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Big Data Technology, Semantics and Analytics
Trends, success and applications for big data including the use of semantic technology
Curated by Tony Agresta
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RDF 101 - Cambridge Semantics

RDF 101 - Cambridge Semantics | Big Data Technology, Semantics and Analytics | Scoop.it
Semantic University tutorial and introduction to RDF.
Tony Agresta's insight:

This post is a bit technical but recommending reading since it represents a one of the most important aspects in data science today, the ability to discern meaning from unstructured data. 


To truly appreciate the significance of this technology, consider the following questions -  Since over 80% of the data being created today is unstructured in forms that include text, videos, images, documents, and more, how can organizations interpret the meaning behind this data?   How can they pull out the facts in the data and show relationships between those facts leading to new insights?

 

This post provides you with the foundation on how semantic processing works.   Cutting to the chase, the technologies are referred to as RDF (Resource Description Framework), SPARQL and OWL. They allow us to create underlying data models that understand relationships in unstructured data, even across web sites, document repositories and disparate applications like Facebook and LinkedIn.

 

These data models store data that has properties extracted from the unstructured data.  Consider the following sentence:   "The Monkeys are destroying Tom's garden."  Semantic processing of this text would deconstruct the sentence identifying the subject, object and predicate while also building relationships between the three.  The subject is "monkeys" and they are taking an action on "the garden". The garden is therefore the object and the predicate is "destroying".  

 

Most importantly, there is a connection made between the monkeys and the garden allowing us to show relationships between specific facts pulled from text.   How can this help us? 

 

Assume for a second you’re working for a government agency tracking a suspicious person who exists on a watch list?   Crawling the web looking for that person's name is one way to identify additional information about the person.   Technology to do this exists today.  When the name is detected, identifying relationships between the person being investigated and other subjects (or objects in the text) can lead you to new people that may also be of interest.  For examples if Sam is on the watch list a sentence like this would be of interest:  "Sam works with Steve at ABC Home Builders Corp.”  Relationships between the suspect (Sam) and someone new in the investigation (Steve) could be identified.   The fact that they both work for the same employer allows analysts to connect the subjects through this employer.

 

These interesting facts help investigators make connections within e-mail, phone conversations, in house data and other sources, all of which can be displayed visually in a graph to show the subjects and how they are linked. 

 

Data models to store, search and analyze this data will become one of the primary tools to interpret massive amounts of data being collected today.  This technology allows computers to understand relationships in unstructured data and display those relationships to analysts in the form of visual diagrams that clearly show connections to other data including phone calls, events, accounts, and more.  The implications of this extend far beyond counter terrorism to include social networking, marketing, fraud, cyber security and sales to name a few.


We are at an inflexion point in big data – data stored in silos can now be consolidated with external data from the open web.  Most importantly, the unstructured data can be interpreted as we form connections that are integral in understanding how things are related to each other.  Data visualization technology is the vehicle to display those connections allowing analysts to explore any form of data in a single application. 


Learn more about this technology and other advances in Enterprise NoSQL here.


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MarkLogic SolutionTracks

MarkLogic SolutionTracks | Big Data Technology, Semantics and Analytics | Scoop.it
Discover how MarkLogic NoSQL database solutions help you make better decisions,
faster, with MarkLogic SolutionTracks—a series of brief, easy-to-follow, whiteboard tutorials.
Tony Agresta's insight:

MarkLogic Solution Tracks - Learn about data consolidation, search & discovery, content delivery and more.

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NSA collecting phone records of millions of Verizon customers daily

NSA collecting phone records of millions of Verizon customers daily | Big Data Technology, Semantics and Analytics | Scoop.it
Exclusive: Top secret court order requiring Verizon to hand over all call data shows scale of domestic surveillance under Obama administration
Tony Agresta's insight:

In my opinion, this demonstrates one of the most important aspects of big data analysis and should continue.    Call data, including outbound call numbers, inbound call numbers, duration of call, start time and end time, are vital pieces of information necessary to analyze and protect us.  US lives are at risk.  The article by Glenn Greennwald in The Guardian states:

 

"Such metadata is what the US government has long attempted to obtain in order to discover an individual's network of associations and communication patterns. The request for the bulk collection of all Verizon domestic telephone records indicates that the agency is continuing some version of the data-mining program begun by the Bush administration in the immediate aftermath of the 9/11 attack."

