A great matrix of the different analytics use cases across industries in Hortonworks’s post “Enterprise Hadoop and the Journey to a Data Lake“:
The data type column section covers multiple dimensions of data. And the authors took a conservative approach for the structured and unstructured categories (in the sense that they marked very few categories as unstructured).
A couple of interesting exercises that can be done using this matrix as an input:
figure out how adding data from different categories to a specific use case would benefit it. One obvious example is: how would Telecom companies benefit from adding to their infrastructure analysis social data?
Building on the above, decide what tools exist to help with this extra scenario.
can one use case from an industry be applied to a different industry to disrupt it?
What would be the quickest road to accomplish it?
Original title and link: Examples of analytics applications across industries ( ©myNoSQL)
Today’s database landscape isn’t just static. It’s positively retro. Remember 2004? Facebook had just launched, the iPad wasn’t even a twinkle in Steve Jobs’ eye, and Gartner’s database market share report put IBM (34.1%), Oracle (33.7%), and Microsoft (20%) in the top spots. In our survey, Microsoft, Oracle, and IBM still hold the top spots; we do add MySQL, but that’s about it for innovation. […]
And those relational databases from Microsoft, Oracle, and IBM? They’re essentially just updated versions of the companies’ 2004 offerings.
You’ll see these numbers in many surveys. But there are a couple of things to keep in mind while reading them:
- the enterprise world is well-known to be a late adopter. A very late adopter actually.
- many of these databases are subscription based so customers are locked-in on at least an yearly basis
- many of these databases have been acquired together with hardware and consultancy/support. Another type of lock-in.
- none of these databases is showing the growth in demand, jobs, and revenue that the top NoSQL databases are seeing for the last 12-18 months.
When you already bought a house, it’s quite difficult to go out looking for a new one. But there’s no good reason for you not to look and get the best appliances and furniture for your house.
Original title and link: 2014 State Of Database Tech: Think Retro ( ©myNoSQL)
myNoSQL’s supporter Aerospike is getting ready for a new case study webinar:
As the industry’s largest online data exchange, BlueKai knows a thing or two about pushing the limits of scale. Find out how they are processing up to 10 trillion transactions per month from Vice President of Data Delivery, Ted Wallace.
Original title and link: April 3 Webinar: The BlueKai Playbook for Scaling to 10 Trillion Transactions a Month [sponsor] ( ©myNoSQL)