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THE RISE OF NOSQL
Mark van der Waals, Capgemini
Michel de Ru, MarkLogic
How NoSQL fits in your Enterprise Architecture
© COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
WHAT BUSINESSES WANTS
WHAT IT & ARCHITECTS NEED TO DELIVER
SLIDE: 2 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Bring new products and services to market fast
Deliver a modern user experience
Interact effectively in a networked ecosystem
Improve operational efficiency
Manage business risk
Use data & intelligence as key asset & enabler
Stay compliant to regulation
Fast time to market
Agility in delivery
Flexibility to change
Reduced cost & complexity
Technological innovation
MOBILE FIRST
NEW
RESEARCH
REQUIREMENTS
Your business is changing… Your data & infrastructure are changing…
NEW
APPS
EXPANSION
SOCIAL MEDIA &
COMMUNITIES
SLIDE: 3 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
ANALYTICS
NEW MONETIZATION
STRATEGIES
VIRTUALIZATION &
CLOUD
NEW
REGULATION
MERGERS &
ACQUISITIONS
EMPLOYEE
TURNOVER
INTERNET OF
THINGS
MACHINE
LEARNING
Separation of transactional & intelligence world
Silo systems also in intelligence world
Content Mgt & Knowledge Mgt
Collaboration platforms
This proliferation of data is:
Resulting in latency …no real time picture
Not consistent & not governable & non-compliant
Challenges in Enterprise Architecture
SLIDE: 4 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Collaboration platforms
Archives (Rules on anonymizing & deleting data,
Right to be forgotten)
DWHs, Operational Data stores with predefined
schema’s
Multiple copies of data & exponential growth
FS data is replicated 5-12 times, only 10% of data is unique
Not effective: Myth of One
Not affordable
Not agile or flexible
Root causes:
1. Heterogenous data in silos
2. Relational DB’s are not made to
solve this problem
As data structures get more complex
and data volume grows, traditional relational
databases—and their need for a pre-defined
schema are falling short.”
“
schema are falling short.”
The Problem With the Relational Approach
1
Take a Current
State Snapshot
Design the New
Data Model
Perform ETL
2
3
4
SLIDE: 6 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
The Business Changes,
The Requirements Change,
The Source Data Changes
Create the
Indexes
4
Build the
Application
5
Restart Process
6
OPERATIONAL
DATA SOURCES BINARY TXT GEOJSONXML
JSON
A Multi Model approach
Decoupling of loading and using the data
Load data & meta data AS IS (one schema on write)
So no upfront modelling & ETL tools needed
Allows for multiple schema’s on read – per use case
Why NoSQL is part of the solution
SLIDE: 7 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
BIDIRECTIONAL
ANALYSIS
OF ALL DATA
MULTI-CHANNEL
DISTRIBUTION
XML
SEMANTIC
DATA
GEOSPATIAL
DATA
BINARY
Allows for multiple schema’s on read – per use case
Allows for Agile & Parallel way of developing use cases
Combining structured and semi/unstructured data such as:
Documents (XML, enriched...)
Geospatial data (2D)
JSON & Binary data (audio,video)
Relating and structuring data in a flexible way
key-value pairs, graphs
Scalability and Elasticity
Why MarkLogic: the only enterprise hardened NoSQL platform
Enterprise hardened
Security
Transactional integrity
SLIDE: 8 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Scalability and Elasticity
Horizontal Scaling on Commodity Hardware
Flexible clustering for elastic scaling of user
queries, transactions, and data volumes
Data can be easily moved, deleted,
designated read-only, taken offline/online, etc.
