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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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Future Big Data: How Analytics Will Impact NFL | SiliconANGLE

Future Big Data: How Analytics Will Impact NFL | SiliconANGLE | Big Data Technology, Semantics and Analytics | Scoop.it
Tony Agresta's insight:

The well-known book and movie documenting the success of Billy Beane and the Oakland A's is probably the best example of using data to provide a completive advantage in sports. 

 

Analyzing player tendencies like pitch sequences, at-bats and defensive moves are interesting.  When you connect them to other players and teams, they become even more interesting and can lead to sets of rules that make up how you coach every detail.  Expectations and patterns taught to players provide them with guidelines on how to react and increase the odds of winning.

 

Could this be applied to football?  It seems like that's what watching film of past games is all about.  If a team could tag the plays with meaningful content about the outcome, the situation, the players on the field, the time, location, weather and then make it discoverable, coaches could identify patterns and tendencies that were previously undetected. 

 

There are probably some other applications of big data in football.  Analyzing new recruits by looking at unstructured data from the open web is one.  Real time twitter streams during game time linked in advertising is likely another.  

 

So who wins?   49ers, 27-24.  Sorry Ray Lewis. Just one ring for you.

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AllAnalytics - Seth Grimes - Scouting the Next Frontiers for 'Unstructured' Data

AllAnalytics - Seth Grimes - Scouting the Next Frontiers for 'Unstructured' Data | Big Data Technology, Semantics and Analytics | Scoop.it
Beyond text, lots of work remains in getting a handle on unstructured data.

Via M. Edward (Ed) Borasky, Bryan St.Laurent
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With MarkLogic Search Technology, Factiva Enables Standardized Search And Improved Experiences Across Dow Jones Digital Network, - semanticweb.com

With MarkLogic Search Technology, Factiva Enables Standardized Search And Improved Experiences Across Dow Jones Digital Network, - semanticweb.com | Big Data Technology, Semantics and Analytics | Scoop.it
With MarkLogic Search Technology, Factiva Enables Standardized Search And Improved Experiences Across Dow Jones Digital Network,
Tony Agresta's insight:

Let's not forget that enterprise search is often a critical component in most big data applications.  Users evaluating NoSQL technology should investigate the degree to which the technology supports search.

 

Here are some of the benefits that Dow Jones found in the MarkLogic Enterprise approach:

 

  • One powerful, unified search platform to service the search needs of both consumer and enterprise customers.
  • The enhancements they make will be scalable and efficiently accessible to everyone.
  • Support for dynamic taxonomy coding of content. For example, the same person  (Barack Obama and President Obama) or company (BP and British Petroleum) may be referred to and discovered without requiring the user to specify all variations of what they are seeking.
  • Improved ability to use "proximity of search" elements allowing users to search for words that may be in close proximity to others words thereby increasing the power and relevance of the search results.
  • Fast response to very precise search
  • Personalized search that customizes results using search history patterns and interests
  • Narrowing the search result set to improve direct access to relevant content within the structured or unstructured data, 
  • Time savings through easy detection of related sources of content

 

If this topic interests you, I would suggest looking at the Search capabilities in MarkLogic 6. You can find them here:  Search Developer Guide.   Some of the guide is technical but a lot of it summarizes the types of applications you can build with MarkLogic.  It will provide you with ideas on what you can include in your search applications.

 

 


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Convergence of technologies will spur big data projects in 2013 -- GCN

Convergence of technologies will spur big data projects in 2013 -- GCN | Big Data Technology, Semantics and Analytics | Scoop.it
Cloud computing, Hadoop, NoSQL databases and semantic technology are related layers that will allow agencies to derive more value from big data applications.
Tony Agresta's insight:

“This is the year that government agencies will see that Hadoop handles distribution of computing tasks well, but doesn’t give real-time, immediate response to the user that most of the applications actually require. Agencies will see that NoSQL databases come into play here, giving responses back to the user in real time"  Chris Biow, CTO Federal at MarkLogic

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Is 3D Visualization the Next Step For Big Data? | Innovation Insights | Wired.com

