meta360enterprise data governance and metadata tool
Copyright ©2016 Global Data Store LLC9/8/2016
#gameChanger #simple #clean #ultrafast #visual #real360view #quickImplementation
Table of Contents
Copyright ©2016 Global Data Store LLC
Enterprise data architecture – challenges, issues, solution?
Crossing the chasm – authentic data management Use Cases
What is meta360?
meta360 differentiation
meta360 fundamentals
meta360 data governance approach
meta360 outcome illustration
Live DEMO
Enterprise Data Architecture – Challenges, Issues, Solution?Challenges : Many organizations lack the business
architecture
Business and technical architecture are not integrated
Business and technical users do not share the content and tools
Data governance and ownership is not established over critical information assets
Big data is not effective without effective metadata management
Issues: Inconsistent and ineffective use of critical
data assets across the organization. Some examples:
Regulatory reporting issues
Increased operational costs
Increased operational risk
Inability to leverage potential of data assets (big data/ data lake)
Solution: Establish 360 view of critical data assets
Allow collaboration between business and technical around the same content and tools
Establish enterprise wide data governance program to manage critical data assets
Business Architecture
TermGlossaries
Internal
Glossaries
External
Glossaries
Industry
Glossaries
Conceptual and
Logical Data
Models
Rules
Data Quality
Rules
Compliance
Business
Functions
Taxonomies
Transactional Data
Loans
Deposits
Securities
Reference and Master
Product
Customer
Ind. Classification
Big Data
Big Transactions
Social networks
M2M
Demographic
Feeds
Data Acquisition
Signal Processing
ETL/ELT
Change Data Capture
Messages
Data Lake / Hadoop Cluster
Analytic Sandbox
Model Validation
Risk Calculators
Finance Data Mart
Operational Data Stores
Risk Mart
CRM
Acq
uis
itio
n
Inte
grat
ion
Sto
re
Consumption
Technology Architecture
Crossing the Chasm – Authentic Data Management Use Cases
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People
•Identify key stakeholders
•Establish Data Governance Organization
•Obtain executive support
Process
•Assign roles and responsibilities and socialize data governance approach
•Establish enterprise wide Data Governance Program
Technology
•Select and implement technology tool(s) to support data governance program
Big Data Implementation
Pillars of effective Data Governance
Effective use of information potential of big data requires end-to-end traceability across the entire big data repository, and that includes business and data lineage. Business lineage refers to associations between business terms and its representations in organization’s technology environment. Data lineage refers to ability to trace data element from business report up to the ultimate source.
Regulatory Reporting and ComplianceHeavily regulated markets, like financial services, put implementation of data governance framework on top of data management priorities. Regulatory initiatives like BCBC 239, CCAR, AnaCredit are impossible to meet without having a robust metadata and data governance solution. For instance, the core component of AnaCreditimplementation is BIRD, The Banks' Integrated Reporting Dictionary (BIRD) is an initiative aimed to streamline the regulatory reporting process for European banks.
meta360 provides an effective and easy to implement 360 view of data assets including business and data lineage.
meta360 provides an effective and easy way to create regulatory reporting and compliance content in metadata repository and integrate that content with your organizations data assets. Moreover, meta360 contains free distribution of regulatory content, like for example BIRD(Banks’ Integrated Reporting Dictionary) that can be used for many European Union Initiatives,
like AnaCredit, SHS, MIR, and many others, as well as some US related content including FR Y 9C and FR Y 14 reports
Data Integration, Data Quality, Reference Data,…
Effective data management requires central point of integration, the “glue” that can make data management capabilities working together under the same framework. Metadata and data governance is that “glue” that can bring business and technical metadata together for effective use of information potential of an organization.
meta360 provides 360 view of data and is designed to be used equally by business and technology users
What is meta360?