 

Let's get to the heart of the matter.   This type of big data analysis has prevented attacks and has proven to work.   At this moment, all of the facts of these investigations are not disclosed (and many classified examples will probably never be revealed) but many news outlets are reporting that a planned bomb attack on the NY subway was diverted because of phone and e-mail intercept and analysis. 

 

For intelligence analysts to do this accurately and completely they need to analyze the haystack of data represented by e-mail, phone and other forms of communication.   For example, if an e-mail from someone is intercepted because that person is corresponding about bomb recipes, our government should have access to the calls this person made and received. They should be allowed to analyze ALL of the connections between other callers to discern whether or not a network of clandestine activity exists.  If warranted, our government should be able to look at the content of the unstructured data to determine if there are other people, events or places referenced in the text.  Initiating these investigations by analyzing all e-mail traffic or all phone calls made to known or suspected terrorists protects everyone of us.

 

Techniques and processes to ingest, search and manage massive amounts of data like phone records and e-mail traffic are being used today. This should not surprise anyone.  Connecting the dots between caller metadata and known or suspected terrorists is one very effective way to maintain the safety of US citizens.   If this means the NSA needs to look more closely at other calls that suspects have made, so be it.  These preventative measures are in place to safeguard our freedom and prevent lives from being lost.   Haven't we seen enough of that?

 


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The Big Data open source tools

The Big Data open source tools | Big Data Technology, Semantics and Analytics | Scoop.it
The Big Data open source tools landscape is growing rapidly. Check it out here.

Via Adrian Carr
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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 :) )

Bryan Borda's curator insight, June 7, 2013 11:04 AM

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.

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

Who is going to be the top 3 tools?

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Content Marketing: A Game of Skill #Infographic

Content Marketing: A Game of Skill #Infographic | Big Data Technology, Semantics and Analytics | Scoop.it
After youve written a major piece of content, do you know how to market it effectively? Its vital that you do.
Tony Agresta's insight:

Clearly not a big data topic but I thought I would post this one anyway.   It's a basic set of channels for your content that we should always keep in mind .

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Adrian Carr's curator insight, June 7, 2013 1:23 PM

With the channel being transparent and the comsumer being fickle, publishers need to work harder to get value from their content.

Right content, right time, right device, right place, right price....

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Big Data Analytics Will Help Us to Explore the Universe

Big Data Analytics Will Help Us to Explore the Universe | Big Data Technology, Semantics and Analytics | Scoop.it
Harnessing data from 500,000 antennas, scientists are building a system to measure radio signals from unexplored parts of the universe.
Tony Agresta's insight:

Pattern recognition, automated learning and data filtering will be applied to tackle this really big data problem.   Read about how SKA helps us explore the universe. 


"It's that building SKA's systems, much of the technology for which doesn't exist today, is the ultimate big data challenge. Each day, 500,000 antennas will pull in a deluge of radio signals -- an unprecedented 14 exabytes of data -- from outer space. That's double the amount of data the Internet produces daily."

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Visualization startup Datahero opens its doors and delivers data analysis for the masses

Visualization startup Datahero opens its doors and delivers data analysis for the masses | Big Data Technology, Semantics and Analytics | Scoop.it
A year after launching, data-analysis-for-the-masses startup Datahero is finally opening its doors to the public. All in all, it delivers on its promise with a service that’s both intelligent and intuitive.
Tony Agresta's insight:

One of the primary challenges with data discovery and visualization technology is the process of exploring and uncovering meaningful insights in your data.  It takes time.  To the extent this can be automated by matching visualization types to the data in support of uncovering hidden meaning, users will find these tools more valuable.  It won't always be perfect but if the automated part of data visualization begins to focus your attention on a slice of the data, the analyst gains an advantage.   Consider it a starting point to continue the interactive side of data discovery which may include filtering the data, integrating other sources, broadcasting results from one chart to another or sharing results with other analysts that may provide additional insights.  It sounds like Chart Magic may have some of this built in. 

