5 Big Wishes For Big Data Deployments - InformationWeek
Data Management // Big Data Analytics
01:27 PM
Doug Henschen
Doug Henschen
Connect Directly

5 Big Wishes For Big Data Deployments

Big data project leaders still hunger for some key technology ingredients. Starting with SQL analysis, we examine the top five wants and the people working to solve those problems.
4 of 6

Wish 3: Easier Paths To Advanced Analytics
Developing algorithms and predictive models is work that has to be carried out by hard-to-find, expensive data scientists. Or is it? Scarcity of talent is one reason big-data, analytics and business intelligence vendors are developing machine-learning approaches. Proven in applications including optical character recognition, spam filtering and computer security threat detection, machine learning uses learning algorithms that are trained by the data itself. If you show the algorithm thousands or tens of thousands of examples of scanned text characters, unsolicited email messages, or virus bots and malware, it can reliably find more examples.

The same approach can be applied to spotting customers who are ready to churn or jet engines that are about to fail. With machine learning, trained models also can continue to learn from new data. Amazon.com and Netflix, for example, use algorithms to spot patterns in customer transactions so they can recommend other books or movies. When a new book or movie comes out, these companies can start recommending it as soon as their algorithms discerns the preference pattern in the data.

Apache Mahout is the leading route to deploying machine-learning-based clustering, classification and collaborative filtering algorithms on Hadoop, but these techniques are also supported by the R statistical programming language. Commercial vendors supporting or embedding machine-learning techniques include Alpine Data Labs, Birst, Causata, Lionsolver, Revolution Analytics and a growing list of others.


Oracle Cuts Big Data Appliance Down To Size

Inside IBM's Big Data, Hadoop Moves

MongoDB Upgrade Fills NoSQL Analytics Void

10Gen Enterprise Release Takes MongoDB Uptown

Will Microsoft's Hadoop Bring Big Data To Masses?

6 Big Data Advances: Some Might Be Giants

Hadoop Meets Near Real-Time Data

Big Data Analytics Masters Degrees: 20 Top Programs

Big Data's Surprising Uses: From Lady Gaga To CIA

13 Big Data Vendors To Watch In 2013

Big Data Talent War: 7 Ways To Win

Teradata Joins SQL-On-Hadoop Bandwagon

4 of 6
Comment  | 
Print  | 
More Insights
Newest First  |  Oldest First  |  Threaded View
How Enterprises Are Attacking the IT Security Enterprise
How Enterprises Are Attacking the IT Security Enterprise
To learn more about what organizations are doing to tackle attacks and threats we surveyed a group of 300 IT and infosec professionals to find out what their biggest IT security challenges are and what they're doing to defend against today's threats. Download the report to see what they're saying.
Register for InformationWeek Newsletters
White Papers
Current Issue
2017 State of the Cloud Report
As the use of public cloud becomes a given, IT leaders must navigate the transition and advocate for management tools or architectures that allow them to realize the benefits they seek. Download this report to explore the issues and how to best leverage the cloud moving forward.
Twitter Feed
InformationWeek Radio
Archived InformationWeek Radio
Join us for a roundup of the top stories on InformationWeek.com for the week of November 6, 2016. We'll be talking with the InformationWeek.com editors and correspondents who brought you the top stories of the week to get the "story behind the story."
Sponsored Live Streaming Video
Everything You've Been Told About Mobility Is Wrong
Attend this video symposium with Sean Wisdom, Global Director of Mobility Solutions, and learn about how you can harness powerful new products to mobilize your business potential.
Flash Poll