Use Cases for NoSQL and MarkLogic references
Record keeping & regulatory reporting
Regulatory reporting
Combining Archiving & Intelligence
Operational Data Warehouse
Content re-purposing
B2C publishing
B2B publishing
Custom reporting
SLIDE: 9 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Operational Data Warehouse
Operational decision making in real-time
Fraud prevention
Next best action
Application processing in banking & insurance
Derivatives core processing
Custom reporting
Video metadata delivery
NoSQL in Regulatory Reporting
A real world use-case
Research /
Portal and
Channels
Execution & Position
Management
CFTC
MIFID I/II
SEC-Reg-SCI
SEC Rule 15c3-5
Treasury
(Funding and
Liquidity)
CRD-IV
Finance &Finance &
Risk Management
BASEL II/III
COREP
Dodd-Frank
SEC-PF
Solvency II
BCBS
239
The Regulatory Landscape
SLIDE: 11 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Client Onboarding
KYC
Research /
Advisory
Finance &
General Ledger
Sarbanes-
Oxley
FINREP
IFRS
Solvency II
Operations
EMIR
FATCA
Corporate
Finance /
M&A
Legal / Compliance /
Surveillance
MADII
Reference
Data
MIFIR
The Endless Cycle of Data Harmonization
1 2
Take snapshot of current data Build master data model based
on initial view
SLIDE: 12 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
34 Extract, transform, &
load data into data model
Revise static model &
restart process for new data
x
The Endless Cycle of Data Harmonization
1 2
Take snapshot of current data Build master data model based
on initial view
SLIDE: 13 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
34 Extract, transform, and
load data into data model
Revise static model and restart
process for new data
x
2-5 years
$5M++
Simple and Fast Data Integration With NoSQL
1 2
Load data “as-is” - index data
now and transform over time
Agile application development
without constraints - and
with a stable data layer
SLIDE: 14 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Datalayer
Time-to-completion: 3 monthsTime-to-completion: 3 months
SLIDE: 15 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Where do we go from here ?
Operational
Data Hub
Operational
360 of
Anything
Is-A
May be
applied to
Is-A
Provides
Governance Risk &
Compliance (GRC)
Operational Transaction
Repository (formerly
known as Trade Store) is
a type of ODH
Covers Orders, Trades
and Settlement Payments
(Money, Shares,
SLIDE: 16 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
Operational
Transaction
Repository
Aggregated Liquidity & Risk
Reporting (CRD IV, CCARS
Solvency II)
Regulatory Book of Record
RBOR (Dodd Frank, MIFID
II)
Fraud / Market Abuse
Surveillance
Consolidated Position
and Portfolio
Management
May be used for
Transaction
360
Provides
Industry
Function
Use
Case
Architecture
Solution
Business
Solution
Enterprise
FinServe
Trading Utilities/SDRs
and Regulators
(Money, Shares,
Commodity Assets)
Capgemini – MarkLogic partnership
Joint projects & bids
Training program:
30 trained Capgemini consultants in India, France, Spain & the Netherlands
SLIDE: 17 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
SLIDE: 18 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

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Cwin16 - Lyon - partner mark logic - the rise of nosql

  • 1. THE RISE OF NOSQL Mark van der Waals, Capgemini Michel de Ru, MarkLogic How NoSQL fits in your Enterprise Architecture © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
  • 2. WHAT BUSINESSES WANTS WHAT IT & ARCHITECTS NEED TO DELIVER SLIDE: 2 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. Bring new products and services to market fast Deliver a modern user experience Interact effectively in a networked ecosystem Improve operational efficiency Manage business risk Use data & intelligence as key asset & enabler Stay compliant to regulation Fast time to market Agility in delivery Flexibility to change Reduced cost & complexity Technological innovation
  • 3. MOBILE FIRST NEW RESEARCH REQUIREMENTS Your business is changing… Your data & infrastructure are changing… NEW APPS EXPANSION SOCIAL MEDIA & COMMUNITIES SLIDE: 3 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. ANALYTICS NEW MONETIZATION STRATEGIES VIRTUALIZATION & CLOUD NEW REGULATION MERGERS & ACQUISITIONS EMPLOYEE TURNOVER INTERNET OF THINGS MACHINE LEARNING
  • 4. Separation of transactional & intelligence world Silo systems also in intelligence world Content Mgt & Knowledge Mgt Collaboration platforms This proliferation of data is: Resulting in latency …no real time picture Not consistent & not governable & non-compliant Challenges in Enterprise Architecture SLIDE: 4 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. Collaboration platforms Archives (Rules on anonymizing & deleting data, Right to be forgotten) DWHs, Operational Data stores with predefined schema’s Multiple copies of data & exponential growth FS data is replicated 5-12 times, only 10% of data is unique Not effective: Myth of One Not affordable Not agile or flexible Root causes: 1. Heterogenous data in silos 2. Relational DB’s are not made to solve this problem
  • 5. As data structures get more complex and data volume grows, traditional relational databases—and their need for a pre-defined schema are falling short.” “ schema are falling short.”