 


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Can You Pass the ACID Test? - MarkLogic

Can You Pass the ACID Test? - MarkLogic | Big Data Technology, Semantics and Analytics | Scoop.it
Visit MarkLogic.com to read Can You Pass the ACID Test?.
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How to harness Big Data in motion | TechRepublic

How to harness Big Data in motion | TechRepublic | Big Data Technology, Semantics and Analytics | Scoop.it
Here are some of the technologies that companies need to look at if they want real-time big data analytics.
Tony Agresta's insight:

The premise of this article is very true.   Harnessing big data in motion is critical in many applications. Hadoop's parallel processing of large sets of data is not the answer today.   Relatively static data in the Hadoop Distributed File System processed in bulk does not meet the demands of mission critical real time applications in either government or commercial sectors. And the article goes on to indicate there are solutions to this problem.

 

But the article fails to reference MarkLogic who has been doing this for over a decade.   Today, in concert with Hadoop, data can be processed in bulk and streamed, in real time, into MarkLogic.   Alternatively, data can be ingested directly into MarkLogic.   Since indexes (many) are derived in real time and stored in both memory and on disk, the data is available instantly through enterprise search, business intelligence tools or customer applications.

 

Applications for big data in motion are diverse and include homeland defense, derivatives trading to assess and manage risk, access to content in support or new digital media products, real time analytics on cargo shipments and a host of customer relationship management applications including data streaming in from the open web.

 

Buyers should look for technology that is "enterprise grade", low risk to your organization, powerful enough to meet the growing data demands and customer expectations.  The ability to read, write, backup and recover big data within a computing architecture that provides real time, high availability should not be underestimated.

 

Adam Fowler does a great job at describing a very important aspect of Enterprise NoSQL here (ACID Transactions):


http://adamfowlerml.wordpress.com/2013/01/25/true-acid-compliance/


Adam also provides some research he collected on why users are choosing to use NoSQL databases  (and not). Notice that streaming data and data volumes are two of the top three reasons in support of NoSQL


http://adamfowlerml.wordpress.com/2013/01/04/why-use-a-nosql-database-and-why-not/







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Big Data Star System - Infographic showing players and relative impact of Big Data on their business

Big Data Star System - Infographic showing players and relative impact of Big Data on their business | Big Data Technology, Semantics and Analytics | Scoop.it

Click here to edit the title


Via Adrian Carr
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Adrian Carr's curator insight, May 16, 2013 5:29 AM

This is a great visualisation of the wikibon analysis of who is doing what in "big data".

It separatres software, hardware and services and shows relative size % of Big Data revenuw as a percentage of total.

Nice.

I love Infographics, definitely the way my small brain learns..

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MarkLogic 7 Vision: World-Class Triple Store and World-Beating Information Store - semanticweb.com

MarkLogic 7 Vision: World-Class Triple Store and World-Beating Information Store - semanticweb.com | Big Data Technology, Semantics and Analytics | Scoop.it
MarkLogic 7 Vision: World-Class Triple Store and World-Beating Information Store
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MarkLogic Search and Discovery Whiteboard

Understand the key challenges faced by enterprises today when delivering search and discovery applications to end users handling Big Data, and, discover how MarkLogic Enterprise NoSQL solutions overcome those challenges.

 


Via Dominic Spitz, Adrian Carr
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Adrian Carr's curator insight, May 10, 2013 11:26 AM

This is a great beginers guide to NoSQL in general and what Enterprise NoSQL means.

Short. Sweet and it starts from what we know...RDBMS !!