Is 3D Visualization the Next Step For Big Data? | Innovation Insights | Wired.com | Big Data Technology, Semantics and Analytics | Scoop.it
Big Data is getting really big. Image: BBVAtech/Flickr With the big data explosion in full steam, companies across multiple industries are resourcefull
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Webcast - Everyone's A Publisher | TechRepublic & MarkLogic

Webcast - Everyone's A Publisher | TechRepublic & MarkLogic | Big Data Technology, Semantics and Analytics | Scoop.it

Wednesday, January 23, 2013 - 11:00 am ET / 8:00 am PT / 16:00 GMT

 


Via Dominic Spitz
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Dominic Spitz's curator insight, January 16, 2013 6:17 AM

Your customers are being inundated with content all day long from companies like yours that are trying to engage. How do you make sure that the most relevant content is in their inbox? How do your marketing and sales teams keep up with content requests?

In this 60-minute webinar, join MarkLogic colleagues Matt Turner, CTO Media Solutions and Diane Burley, Chief Content Specialist. Both Turner and Burley have come from the break-neck world of media - where deadlines are yesterday and updates are constant.

For marketers who need to get consistent, contextually relevant messages across all possible touch points, they need the flexibility of an agile brand management platform. Take a page from some of the world's largest media companies - and build a dynamic publishing platform - powered by MarkLogic.

Please be sure to join us and learn how to:

Ensure a consistent brand experienceGain efficiencies in the creation of content

 

Leverage content components across channels

 

"Apply the learnings" on the content consumption

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Intelligence center develops Biometrically Enabled Intelligence to support warfighter | Article | The United States Army

Intelligence center develops Biometrically Enabled Intelligence to support warfighter | Article | The United States Army | Big Data Technology, Semantics and Analytics | Scoop.it
With high-tech gadgets that scan a person's iris and take fingerprints, the National Ground Intelligence Center uses forensic science, known as Biometrically Enabled Intelligence, to support the warfighter.

Via R.J. Caster
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R.J. Caster's curator insight, January 10, 2013 9:38 AM

The ability to gather and use unstructured data in real-time saves money, and saves lives.  

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Finding structure for unstructured data - FCW.com

Finding structure for unstructured data - FCW.com | Big Data Technology, Semantics and Analytics | Scoop.it
Fort Mills Times
Finding structure for unstructured data
FCW.com
If hype equaled performance, big data and cloud computing would already be unmatched cost-cutting, efficiency-increasing, bottom line-building tools in the federal space.

Via Toni Sánchez
Tony Agresta's insight:

There's a link to the paper entitled "Delivering on the Promise of Big Data in The Cloud" which goes into more detail on the Reference Data Architecture.   In that paper, the authors describe some of the techniques used to filter big data and visualize it in support of revealing meaning in the data.  Some of this visualization will involve charting, maps, timelines, tables and relationship graphs.  Big data is manageable given the right tools and methods of analysis.

 

When using this tools, here are some of the steps I've seen applied in the past with success -

 

  • Take an inventory of your data identifying data sources, tables, fields, missing values and the range of values for each field you will be working with.  How clean is the data?   Do you have what your need for the analysis?
  • Form your hypothesis and a detailed set of questions you want to answer about the data.  What are you trying to uncover?  What questions do you need to ask of the data?
  • Filter your data to arrive at a set of data to visualize.  This may need to be done in stages. For example, if you're using a visualization tool, you may be able to pre-process the data selecting a subset for your analysis. After some initial charting, you may identify a sub segment of data you want to look at more closely.  After looking at that data in different forms (maps, timelines, tables), you may decide it can be refined even further.
  • Use relationship graphing (link analysis) to connect the dots.   You may decide you need to see relationships between people and the flights they took, or people, where they live and where they work.  Any number of connection points can be analyzed with commercially available tools.   Too many connections will make the graph overly complex.   Three to six is probably ideal.
  • From that point, there are ways to highlight meaning in the data - scaling the size of the nodes and links based on other measures such as amount of deposits, number of calls, number of connections to other nodes – all of these will point you toward parts of the graph you need to explore in more detail.  Labeling and showing direction between the nodes (Did Jim call Steve or did Steve call Jim?) are other ways to analyze the data. 
  • Most tools that perform link analysis allow you to draw the graphs using different layouts. For example, draw the graph with the node that has the greatest number of connection points at the center.   Social network metrics like centrality and betweeness help you identify important nodes on the graph.  The entire space should be searchable providing you another level of filtering to identify individuals of interest.
  • There's usually a time dimension that's important in this type of analysis.  For example, when accounts were opened and closed, when phone calls were made or when flights were taken may provide additional insights.   Some tools allow you to build the graph based on this time dimension as if you're watching a movie. The graph is constructed based on these important events.
  • Share your results along with the insights you've found.  See if other analysts have additional things to add.

