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Gartner's basic business rules for capitalizing on big data

Gartner's basic business rules for capitalizing on big data | Federal healthcare Big Data | Scoop.it
A breakthrough like big data comes around only once in a blue moon. Here are some basic business rules on what executives need to do to capitalize on it.

Via Adrian Carr, Tony Agresta
Bryan Borda's insight:

Excellent insights from Gartner.

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Adrian Carr's curator insight, April 25, 2013 10:00 AM

Doug Laney of Gartner continues to drive out the ghosts of "Big Data" and pin it's feet firmly to the ground (mixing metaphors ? - maybe).

A pragmatic approach to grounding objectives in business necessity, starting with internal data sources (not all Big Data projects start with collecting Tweets and blogs..) and then evolve.

 

I am turning into a big fan of Doug's.

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3 Reasons To Transition From Waterfall to Agile - MarkLogic

3 Reasons To Transition From Waterfall to Agile - MarkLogic | Federal healthcare Big Data | Scoop.it
Here are 3 key reasons why some of MarkLogic's leading customers like McGraw Hill, Dow Jones, and Conde Nast have chosen Agile over Waterfall

Via Adrian Carr
Bryan Borda's insight:

Excellent blog on Waterfall vs Agile development.  The choice is obvious if business and technology desire to share responsibility for success of critical projects (as they should!).

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Adrian Carr's curator insight, July 23, 2013 5:14 AM

Three solid reasons for using an Agile approach for projects especially in the Big Data environment.  This is characterised by the business often not knowing what they wanted in the first place which makes a Waterfall approach very risky.

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The Big Data open source tools

The Big Data open source tools | Federal healthcare Big Data | Scoop.it
The Big Data open source tools landscape is growing rapidly. Check it out here.

Via Adrian Carr
Bryan Borda's insight:

Talk about crowded markets!  How will you know which will survive and which will not?  The diagram title is a bit misleading, not all the solutions are open source tools.  However even those that are open source are NOT FREE! 

 

Look at longevity and enterprise customer base.  Look especially at those big data platforms who have customers using their solution in mission critical applications.  When serious make sure a thorough, competitive, apples to apples evaluation/proof of concept is conducted.

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Adrian Carr's curator insight, June 7, 2013 3:49 AM

Another diagram attempting to categorise all the software offerings within the Big data space.

This looks to be derived from the 451 Group diagram or similar at least.

There are few comments :

- These are not all Open Source

- Many of the offerings will span several groupings, what is important is where (functionally) they come from and where they are going

- Open Source does not equate to free...check out the profits of Red Hat in case you are confused.

- There are way too many companies here to survive so choose wisely.

(not sure why I had the urge to write 'Grasshopper' at the end of the last senetence but I controlled it :) )

Henry Pan's curator insight, June 8, 2013 10:43 AM

Who is going to be the top 3 tools?

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Gartner's basic business rules for capitalizing on big data

Gartner's basic business rules for capitalizing on big data | Federal healthcare Big Data | Scoop.it
A breakthrough like big data comes around only once in a blue moon. Here are some basic business rules on what executives need to do to capitalize on it.

Via Adrian Carr, Tony Agresta
Bryan Borda's insight:

Excellent insights from Gartner.

more...
Adrian Carr's curator insight, April 25, 2013 10:00 AM

Doug Laney of Gartner continues to drive out the ghosts of "Big Data" and pin it's feet firmly to the ground (mixing metaphors ? - maybe).

A pragmatic approach to grounding objectives in business necessity, starting with internal data sources (not all Big Data projects start with collecting Tweets and blogs..) and then evolve.

 

I am turning into a big fan of Doug's.

Rescooped by Bryan Borda from Big Data Technology, Semantics and Analytics
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What's the Scoop on Hadoop?

What's the Scoop on Hadoop? | Federal healthcare Big Data | Scoop.it
If you are an investor in the field of Big Data, you must have heard the terms “Big Data” and “Hadoop” a million times.  Big Data pundits use the terms interchangeably and conversations might lead you to believe that...

Via Tony Agresta
Bryan Borda's insight:

Excellent information on advantages to using NoSQL technology with a Hadoop infrastructure.  Take advantage of the existing Hadoop environment by adding powerful NoSQL features to enhance the value.

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Tony Agresta's curator insight, July 17, 2013 5:34 PM

"Hadoop is not great for low latency or ad-hoc analysis and it’s terrible for real-time analytics."


In a webcast today with Matt Aslett from 451 Research and Justin Makeig from MarkLogic, a wealth of inforrmation was presented about Hadoop including how it's used today and how MarkLogic extends Hadoop.  When the video becomes available, I'll post it but in the meantime, the quote from the Forbes article echoes what the speakers discussed today.


