high schools and neighborhoods.
Just as every company is now a technology company because you can't be in business without technology, every company is a data company - but most companies don't know about data or what to do with it.
With new competition from Oracle, Salesforce and Adobe looming, Segment is accelerating its expansion.
In just five years, the data management company has earned a $3.3B valuation; now it's rolling out new services and capabilities to help customers derive more value out of their data.
Not every business problem can be solved by using chatbots. Here are some inappropriate uses for the AI tool.
Traditionally, operational databases and platforms for data analysis have been two different worlds. This has come to be seen as natural, as after all the requirements for use cases that need immediate results and transactional integrity are very different from those that need complex analysis and long-running processing.
Remember how we noted data is going the way of the cloud? While there are no signs of this slowing down, there's another interesting trend unraveling, the so-called Insight Platforms as a Service (IPaaS). The thinking behind this is simple: if your data is in the cloud anyway, why not use a platform that's also in the cloud to run analytics on them, and automate as much of the process as possible?
The endless streams of data generated by applications lends its name to this paradigm, but also brings some hard to deal with requirements to the table: How do you deal with querying semantics and implementation when your data is not finite, what kind of processing can you do on such data, and how do you combine it with data from other sources or feed it to your machine learning pipelines, and do this at production scale?
The pace of change is catalyzed and accelerated at large by data itself, in a self-fulfilling prophecy of sorts: data-driven product -> more data -> better insights -> more profit -> more investment -> better product -> more data. So while some are still struggling to deal with basic issues related to data collection and storage, governance, security, organizational culture, and skillset, others are more concerned with the higher end of the big data hierarchy of needs.
As descriptive and diagnostic analytics are getting commoditized, we are moving up the stack towards predictive and prescriptive analytics. Predictive analytics is about being able to forecast what's coming next based on what's happened so far, while prescriptive analytics is about taking the right course of action to make a desirable outcome happen.
FC Barcelona is focusing on data analysis to give it an edge on the soccer field and at the bank.
Not all graphs are created similar. Here are the main differences between RDF and LPG, as presented by Jesus Barrasa, Director Telecoms Practice, Neo4j: http://bit.ly/howSemanticIsYourGraph
Facebook CEO Mark Zuckerberg has shared a series of pictures from the social network's datacenter site up near the Arctic Circle in Sweden.
Estimates peg more than one million people will visit Super Bowl City alone in the two weeks leading up to Super Bowl Sunday. No word yet on how many Instagrams of burritos and palm trees that could produce.
Ashley Madison users have many priorities. Apparently, an airtight password is not one of them.
Letter rip: Lessons any high-tech office warrior can learn from the teenage word masters of the National Spelling Bee
The annual Outside Lands music and food extravaganza marks the first occasion where AT&T is deploying all three of the biggest wireless tools in its arsenal at a single festival.
As well as acting as the hub for a grid of scientific institutions around the world, CERN's datacenter has to cope with vast amounts of raw data from its particle physics experiments.
There's no better way to put Chef Watson to the test than actually putting on an apron, heading down to the kitchen and taste whatever big data actually has to offer.
A couple of years back, even researchers would wave off using DNA to store data as something too futuristic. Today, you can run PostgreSQL on DNA. Read more: https://zd.net/2KyplhF
Yes, Facebook is a data-driven monopoly. But the only real way to break it up is by getting hold of its data and functionality, one piece at a time. Read more: https://zd.net/2Hw5EqA
ZDNet's Larry Dignan caught up with Dan Wulin, head of data science and machine learning at Wayfair to talk about how the company is using natural language processing for unstructured data and tracking returns on machine learning investment.
Mia Gaudet, ACS strategic director for breast and gynecologic cancer research, explains how machine learning techniques are advancing a research study launched in 1992 and what it took to prepare the data for analysis.
Brinker, the company behind the Chili's restaurant chain, is big on hybrid whether it's the approach to cloud computing, data science and the front end customer experience via a pilot with Apple iPads. We caught up with Wade Allen, chief digital officer of Brinker, to talk shop.
ZDNet's Greg Nichols tells TechRepublic's Karen Roby about how augmented reality and virtual reality are working to change the way we interact with data.
What if machine learning applications on the edge were possible, pushing the limits of size and energy efficiency? GreenWaves is doing this, based on an open-source parallel ultra low power microprocessor architecture. Read more: https://zd.net/2Nu2t43
Schools and charities beware: if someone pretending to be your boss emails you to buy Apple iTunes or Google Play gift cards, it’s almost certainly a scam.
For standard invoices and reports requiring efficient delivery, PDF-eXPLODE could well be a lifesaver. It can be a bit touchy on occasion, but once your document templates are set up properly it should be plain sailing.
InterSystems launches CACHÃƒÆ’Ã¢â‚¬Â° 2007, the latest update to their post-relational database product.
IBM's DB2 database adds several powerful new tools in version 9 including native XML support and DB2 Developer Workbench, and offers serious competition to Oracle and Microsoft.
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