 

There are a ton of techniques you can use when it comes to big data visualization.    This is just a small sample but hopefully it helps analysts naviagte through large sets of data using data visualization and link analysis.

 


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Real world NoSQL performance pitfalls…

I’ve said for a long time that I am concerned about the accuracy of performance claims on Open Source NoSQL databases. In this blog post I give you a couple of links to people who have tried ...
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Tony Agresta's comment, January 7, 2013 2:37 PM
More insights from Adam Fowler's Blog
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'Big data' – the crown jewel or another missed opportunity for telcos? - Insight - News | Analysys Mason

'Big data' – the crown jewel or another missed opportunity for telcos? - Insight - News | Analysys Mason | Big Data Technology, Semantics and Analytics | Scoop.it
Analysys Mason delivers strategy advice, operations support, and market intelligence worldwide to leading commercial and public sector organisations in telecoms, IT, and media.
Tony Agresta's insight:

With vast amounts of data about consumer usage, cost effective advertising, churn reduction and effective cross sell seem well suited to be addressed with big data technology in the telco space.    Now that data streams can be captured in real time as data is pushed to communication service providers, this data can be connected to data pulled from other databases to create vivid usage patterns.   When anonymized and profiled correctly, it represents a perfect fit for advertisers, especially with any geospatial attributes available.  According to this article, Telefonica is doing just that.  


With enterprise search available through indexed data management, telcos can track pattern changes in real time while displaying results in dashboards. It’s this dynamic data analysis that can lead to more targeted advertising.   Load balancing based on network usage can also be monitored with big data triggers in place to avoid thresholds from reaching certain levels.   In other words, service interruptions can be avoided as part of this process.   Out of home advertising will become more pervasive in 2013 and 2014 as taxis and other forms of transportation begin to dynamically advertise based on geo location. If the advertising is relevant, timely, has the proper incentive and respects privacy, it has the potential to create new forms of revenue for the telco industry as well.

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How Large Enterprises are Benefiting from The Use of NoSQL Database

How Large Enterprises are Benefiting from The Use of NoSQL Database | Big Data Technology, Semantics and Analytics | Scoop.it
For the most part, the world of database management systems has been ruled by the SQL model for quite some time. There have been a few alternative methods that have temporarily popped up but SQL has maintained its dominance.
Tony Agresta's insight:

Quite true, the NoSQL movement is gaining momentum and this trend will continue for years to come.   But beware - not all NoSQL approaches are the same.   At MarkLogic, we distinguish between the open source vendors, some legacy relational players with nascent offerings and our Enterprise approach with 6 releases over 10 years.  Areas of distinction include but not are not limited to developer productivity, application performance and enterprise readiness.

 

Advanced search using facets, geospatial search, entity enrichment, data consistency, the ability to retrieve multiple documents, integration with the BI stack using SQL, real time data ingestion and security are just some of the areas that organizations evaluating this class of technology should look closely at.

