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

231 views

Published on

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

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
231
On SlideShare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
7
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

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

  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 10. NoSQL in Regulatory Reporting A real world use-case
  11. 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. 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. 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. 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. 15. SLIDE: 15 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.
  16. 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. 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. 18. SLIDE: 18 © COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

×