Smart Content Summit: Unlock the Value with the Right Data Pattern

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The document discusses using a semantic approach to data to enable smart content. It describes how traditional databases store data in silos by category and attributes. A new approach uses a NoSQL database with semantics to break down these silos. An example is given of a Saturday Night Live app that allows semantic search of talent, episodes, characters and other metadata. The operational data hub pattern is proposed to ingest raw data from various sources, harmonize it using semantics, and allow both analytical and operational applications to access the normalized data. This creates smart content by breaking down data silos.

Software

8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Unlock Smart Content
with the Right (Data) Pattern
Matt Turner, CTO Media & Manufacturing
@matt_turner_nyc
#SCCWest18

SLIDE: 5 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Traditional Database Approach
Category
Feature
Series
Action
Drama
Comedy
Documentary
…
Cable
Broadcast
Drama
Comedy
…
Action
Drama
Family
Documentary
…
Title ProductionDate Category AssetType Length
Film1 3/1/14 Feature HD Master 2:40
Show1 6/4/13 Series HD720 0:40
Film2 6/4/05 Feature Archive 1:55

SLIDE: 6 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

SLIDE: 7 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
INCEPTION1 PRE-PRODUCTION2 PRODUCTION3 POST-PRODUCTION4 DISTRIBUTION5 ARCHIVE6
SEMANTICSTAXONOMIESCONTENT CUSTOMERSMETADATA
The Result: Data in Silos

SLIDE: 8 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
A New Approach

SLIDE: 9 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
NoSQL and Semantics = Smart Content!

SLIDE: 10 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
The SNL App

SLIDE: 11 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Semantics-driven search
Talent
Kristen Wiig
Acted in
Episode 4
Anne Hathaway and Killers
Part of
Played
Character
Maharelle Sister
Season 34
Segment
The Lawrence Welk Show
Aired on
Date
10/4/08
Era
Acted in
Includes
Part of

SLIDE: 12 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
NoSQL and Semantics … and More Data
Finance +Sales
Customers
Products
…

SLIDE: 13 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Operational Data Hub Pattern
SMART CONTENT
MESSAGE
BUS
RDBMS
CONTENT
FEED
INGEST
ANALYTICAL
APPS
OPERATIONAL
APPS
DOWNSTREAM
SYSTEMS
DELIVER
STAGING
(RAW DATA AS IS)
FINAL
(HARMONIZED, INDEXED DATA)
SOURCE 1
DOCUMENTS
SOURCE 2
DOCUMENTS
SOURCE N
DOCUMENTS
ENVELOPED DOCS
(ENTITY 1)
ENVELOPED DOCS
(ENTITY 2)
ENVELOPED DOCS
(ENTITY N)HARMONIZE
INDEX, SEARCH,
DISCOVERY, &
HARMONIZATION
INDEX, SEARCH,
& SERVICES
f(x)

SLIDE: 15 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
PLANNING1 PRE-PRODUCTION2 PRODUCTION3 POST-PRODUCTION4 DISTRIBUTION5 ARCHIVE6
TAXONOMIES CUSTOMERSMETADATASEMANTICSCONTENT
Operational Data Hub for Media

8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Thank You!
Matt Turner, CTO Media & Manufacturing
@matt_turner_nyc
#SCCWest18

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Smart Content Summit: Unlock the Value with the Right Data Pattern

5. SLIDE: 5 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. Traditional Database Approach Category Feature Series Action Drama Comedy Documentary … Cable Broadcast Drama Comedy … Action Drama Family Documentary … Title ProductionDate Category AssetType Length Film1 3/1/14 Feature HD Master 2:40 Show1 6/4/13 Series HD720 0:40 Film2 6/4/05 Feature Archive 1:55

7. SLIDE: 7 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. INCEPTION1 PRE-PRODUCTION2 PRODUCTION3 POST-PRODUCTION4 DISTRIBUTION5 ARCHIVE6 SEMANTICSTAXONOMIESCONTENT CUSTOMERSMETADATA The Result: Data in Silos

11. SLIDE: 11 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. Semantics-driven search Talent Kristen Wiig Acted in Episode 4 Anne Hathaway and Killers Part of Played Character Maharelle Sister Season 34 Segment The Lawrence Welk Show Aired on Date 10/4/08 Era Acted in Includes Part of

13. SLIDE: 13 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. Operational Data Hub Pattern SMART CONTENT MESSAGE BUS RDBMS CONTENT FEED INGEST ANALYTICAL APPS OPERATIONAL APPS DOWNSTREAM SYSTEMS DELIVER STAGING (RAW DATA AS IS) FINAL (HARMONIZED, INDEXED DATA) SOURCE 1 DOCUMENTS SOURCE 2 DOCUMENTS SOURCE N DOCUMENTS ENVELOPED DOCS (ENTITY 1) ENVELOPED DOCS (ENTITY 2) ENVELOPED DOCS (ENTITY N)HARMONIZE INDEX, SEARCH, DISCOVERY, & HARMONIZATION INDEX, SEARCH, & SERVICES f(x)

14. Operational Data Hubs

15. SLIDE: 15 8 March 2018© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. PLANNING1 PRE-PRODUCTION2 PRODUCTION3 POST-PRODUCTION4 DISTRIBUTION5 ARCHIVE6 TAXONOMIES CUSTOMERSMETADATASEMANTICSCONTENT Operational Data Hub for Media

Editor's Notes

This pattern for an operational data hub has been developed from real world requirements from ongoing customer projects at Fortune 500 companies, by working closely with the on-site consultants to capture the common patterns that were used to conceptualize the overall framework. At the high level it comes down to 3 step process: Data Ingestion: Where source documents from multiple sources land into MarkLogic staging area – taking full advantage of ‘load as is’ capability of MarkLogic Data Harmonization: This is where MarkLogic secret sauce – its rich indexes and powerful query/scripting mechanism either using Xquery or JavaScript is used to standardize a variety of source documents into entity instances where entity could be a Customer, a Patient, an Insurance Claim and so on. The entity instances are documents which are formatted using the envelop pattern which is again very commonly used in the field to capture the standard attributes related to the entities. This is where complexity of data silos – different models, different schemas, different languages is turned into standardized data structures within MarkLogic that are made available in what is called as ‘final’ area. Serving: Serving refers to making the data accessible to a number of consuming applications. These could be operational apps, analytical apps and so on. All applications have different needs in terms of how they want to access the data, what data formats they can handle etc. In other words ‘Schema on Read’ which is another aspect where MarkLogic is really good at. Again this is where MarkLogic indexes and rich query capabilities play an important role. Since all the data is available in standardized entity instances in the final area, it’s easier to serve that data in whatever format the consuming application needs it. The best practices captured here are: Separation of staging/final area – Typically these are two different databases. They have different indexes, different security policies, and different life cycle management or storage management policies associated with them. Concept of the envelope pattern to capture standardized entity attributes without throwing away the original source documents. Implementation best practices – making sure there are guardrails in place when it comes to implementing all different steps but specifically the data harmonization step.

Smart Content Summit: Unlock the Value with the Right Data Pattern

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Smart Content Summit: Unlock the Value with the Right Data Pattern

Editor's Notes