 

Here are two links to additional information on these topics:

 

Important components of an Enterprise NoSQL Database:

http://www.marklogic.com/what-is-marklogic/enterprise-nosql/

 

Customer Success with enterprise grade deployments:

http://www.marklogic.com/customers/

 

 

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Big Data In the Enterprise: A Lesson Or Two From Big Brother - Forbes

Big Data In the Enterprise: A Lesson Or Two From Big Brother - Forbes | Big Data Technology, Semantics and Analytics | Scoop.it
Guest post written by Franz Aman Franz Aman is chief marketing officer and senior VP of Business Strategy at SGI.
Tony Agresta's insight:

MarkLogic Corporation, provider of the enterprise NoSQL database, and SGI (NASDAQ: SGI), the trusted leader in technical computing and provider of Hadoop® Big Data solutions, today announced the SGI® DataRaptor™ with MarkLogic® database. An integrated and optimized hardware and software solution, SGI DataRaptor is designed to make it faster and easier for organizations to generate reliable, scalable and secure Big Data results.

 

You can learn more here:

 

http://www.marklogic.com/press-releases/big-data-ready-set-go-new-sgi-dataraptor-with-marklogic-database-is-having-big-data-for-lunch/

 

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Here is how cloud computing, big data, and some innovation can reinvent healthcare

Here is how cloud computing, big data, and some innovation can reinvent healthcare | Big Data Technology, Semantics and Analytics | Scoop.it
No matter if you were for or against the new healthcare regulatory changes, the end result is that more people will be tossed into a system that is already at capacity. You can either ration the c...

Via Mason Powers
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Mason Powers's curator insight, December 27, 2012 11:09 AM

Interesting article with 2 recommendations for Healthcare Providers & Payers in leveraging big data technologies:

 

1. Manage patient data holistically, and in new, innovative ways. 

 

This is exactly what Informatics Corporation of America is doing through their industry leading Health Information Exchange.  By powering this exchange with MarkLogic's enterprise-hardened NoSQL database technology, ICA is able to provide a holistic view of the patient across all delivery networks. 

 

2.  Combine data into huge analytical data sets that exist on cloud computing providers, providing universal open access.

 

This continues the discussion of the available technologies which can now combine ALL data:  diagnostic, treatment, and outcome data into a single, searchable repository (i.e. MarkLogic 6).  Analysts can combine this data, better understand factors of quality of care, and keep healthcare costs low.  Low healthcare costs = healthy Americans; this inverse relationship should be the most obvious and striking point to motivate both providers and payers to adopt a big data strategy that focuses on lowering costs.  Whereas lower costs leads to healthier citizens, it also leads to higher margins.   

 

The next generation of technologies is here:  technologies that can manage vast amounts of unstructured, strucutred, and poly-structured data, all from the same platform; technologies that can maintain performance, speed, and scale under constant ingest and high frequency queries; technologies that work better, enable innovation, and do so for much, much cheaper.  

 

Please take a look at www.marklogic.com to learn how we are helping leading Healthcare organizations leverage their big data and improve quality of care through shortened billing cycles with better outcomes. 

Tony Agresta's comment, December 28, 2012 7:19 AM
Good insight Mason. If you like Mason's post, you will also like this: http://www.slideshare.net/tagresta/marklogic-applications-in-healthcare
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Data Virtualization Solutions | MarkLogic

Data Virtualization Solutions | MarkLogic | Big Data Technology, Semantics and Analytics | Scoop.it
MarkLogic’s enterprise NoSQL database overcomes the limitations of rigid RDBMS-based systems, enabling comprehensive data virtualization.

Via Dominic Spitz
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Dominic Spitz's curator insight, January 21, 2013 8:13 AM

Organizations with business critical information scattered across separately owned and managed silos need this data in one place. MarkLogic’s Enterprise NoSQL database overcomes the limitations of rigid RDBMS-based systems, enabling comprehensive data virtualization.

 

The growing volumes of information available today continue to put a heavy work load on data analysts. It is difficult and often too time consuming for analysts to separate the useful information from the rest. They risk drawing incorrect conclusions because they missed buried, relevant information. Or they risk missing a critical deadline or opportunity because it took so long to analyze the data.

 

MarkLogic is the Enterprise NoSQL database that manages all types of data at scale in real time. MarkLogic lets developers build the visualization capabilities that help analysts make quick, informed decisions with Big Data.

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How the Cloud and Big Data Are Changing Entertainment - Forbes

How the Cloud and Big Data Are Changing Entertainment - Forbes | Big Data Technology, Semantics and Analytics | Scoop.it
filmratings.com From Amazon to Wal-Mart, companies are carving up the fast-growing market for direct digital delivery of movies to the living room.