  • 6. The Problem With the Relational Approach 1 Take a Current State Snapshot Design the New Data Model Perform ETL 2 3 4 SLIDE: 6 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. The Business Changes, The Requirements Change, The Source Data Changes Create the Indexes 4 Build the Application 5 Restart Process 6
  • 7. OPERATIONAL DATA SOURCES BINARY TXT GEOJSONXML JSON A Multi Model approach Decoupling of loading and using the data Load data & meta data AS IS (one schema on write) So no upfront modelling & ETL tools needed Allows for multiple schema’s on read – per use case Why NoSQL is part of the solution SLIDE: 7 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. BIDIRECTIONAL ANALYSIS OF ALL DATA MULTI-CHANNEL DISTRIBUTION XML SEMANTIC DATA GEOSPATIAL DATA BINARY Allows for multiple schema’s on read – per use case Allows for Agile & Parallel way of developing use cases Combining structured and semi/unstructured data such as: Documents (XML, enriched...) Geospatial data (2D) JSON & Binary data (audio,video) Relating and structuring data in a flexible way key-value pairs, graphs
  • 8. Scalability and Elasticity Why MarkLogic: the only enterprise hardened NoSQL platform Enterprise hardened Security Transactional integrity SLIDE: 8 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. Scalability and Elasticity Horizontal Scaling on Commodity Hardware Flexible clustering for elastic scaling of user queries, transactions, and data volumes Data can be easily moved, deleted, designated read-only, taken offline/online, etc.
  • 9. Use Cases for NoSQL and MarkLogic references Record keeping & regulatory reporting Regulatory reporting Combining Archiving & Intelligence Operational Data Warehouse Content re-purposing B2C publishing B2B publishing Custom reporting SLIDE: 9 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. Operational Data Warehouse Operational decision making in real-time Fraud prevention Next best action Application processing in banking & insurance Derivatives core processing Custom reporting Video metadata delivery
  • 10. NoSQL in Regulatory Reporting A real world use-case
  • 11. Research / Portal and Channels Execution & Position Management CFTC MIFID I/II SEC-Reg-SCI SEC Rule 15c3-5 Treasury (Funding and Liquidity) CRD-IV Finance &Finance & Risk Management BASEL II/III COREP Dodd-Frank SEC-PF Solvency II BCBS 239 The Regulatory Landscape SLIDE: 11 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. Client Onboarding KYC Research / Advisory Finance & General Ledger Sarbanes- Oxley FINREP IFRS Solvency II Operations EMIR FATCA Corporate Finance / M&A Legal / Compliance / Surveillance MADII Reference Data MIFIR
  • 12. The Endless Cycle of Data Harmonization 1 2 Take snapshot of current data Build master data model based on initial view SLIDE: 12 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. 34 Extract, transform, & load data into data model Revise static model & restart process for new data x
  • 13. The Endless Cycle of Data Harmonization 1 2 Take snapshot of current data Build master data model based on initial view SLIDE: 13 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. 34 Extract, transform, and load data into data model Revise static model and restart process for new data x 2-5 years $5M++
  • 14. Simple and Fast Data Integration With NoSQL 1 2 Load data “as-is” - index data now and transform over time Agile application development without constraints - and with a stable data layer SLIDE: 14 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. Datalayer Time-to-completion: 3 monthsTime-to-completion: 3 months
  • 15. SLIDE: 15 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
  • 16. Where do we go from here ? Operational Data Hub Operational 360 of Anything Is-A May be applied to Is-A Provides Governance Risk & Compliance (GRC) Operational Transaction Repository (formerly known as Trade Store) is a type of ODH Covers Orders, Trades and Settlement Payments (Money, Shares, SLIDE: 16 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. Operational Transaction Repository Aggregated Liquidity & Risk Reporting (CRD IV, CCARS Solvency II) Regulatory Book of Record RBOR (Dodd Frank, MIFID II) Fraud / Market Abuse Surveillance Consolidated Position and Portfolio Management May be used for Transaction 360 Provides Industry Function Use Case Architecture Solution Business Solution Enterprise FinServe Trading Utilities/SDRs and Regulators (Money, Shares, Commodity Assets)
  • 17. Capgemini – MarkLogic partnership Joint projects & bids Training program: 30 trained Capgemini consultants in India, France, Spain & the Netherlands SLIDE: 17 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
  • 18. SLIDE: 18 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.