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meta360 is an enterprise scale, the state-of-the-art data governance and metadata management tool which provides an easy way to collect and manage all relevant business and technical metadata from your enterprise data environment.
innovative, matured and proven approach for data management operationalization (big data, data governance, data quality, reference data, etc.)
industry agnostic, can be used in various industries (FSI, communications, life science, etc.)
easy to implement – up and running within 6 weeks, even for the large organizations
cloud based (Amazon Cloud) – significantly reduces operational costs
easy content contribution – CSV and JSON file import, manual entry (can be used as primary tool for particular concept types)
exceptional user experience - visually attractive and easy-to-use, multilanguage support. Responsive, works on all devices
predefined content for AnaCredit, BCBS 239 and CCAR regulatory frameworks
Key Features:
meta360 is designed and built by top level consultants who deliver strategic consulting engagements to global financial services organizations.
Superb Technology
MongoDB is the leading NoSQL database, empowering businesses to be more agile and scalable.
Express is a minimal and flexible node.js web application framework, providing a robust set of features for building single and multi-page, and hybrid web applications.
AngularJS lets you extend HTML vocabulary for your application. The resulting environment is extraordinarily expressive, readable, and quick to develop.
Node.js is a platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications.
meta360 is built and powered by new trending technology - MEAN stack. MEAN stands for:
meta360 is deployed on Amazon Web Service Cloud which provides scalability and performance, but also significantly lower infrastructure costs. AWS data center and network architecture are built to meet the requirements of the most security-sensitive organizations.
meta360 differentiation
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There are 4 clear differentiators of meta360
Easy to useEasy to
implement
Real 360 view of data
assets
Outstanding Performance
meta360 design provides exceptional user experience for both, business and technical users.
easy content contribution and bulk import. Even in complex environments meta360 can be up and running within less then 6 weeks.
meta360 provides an innovative way to bring business and technology data together.
Built in latest and greatest technologies (MEAN stack) meta360 is incredibly FAST, secure, scalable and reliable.
Concept and Relationship (1/2)
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Two most fundamental concepts in meta360 are Concept and Relationship.
Concept
Concept is an abstract or generic idea generalized from particular instances. meta360 concept has following attributes: name. definition, type, namespace, flag for criticality and properties (depends on concept type).
Concept Examples
meta360 Concept Types (*):
Glossary Term TaxonomyBusiness Function
Report Report Section
Report Position
Logical data model
ldmEntity ldmAttribute
Database dbTable dbColumn Data Flow
(meta360)Namespace
User User GroupOrganization
Name Asset
Type Term
Definition An economic resource that is expected to be of benefit in the future. Probable future economic benefits obtained as a result of past transactions or events. Anything of value to which the firm has a legal claim. Any owned tangible or intangible object having economic value useful to the owner.
Namespace Glossary of Finance Terms
Critical YES
Name Glossary of Finance Terms
Type Glossary
Definition Contains terms from Finance and Accounting business domain
Namespace Finance Namespace (namespace)
Critical YES
Name Product Type
Type ldmEntity
Definition Product Type classifies a product based upon its inherent characteristics, structure, and the market needs it addresses.
Namespace Product Fundamentals (Logical data model)
Critical YES
(*) Note: concept list can be tailored and extended for specific implementations
BusinessTechnology(logical model)
Technology(physical data) Governance
1
Rule
Application
Technology(apps)
2
3
Concept and Relationship (2/2)
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Two most fundamental concepts in meta360 are Concept and Relationship.
Relationship
Relationship refers to any kind of association between two concepts.
Important considerations: Relationship between two concepts is also called assertion or
ontology triple. Ontology triple consist of subject concept, object concept and
association between them. Associations are represented as verbs. Once you establish relationship between two concepts you can
read it eater way, buy using verb or its opposite.