Via Toni Sánchez
Tony Agresta's insight:

"Whether a consumer is browsing the shelves of a traditional video rental store or choosing a movie from the cloud, discoverability is a huge user challenge.


That’s why many of the streaming services are investing in big-data analytics, to help give consumers suggestions of what movies they might want to watch."

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Big Data, MarkLogic, and Tableau = Greatest Possible Insights

Big Data, MarkLogic, and Tableau = Greatest Possible Insights | Big Data Technology, Semantics and Analytics | Scoop.it
This presentation at the recent Tableau conference was so popular, we just had to repeat it! Fernando Mesa, Chief Technologist, Enterprise, will reprise the presentation in this special webcast.
Tony Agresta's insight:

User adoption of analytics technology is driven by ease of use and robust functionality the result of which are insights you can apply to drive performance. When combined with an Enterprise NoSQL approach that includes native search capabilities, data can be exposed to Tableau in a highly scalable, secure environment that also includes real time analysis, notifications, geospatial search and other angles of analysis. Loading data “as is” using a schema-less database can dramatically shorten the cycles from data ingestion to decisions. This premise is especially important in mission critical applications across healthcare, government, financial services and media markets, to name a few. Hadoop is now part of the MarkLogic platform allowing users to store the data and make it available to MarkLogic “on demand”. This staging area has many benefts including data enrichement and on demand delivery to MarkLogic (and therefore Tableau) for specific sets of data.  MarkLogic data is exposed to Tableau though an ODBC SQL query.  Enhanced data discovery includes all of  your data - including unstructured and semi-structured data in MarkLogic.

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Build or Buy: Open Source or Enterprise Software | MarkLogic

Looking for a NoSQL database? Should you build or buy, use open source or Enterprise software?
Tony Agresta's insight:

A must read for anyone considering big data technology.  

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Giving big data publishing the royal treatment

Giving big data publishing the royal treatment | Big Data Technology, Semantics and Analytics | Scoop.it
U.K. royal society jumps into 21st century with the MarkLogic NoSQL database, opening 170 years of content to public view
Tony Agresta's insight:

 

A NoSQL database from MarkLogic provides the Royal Society of Chemistry (RSC) with the ability to unlock a treasure trove of assets.  Now the RSC can publish three times as many journals and four times as many articles. It also gave the Society the ability to develop new educational applications to make chemistry accessible to a wider audience.

 

Modern approaches to information products replete with full text search have the power to transform your business.  Built on an enterprise hardened NoSQL database that can ingest data in real time using a "schemaless" design, they provide a brilliant user experience displaying search results, allowing users to filter, save searches and more.

 

Unstructured data assets hidden in the recesses as dark data can be consolidated with new forms of data streaming from the internet.

 

"The accumulated content includes more than 1 million images, millions of science data files, and hundreds of thousands of articles from more than 200,000 authors. On top of that, add the recent capture of social media, video, and other digital content."   

 

This reminds me of another application built on MarkLogic called AuthorMapper from Springer Media. Using geospatial search, users can zoom into countries, identify articles of interest, read the abstracts, search by date range, apply full text search and more - all within a durable, reliable enterprise NoSQL platform that offers real time alerts in a scale out environment.  Can MongoDB do this?   No they can't.

 

New Information products like these can be brought to market quickly since developers can built them with Java, Rest and other common languages.   Extending them to include interactive analytics in the form of data visualization is built into MarkLogic.  Don't be fooled by NoSQL pretenders only to discover you need to write hundreds of thousands of lines of code. 

 

You can watch a video of the RSC at www.marklogic.com under the Customers tab.  Click on videos and it’s in the lower right.  You can experiment with the Springer application at www.authormapper.com

 

 

 

 

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Insights for 2013: Understanding Your Customers & The Full Value of Digital - Analytics Blog

Insights for 2013: Understanding Your Customers & The Full Value of Digital - Analytics Blog | Big Data Technology, Semantics and Analytics | Scoop.it
Tony Agresta's insight:

With digital customer interactions exploding across more channels than ever before, marketing mix optimization has become even more complex.   What if customers interactions could be stored in one database, ingested from many sources?  What if customer conversion metrics could be calculated in that database in real time?  What if you could interactively analyze campaigns to identify the over and underperforming ones?   With so many clicks, opens, web page visits and more, this may seem daunting.