Today, Hadoop is used to store, process and integrate massive amounts of structured and unstructured data and is typically part of a database architecture that may include relational databases, NoSQL, Search and even Graph Databases.  Organizations can bulk load data into the Hadoop Distributed File System (HDFS) and process it with MapReduce.   Yarn is a  technology that's starting to gain traction enabling multiple applications to run on top of HDFS and process data in many ways. But it's still early stage.


What's missing?  Real Time Applications.  That's an understatement since reliability and security have also been question marks as well as limited support for SQL based analytics.   Complex configuration makes it difficult to apply Hadoop.


MarkLogic allows users to deploy an Enterprise NoSQL database into an existing Hadoop implementation and offers many advantages including:


  • Real time access to your data
  • Less data movement
  • Mixed workloads within the same infrastructure
  • Cost effective long term storage
  • The ability to leverage your existing infrastructure


Since all of your MarkLogic data can be stored in HDFS including indexes, you can combine local storage for active, real time results with lower cost tiered storage (HDFS) for data that's less relevant or needs additional processing.  MarkLogic allows you to partition your data, rebalance and migrate partitioned data interactively.


What does this mean for you?  You can optimize costs, performance and availability while also satisfying the needs of the business in the form of real time analytics, alerting and enterprise search. You can take data "off line" and then bring it back instantly since it's already indexed.  You can still process your data using batch programs in Hadoop but now all of this is done in a shared infrastructure. 


To learn more about MarkLogic and Hadoop, visit this Resource Center


When the video is live, I'll send a link out.



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Data Analysis and Unstructured Data: Expanding Business Intelligence (BI) by Thinking Outside of the Box - Zunia.org

Data Analysis and Unstructured Data: Expanding Business Intelligence (BI) by Thinking Outside of the Box - Zunia.org | Federal healthcare Big Data | Scoop.it

Via Tony Agresta
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Tony Agresta's curator insight, April 8, 2013 3:22 PM

New forms of business intelligence incorporate both structured and unstructured data into your analysis.   Where does this apply today?  Customer service, intelligence analysis in government, fraud analysis in financial services, healthcare, consumer packaged goods, retail and other markets can benefit from this approach.  The open web provides organizations with limitless data containing valuable information on sentiment, people, events, employers, relationships and more.   The ability to extract meaning from unstructured sources combined with structured data yields new insights that can be used to improve decisions. 

 

Let's take a look at healthcare, for example.

 

In an article by Dennis Amorosano entitled "Unstructured data a common hurdle to achieving guidelines", Mr. Amorosano writes "... of the 1.2 billion clinical documents produced in the United States each year, approximately 60 percent contain valuable information trapped in unstructured documents that are unavailable for clinical use, quality measurement and data mining. These paper documents have until now been the natural byproduct of most hospital workflows, as healthcare is one of the most document-intensive industries."

 

Forbes published an article last year entitled "The Next Revolution in Healthcare"  (http://www.forbes.com/sites/singularity/2012/10/01/the-next-revolution-in-healthcare/) in which the author points out that the best healthcare institutions in the world still rely heavily on calculating risk to patients using clinical data.  At the same time "the real tragedy is that the information needed to properly assess the patient’s risk and determine treatment is available in the clinician’s notes, but without the proper tools the knowledge remains unavailable and hence, unused."

 

The good news is that new analytic solutions are available that leverage both forms of data.   BI connectivity brings the power of familiar Business tools to your applications that include unstructured data. Some of the benefits to this approach include:

 

  • Combining BI and NoSQL provides capabilities not available using relational stores and EDWs - real-time analysis and extended query features.
  • BI tools layer on top of NoSQL databases that use sophisticated security models to protect sensitive data. Users see only the information for which they have permissions.
  • Analysts can learn faster using data discovery tools that allow for rapid investigation of both unstructured and structured data within the same application.  A more complete view of your analysis offers tremendous advantages in patient diagnosis, claims analysis and personalized care.

 

To learn more about how analytics technology is working with Enterprise NoSQL Databases ideally suited to ingest, store, search and analyze all types of data, you can visit this page:

 

http://www.marklogic.com/what-is-marklogic/analytics-business-intelligence/

 

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If I haven't heard of it it's probably NoSQL! | Bloor

It's all too easy to think that all noSQL vendors fall into the same camp. MarkLogic is a notable exception.

Via Tony Agresta
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Tony Agresta's curator insight, February 13, 2013 6:03 AM

Relevant insights from Philip Howard at the Bloor Group about the NoSQL market.