Tableau: All content tagged as Tableau in NoSQL databases and polyglot persistence
For the beginning of the week, some good and bad news:
Tableau Software’s IPO is considered successful.
The company didn’t really need more capital to operate, Chabot said, but one of the primary drivers was to raise awareness of the company. It has about 12,000 customers, he said, but there are millions more possible users. As part of attracting them, the company is going to expand globally and is working to improve its reach across mobile devices, the cloud and the Mac operating system.
Bradford Stephens announces that Drawn to Scale closes. Drawn to Scale was building a SQL-on-HBase solution and according to the post it already had paying customers.
It seemed we had everything going for us — paid customers such as American Express, a major telecom, Flurry, and 4 others. Our technology worked brilliantly, we had a big hiring pipeline, and we had great media presence against our competitors who raised 10-100x more cash.
Yet five days before we signed term sheets for a big A round or sold the company, we started getting hit by a series of black swans — and we just didn’t have what we needed to recover.
I didn’t talk to Bradford Stephens, but I assume the black swans are all the recent big name announcements related to SQL-on-Hadoop.
✚ Bradford, I’m sad to learn that the Drawn to Scale adventure has ended. But an end is just a new beginning. Good luck!
Original title and link: One Good and one bad ( ©myNoSQL)
- Big data gets even bigger
- Self-reliance is the new self-service
- The “Consumerization of Enterprise Software accelerates”
- Mobile BI goes mainstream
- Some companies start to get comfortable with social BI
- Companies explore the BI cloud
- Most jobs will require analytical skills… leading to talent shortages
- BI projects flourish under aligned IT & business
- Interactive data visualization becomes a requirement
- Hadoop gathers momentul — unstructured data isn’t going anywhere.
It sounds like companies will have to discover the fountain of money to be able to accomplish 2, 6, and 8 within an year.
Shawn Rogers has a short but compelling list of Big Data deployments in his article Big Data is Scaling BI and Analytics. This list also shows that even if there are some common components like Hadoop, there are no blueprints yet for dealing with Big Data.
Facebook: Hadoop analytic data warehouse, using HDFS to store more than 30 petabytes of data. Their Big Data stack is based only on open source solutions.
Quantcast: 3,000 core, 3,500 terabyte Hadoop deployment that processes more than a petabyte of raw data each day
University of Nebraska-Lincoln: 1.6 petabytes of physics data Hadoop cluster
Yahoo!: 100,000 CPUs in 40,000 computers, all running Hadoop. Also running a 12 terabyte MOLAP cube based on Tableau Software
eBay: has 3 separate analytics environments:
- 6PB data warehouse for structured data and SQL access
- 40PB deep analytics (Teradata)
- 20PB Hadoop system to support advanced analytic workload on unstructured data
Original title and link: Big Data Is Going Mainstream: Facebook, Yahoo!, eBay, Quantcast, and Many Others ( ©myNoSQL)