 

But it is possible.   Today, most CRM systems allow users to store this data but aren’t all that friendly when it comes to analysis.   Big data technology integrated with interactive data analysis tools allows you to ingest different both structured and unstructured data providing marketing analysts with the ability to search the data, isolate sets of data for analysis and work with applications that display the ad or video alongside data visualization widgets that measure response,  performance and trends over time.   Notifications triggered using pre-built alerts tell you when conversion rates exceed predefined thresholds or fall below expectations.

 

Not many companies have applied enterprise NoSQL technology for marketing applications like but all of the technology components to accomplish this have been deployed in applications that share some of the same characteristics.  Look at the excellent work the BBC did at last year's Summer Olympics.   They ingested real time data feeds from over 20 venues, twitter and authored articles. They consolidated this with photos, bios, player statistics - all on one website and all with sub-second, instantaneous response.    The user experience was remarkable – stickiness personified.

 

Measuring advertising and campaign performance along with historical visitor traffic data is not a far cry from this type of application.  The end game is improved loyalty, optimized ad spend, faster decision making and increased sales.

 

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When Pirates Meet Advanced Analytics

When Pirates Meet Advanced Analytics | Big Data Technology, Semantics and Analytics | Scoop.it
Seagoing criminals are always changing tactics. To catch them, uncover their hidden patterns.

Via Toni Sánchez
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Tony Agresta's comment, January 15, 2013 6:30 AM
This article is spot on - with so many different sources of data, identifying suspects can be challenging. The volume and variety of data stored in different systems makes the job of the intelligence officer almost impossible. But new approaches in big data technology allow data scientists to consolidate the data, including unstructured data. Tight integration with data visualization tools that talk to Enterprise NoSQL databases make it easier than ever to profile all of the data in support of identifying connections between people, events, locations and more. This approach has proven to work in some of the largest intelligence agencies in the world. It has been applied in local law enforcement, fraud detection, loss prevention, cyber security and social networking. Real time alerts make it possible to immediately notify analysts as big data streams into the NoSQL database meeting predefined conditions. But to do this you need an Enterprise approach to NoSQL one that is hardened, scales, meets security requirements and has disaster recovery and high availability as part of the foundational technology providing production grade implementations in less time.
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NoSQL, huh, what is it good for?…

…Actually quite a lot really. Say it again, y’all! In this post I try to dymystify NoSQL for the Relational DB crowd / average human, and give some real world examples of how NoSQL can ...

Via Dominic Spitz
Tony Agresta's insight:

To echo some of Adam's thoughts...In a recent key note by Mike Bowers of The Church of Latter Day Saints, Mike discussed why the NoSQL model is the best model for developing applications.  Here are some of his conclusions after years of working with all major classes of databases.

 

  • The NoSQL approach Increases developer productivity since it supports agile development without a schema
  • With NoSQL, you can handle rapidly changing requirements.
  • NoSQL handles deeply hierarchical, complex, and highly variable data structures
  • There is little-to-no impedance mismatch between application and database
  • JSON is the new lingua franca of the web
  • There's the potential to enable better search relevance including full-text search in context of document structure and full-featured queries of any data anywhere in a document.

 

Specific to the MarkLogic approach, Mike indicated that Enterprise Search capabilities clearly distinguished MarkLogic from the pack, a sentiment echoed by leading analysts around the world.    He went on to break down the most important aspects of this including:

 

  • Ability to Query to find multiple documents, a capability that is not as good in Mongo, poor in Riak and Cassandra.
  • MarkLogic stand alone in the category of search relevance and advanced search with facets, geospatial search and entity enrichment.
  • Data integration capabilities and data consistency are also unique differentiators and large contributors to developer productivity.