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The Many Uses for Searchable Databases: Video

The Many Uses for Searchable Databases: Video | Big Data Technology, Semantics and Analytics | Scoop.it
MarkLogic CEO Gary Bloom discusses the uses for searchable databases with Cory Johnson on Bloomberg Television's "Bloomberg West." (Source: Bloomberg)
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U.S. National Archives Launches Founders Online Website on MarkLogic(R)

U.S. National Archives Launches Founders Online Website on MarkLogic(R) | Big Data Technology, Semantics and Analytics | Scoop.it
SAN CARLOS, CA--(Marketwired - Jun 13, 2013) - MarkLogic Corporation, provider of the enterprise NoSQL (not only SQL) database platform, announced that the Founders Online website, publically launched today by the National Archives and the...
Tony Agresta's insight:

A fantastic database of historical documents written by America's Founders just became available on line.  Here's a link:


Founders OnLine


I was searching through it and found an interesting plan written by Brigadier General Nathanael Greene to George Washington in February of 1776.  Here's an excerpt.


"In Obedience to Your Excellency’s Orders, we have considered the Matters referred to Us, & beg leave to recommend the following Signals to be given from Roxbury, in Case of any Movement of The Enemy to Distress our People at Dorchester Hill"


"We further beg leave to recommend to Yr Excellency That should it appear from the Signals at Roxbury or in any other way, that an Attack may be made upon Boston, with good probability of Success; We Recommend, that four Thousand Men Embark at the Mouth of Cambridge River.1 Two Thousand of Them to be Furnish’d from Cambridge, & Two Thousand from Prospect, & Winter Hill. One Thousand from each of those Hills; The Two Thousand from Cambridge to be Commanded By Brigadier Genl Sullivan & The Other Two Thousand By Brigr Genl Greene, The whole to be Commanded By Major General Putnam."


You can search these documents in any number of ways. There's a full explanation of search tips you can access directly from the site and there's a great UI that lets users search by authors, recipients, periods and dates.   This is well worth looking into...all built on MarkLogic.


Link to Search Tips





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Updated Database Landscape map – June 2013 — Too much information

Updated Database Landscape map – June 2013 — Too much information | Big Data Technology, Semantics and Analytics | Scoop.it
Tony Agresta's insight:


MarkLogic is uniquely positioned on this database landscape map.    Here's what makes the position very different from other vendors:


1.  Search - MarkLogic is directly connected to all the major enterprise search vendors.   Recent recognition of this was confirmed by Gartner in its Enterprise Search Magic Quadrant.   Notice that other NoSQL technologies are nowhere close to this connection point.


2.  General Purpose - MarkLogic provides an enterprise NoSQL database and Application Services and Search.   With support for many development languages, REST and JAVA APIs, MarkLogic has clear links to SAP, Enterprise DB and a host of other database providers.


3.   Graph and Document - MarkLogic has long been recognized as a document store and used widely all over the world for this purpose.  Notice the subtle connection to Graph as well connecting MarkLogic to other vendors in this space like Neo4J.  MarkLogic 7 promises to deliver a world class triple store to index subjects, predicates and objects in XML documents or load other triples through the MarkLogic Content Pump.  For the first time, the only Enterprise NoSQL technology with search will include semantics.  Updated APIs and support for SPARQL are part of this release.


4.  Big Tables - MarkLogic's ability to handle big data has long been known.  The olive green line is designated for vendors like MarkLogic, Cassandra, HBASE, etc.   MarkLogic's partnership with Intel for Distribution of Apache Hadoop and the fact that MarkLogic ships with Hadoop connectors provide additional confirmation for this position.


5.   Key Value Stores - Data can be stored as keys without a database schema required lby relational databases.  In MarkLogic's case, huge quantities of data can be indexed in real time with data stored in memory and disk making search results instant and complete.   After a recent analysis of over 50+ MarkLogic customers, the abilty to quickly get up and running and deliver new information products to market was a business driver they mentioned over and over again.


The fact is, no one else on the list has all of these qualities.   Because of this unique position, visually you see MarkLogic distanced from other clusters or long lists of technology vendors.  


To learn more, you can go to MarkLogic Resources.






