04 March 2014
Learn fundamental usage of IBM's Big SQL technology for Hadoop over HBase by creating tables and examining ways to load data. Follow a basic storyline of migrating a relational table to HBase using Big SQL.
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InfoSphere Streams Quick Start Edition puts real-time analytic processing at your fingertips. Now you can analyze massive data volumes quickly (even in real time) and turn data into insight you can use to make better decisions. InfoSphere Streams can quickly ingest, analyze, and correlate information as it arrives from thousands of real-time sources. Try out the newest stream computing software — free to download, quick to start.
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- Using IBM Big SQL over HBase, Part 2: Query
handling and business intelligence
Learn about query handling and how to connect to Big SQL via JDBC to run business intelligence and reporting tools such as BIRT or Cognos.
- Process small, compressed files in Hadoop using
Discover how to use CombineFileInputFormat within the MapReduce framework to decouple the amount of data a Mapper consumes from the block size of the files in HDFS.
- Process complex text for information
Even the basic task of picking out specific words, phrases, or ideas from raw text is challenging. Learn how AQL and InfoSphere BigInsights can help you process text into meaningful data that can be converted to usable information.
- Extract meaningful statistical measures from
data in JSON using R
- Create MapReduce queries to process particular
types of data
With easy-to-follow patterns and examples, learn how to write queries to process the exact information you need and apply these to your own MapReduce solutions.
- BigSheets for the common man
See how BigSheets technology takes your big data and makes it easy to browse, read, and identify. Learn how to turn analyzed information into visualized information that can then be integrated into future data processing tasks.
- Apply SPSS analytics technology to big
Add SPSS to IBM Netezza, InfoSphere BigInsights, and InfoSphere Streams to get powerful analytics tools for big data at scale, in batch or real time.
- Developing IBM PureData System for Hadoop
applications with the Eclipse IDE
Learn how to set up OpenVPN an open source implementation of VPN server and VPN client software published under the GNU General Public License on a connected client to enable secure access to the Hadoop cluster.
- Big data architecture and patterns, Part
Using patterns based on three fraud-detection scenarios, learn how a big data solution can address the complexity of analyzing large volumes of varied data across many data sources.
- Building flexible apps from big data
InfoSphere BigInsights makes it easier to manage and run big data jobs through a simple REST API and Jaql interface to Hadoop. Examine how these systems work together to give you a rich basis for capturing data and provide an interface to get the information back out again.
- The world of interactive media systems and
The all-digital media world allows for a much wider range of artist and creative developer participation, including the consumer as an interactive participant. Anyone who has a creative mind, some computer skills, and patience can join this new creative digital culture.
… you missed out on having experts lead you through hands-on exercises about big data services in Codename: BlueMix, but you can get valuable how-to information in these lab materials about the MapReduce service and Hadoop on the cloud using InfoSphere BigInsights (PDF) (sign-in required).
As the world becomes more interconnected and more data is gathered, the opportunity for gaffes in using that data increases dramatically. David Corrigan describes some of the steps an organization should take in securing and analyzing big data to ensure they can regain and retain confidence.
(10:32) | Watch the video
Get practical guidance for many common InfoSphere BigInsights issues and use this knowledge to improve the value of your Big Data implementation. Get tips from leading experts on how to improve your InfoSphere BigInsights experience.
IBM big data platform capabilities
Hadoop-based analytics: Store any data type in the low-cost, scalable Hadoop engine to reduce the cost of processing and analyzing massive volumes of data.
Stream computing: Continuously analyze massive volumes of streaming data with sub-millisecond response times to take action in real time.
Text analytics: Analyze textual content to uncover hidden meaning and insight in unstructured information.
Accelerators: Deploy pre-packaged analytical and industry-specific software modules to extract value from big data.
Application development: Develop text analytics applications with toolkits and tools, including an extensive library of extractors you can customize and extend.