 

Enterprise readiness was discussed in detail during the key note.  More on that in another post.

 


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Why use a NoSQL Database, and why not?

I just conducted a review of the first 70 results from Google on the question “Why use a NoSQL database?”. In this post I show you the results in the for camp, and the against camp. The...
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Financial Services | MarkLogic: Risk Management and Post-Trade Processing

Financial Services | MarkLogic: Risk Management and Post-Trade Processing | Big Data Technology, Semantics and Analytics | Scoop.it
Visit MarkLogic.com to read Financial Services.

Via Dominic Spitz
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Dominic Spitz's curator insight, January 3, 2013 3:52 AM

By consolidating separate copies of data into a single database, banks can more effectively assess and manage the risks associated with their trading activities. Eliminating multiple databases has the additional benefit of significantly reducing maintenance costs. Benefits include risk reduction as well as lower costs per trade resulting in a competitive advantage over peers using legacy systems. Learn how a top 5 global trading bank achieved this objective using MarkLogic.

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NYT: Big Data Is Great, but Don't F

NYT: Big Data Is Great, but Don't F | Big Data Technology, Semantics and Analytics | Scoop.it
It is easier than ever to measure and monitor people and machines, but the technology of Big Data is not without its shortcomings.
Tony Agresta's insight:

Intuition helps but there's no substitute for big data technology and analysis.  Technology to ingest, store, search and analyze big data will proliferate across government and commerical sectors in 2013 and beyond.

 

Techniques for segmentation, clustering and modeling data allow organizations to revel meaning hidden inside massive amount of data.

 

Experienced analysts can recommend independent attributes for inclusion in the analysis, variables that have explanatory power in a model or segmentation scheme.  When this experience is coupled with data discovery methods to explore data in an unconstrained way, analysts can pinpoint data elements and relationships that may be correlated with a specific outcome and therefore improve the accuracy of the model.  It’s the combination of intuition, proven experience, flexible discovery tools, proven statistical methods and a full set of data that lead to the fastest, most significant insights.

 

This freedom to explore data has other benefits including identifying missing or poor quality data yielding improved standards and collection processes.  Most of this can be discovered through profiles and histograms of each data field.

 

Data discovery tools, when combined with the approaches referenced above, allow analysts to confirm findings and expand the way analyst’s model data. During this process, the analyst may discover new ways to transform data, group continuous data into categorical data or calculate new data attributes to be used in the analysis. 

 

This class of tools has the added advantage of telling a story about your data using a full complement of visualizations designed to focus the audience on insights and conclusions.  Once the data story is presented to the business, they rapidly draw conclusions to shape programs.

 

Look at the work MarkLogic has done with Tableau Software to better understand the enhanced power of data discovery using the full breadth of both unstructured and structured data. Sure, intuition is important.  But proven analytical methods that leverage new forms of data in real time will give you the most bang for your buck.  

 

http://resources.marklogic.com/library/media/big-data-marklogic-tableau-insights

 

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Healthcare IT: The 4 Pillars Of Technical Innovation - CRN

Healthcare IT: The 4 Pillars Of Technical Innovation - CRN | Big Data Technology, Semantics and Analytics | Scoop.it
Healthcare IT: The 4 Pillars Of Technical Innovation CRN Four major technology trends, which are becoming more intertwined every day, will dominate the healthcare IT landscape in 2013, according to IDC Health Insights' top researcher, Scott...

Via Mason Powers
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Mason Powers's curator insight, December 20, 2012 1:10 PM

The 4 trends for Healthcare IT in 2013:

 

1. Cloud

2. Big Data & Analytics

3. Social Media

4. Mobility

 

Here is how the industry's leading big data platform provider, MarkLogic, supports these 4 trends, with the agility and security Healthcare organizations require:

 

1. Cloud: http://www.marklogic.com/solutions/data-virtualization/  

2. Big Data & Analytics:  http://www.marklogic.com/what-is-marklogic/analytics-business-intelligence/

3. Social Media:  http://www.marklogic.com/solutions/social-media-analysis/

4. Mobility:  http://www.marklogic.com/solutions/content-delivery/