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Graph Analysis Powers the Social and Semantic Spheres of Big Data — IBMdatamag.com

Graph Analysis Powers the Social and Semantic Spheres of Big Data — IBMdatamag.com | Big Data Technology, Semantics and Analytics | Scoop.it
Why predictive modeling of human behavior demands an end-to-end, low-latency database architecture
Tony Agresta's insight:



Here are some key points from the article in addition to some insights about graph analysis and big data:

 

  • Semantic graphs map relationships among words, concepts and other constructs in the human language allowing for unstructured data to be used in a graph showing important connections.
  • Graph analysis is not new.   It has been used as a form of data visualization to explore connections and identify patterns and relationship that would otherwise have gone undetected.
  • Some vendors have taken their graph capabilities to new levels. For example, Centrifuge Systems allows users to draw the graphs, search the graph space, interact with charts and display important measures about the graph network.   Analysts can easily pinpoint portions of the graph that require additional analysis.  Hotspots of interesting activity jump out from the graph based on the number of connections and important performance measures.
  • While social graphs may be the most popular, this approach is especially useful in detecting fraud networks, cyber data breaches, terrorist activity and more. 
  • One of the most important points is that graphs can incorporate diverse streams of big data including both structured and unstructured.  Imagine the ability to analyze banking wire transfer data in the same graph with unstructured data that includes names, locations, and employers - intelligence that has been discovered through the semantic processing of unstructured data.   That's a powerful combination of sources linking data from the open web with transactional information. When done in real-time, this can be used in anti-money laundering, fraud prevention and homeland defense.
  • "Data scientists explicitly build semantic graph models as ontologies, taxonomies, thesauri, and topic maps using tools that implement standards such as the W3C-developed Resource Description Framework (RDF)."

 

While this may be beyond the scope of many NoSQL and Hadoop databases, MarkLogic 7 is embracing triple stores as they continue to innovate on their Enterprise NoSQL approach. No one else has values, triple store data derived from semantic processing and documents with real time indexing and search - The bar for Enterprise  NoSQL is about to be raised again.

 

You can read more about this on Semantic Web:

 

http://semanticweb.com/marklogic-7-vision-world-class-triple-store-and-world-beating-information-store_b37123








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Maps BI | Introducing Our Data Visualization Series

Tony Agresta's insight:

How do you solve information problems?   Data visualization provides clarity to big data challenges.  "The Beauty of Data Visualization" shows examples of big data collected from Facebook, news articles, miltary spend, nutritional supplement usage and more.   David McCandless does a very nice job pointing out the significant aspects of each visualization.  He clearly articulates why data visualizations are so important at a time when massive volumes of data require new forms of analysis.

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Big Data Techniques | SmartData Collective

Big Data Techniques | SmartData Collective | Big Data Technology, Semantics and Analytics | Scoop.it
Recent trends have contributed to Big Data's growth -- namely, volume, velocity, and variety.

Via Adrian Carr
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Adrian Carr's curator insight, June 4, 2013 10:22 AM

Guess what, another Big Data Infographic.

Another good one too.

It shows the convergence of several IT trends/developments which have a bearing on Big Data.  It also demonstrates that currently only a small percentage of data is tagged or analysed. so far.

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Wearable technology 'will be powerful for big data analytics' says Rackspace

Wearable technology 'will be powerful for big data analytics' says Rackspace | Big Data Technology, Semantics and Analytics | Scoop.it
Technology will allow firms like Nike to mine a rich new seam of consumer data
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The human-safety side of big data

The human-safety side of big data | Big Data Technology, Semantics and Analytics | Scoop.it
How the Canadian operations of an international construction company used data analytics to drastically
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Beyond Enterprise Search...

Searching through all your content is fine - until you get a mountain of it with similar content, differentiated only by context. Then you'll need to understand the meaning within the content. In t...
Tony Agresta's insight:

A  must read from Adam Fowler.