GlossaryTermbelongs
contains
ObjectConcept
SubjectConcept
Association(verb)
Opposite
meta360 Supported Verbs (*):
(*) Note: verb list can be tailored and extended for specific requirements
Relationship Examples
verb opposite
is associated with is associated with
is a kind of has a subtype
belongs to contains
is a source for is a target for
is a child of has child
is an owner of has owner
is a member of has member
is a subscriber of has subscriber
is a predecessor of has predecessor
is a successor of has successor
Asset (term) belongs Glossary of Finance Terms (glossary)
Glossary of Finance Terms (glossary)
Finance Namespace (meta360 namespace)
belongs
Total Asset (report position)
FRY 9C(report)
belongs
Asset (term) is associated withTotal Asset (report position)
Total Asset (report position)
Col3123(dbColumn)
is a source for
1
2
3
4
5
Automatically created from input files
Manually created by users
Content Organization
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Concept NamespaceIn meta360 world, concepts are stored in containers named namespaces.
Important considerations: Each concept type has his own container type where can be stored (e.g. terms can be
stored only in glossaries, dbcolumns can be stored only in dbTables, etc.). The basic rule is that within the single namespace, the concept name must be unique. meta360 namespaces are top level containers and they have no namespace
associated . Namespaces cannot be nested. Global Namespace is default meta360 namespace that contains users and user groups
and should not be used for other content. NamespaceURL represents full namespace path from the model root to the particular
concept. For example, the namespace for Asset term will be [Finance Namespace.[Glossary of Finance Terms]
Concept Namespace
term glossary
glossary meta360 namespace
taxonomy meta360 namespace
report meta360 namespace
report section report
report position report section
rule meta360 namespace
logical data model meta360 namespace
ldm entity logical data model
ldm attribute ldm entity
application meta360 namespace
database meta360 namespace
db table database
db column db table
data flow meta360 namespace
organization meta360 namespace
user meta360 namespace (Global Namespace)
user group meta360 namespace(Global Namespace)
meta360 concepts and their namespaces (containers):
Finance Namespace (meta360 namespace)
Glossary of Finance Terms
Asset
Data Governance Approach – Just simple as it is…
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meta360 provides innovative “easy-to-implement” data governance approach.
Guiding principles: meta360 has two types of users: standard and admin Standard user can do the following changes:
direct changes for any content that owns change request for content that does not own
Admin user can make direct changes to any content Each user can be assigned to one or many users groups Each concept can be own by one or many users/user groups Concept owners (users or members of user groups) are notified about each of change requests from non-owners. Any user that has ownership assigned to the concept can approve change request related to that particular concept. Change request for concept relationships must be approved by owners of both concepts that participate in the particular relationship
meta360 data governance process Illustration
standard (non-owner)
Term
standard (owner)
admin
Glossary
standard (owner) standard (non-owner)
admin
belongsrequest requestchange
change
change
change
We strongly recommend to assign ownership over the concepts to User Groups rather then to particular user. On that way you can easily assign new owner to multiple concepts by adding user to the user group.
meta360 - The Outcome Illustration - Visualization
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Concept Relationship Diagram Data Flow DiagramTaxonomy Tree Diagram
ER/Database Diagram
meta360 provides “fit for purpose” view over repository content for various business and technical users.
Predefined content
• BIRD (Bank’s Integrated Reporting Dictionary)
• Can be used to accelerate efforts for ECB’s collection of granular credit data and credit risk data (AnaCredit), ECB’s Securities Holdings Statistics (SHS), ECB’s Monetary Financial Institutions’ Balance Sheet Items Statistics (BSI), ECB’s Monetary Financial Institutions’ Interest Rate Statistics (MIR), other statistics, such as the balance of payments and national accounts, additional requirements of the Single Supervisory Mechanism and EBA’s Implementing Technical Standards (ITS), which encompasses Common Reporting (COREP) and Financial Reporting (FINREP)
• FR Y 9C and FR Y 14 reports
• Can be used for US CCAR and BCBS239 regulatory requirements
• Finance and Accounting Glossary
• General glossary of finance and accounting terms
• Insurance Glossary
• General glossary of insurance term
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