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MarkLogic Enhances Enterprise NoSQL Database Applications & Analytic Solutions With Intel(R) Distribution for Apache Hadoop Software

MarkLogic Enhances Enterprise NoSQL Database Applications & Analytic Solutions With Intel(R) Distribution for Apache Hadoop Software | Big Data Technology, Semantics and Analytics | Scoop.it
SANTA CLARA, CA--(Marketwire - Feb 26, 2013) - Strata Conference - To ensure that organizations are able to securely make use of their growing

Via Dominic Spitz
Tony Agresta's insight:

With this announcement, Enterprise Hadoop meets Enterprise NoSQL including certification and testing of a known configuration, integrated support, enterprise management tools and performance & security enhancements.  To be specific, Apache Hadoop can take full advantage of the advanced processor capabilities such as AES-NI and SSE.   Energy efficient servers for scale-out architectures are enabled with Xeon E5.   Faster data ingest, export, perfromance and reliability support SSD big data usage models.    Most importantly, enterprise hadoop complements Marklogic in areas such as operational applications, real time decision making, distributed indexes and enterprise search.


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Dominic Spitz's curator insight, February 26, 2013 12:18 PM

To ensure that organizations are able to securely make use of their growing volumes of data MarkLogic Corporation today announced that it will deliver an enterprise-grade application and analytics software solution to unlock the power of Big Data based on the Intel® Distribution for Apache Hadoop software (Intel® Distribution). The Intel Distribution will work seamlessly with the MarkLogic Enterprise NoSQL (not only SQL) database to enable real-time transactional and analytic applications.


Read More At IBD: http://news.investors.com/newsfeed-marketwire/022613-141442300-marklogic-enhances-enterprise-nosql-database-applications-and-analytic-solutions-with-intelr-distribution-for-apache-hadoop-software.aspx#ixzz2M1i05XXF
Adam Fowler's curator insight, May 3, 2013 9:04 AM

Hadoop is increasingly important for cheap data archival and batch analysis. Read why using this with MarkLogic is of benefit.

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Imagine what you could do if you had access to all your data.......

Imagine what you could do if you had access to all your data....... | Big Data Technology, Semantics and Analytics | Scoop.it
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Facebook Is About To Launch A Huge Play In 'Big Data' Analytics

Facebook Is About To Launch A Huge Play In 'Big Data' Analytics | Big Data Technology, Semantics and Analytics | Scoop.it
Facebook has data on $1 trillion off-line purchases.
Tony Agresta's insight:

Enhancing your data with third party information has significant benefits.  For one, profiles of your customers or prospects become much more vivid.  In years past, enhancement was limited to adding demographic, socio-economic and lifestyle attributes for the geographic areas in which the customer lived.    Today, the detailed information specific to the information is extraordinary and growing all the time.  Targeted advertising becomes much more precise.  Using the enhanced data as inputs into predictive models can improve the accuracy of the models. 

Real time access to data helps both government and commercial organizations.  Access to public records data on personal property owned, places of residence and employment history are often used in investigations analysis.  This could lead to identifying related individuals comprising a network of activity. 


Big data includes more than just your internal data.   Third party data can play a significant role in your big data targeting strategy.  One word of caution - when adding third party data, look closely at whether or not the data is specific to the person or inferred about the person based on similar profiles or models.   Typically vendors have this for each data characteristic and will provide it at the macro level.  Understanding how the inferred data is added will be important as well.  

If you’re trying to decide how significant a role the enhanced data can play in your targeting strategy, you could always enhance a sample, test the results and see which of the variables has some explanatory power before you enhance massive amounts of data and burn through your budget.


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MarkLogic points up its Hadoop big-data future | ZDNet

MarkLogic points up its Hadoop big-data future | ZDNet | Big Data Technology, Semantics and Analytics | Scoop.it
Open-source distributed computing software Hadoop features strongly in the plans of NoSQL database company MarkLogic.
Tony Agresta's insight:

Ths article includes important information about the benefits of tiered storage in managing Big Data as well as MarkLogic's relationship with Intel.   Layering your data across different storage tiers provides flexibility, performance gains and cost management benefits.  Service levels can be optimized. 

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