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meta360 - enterprise data governance and metadata management

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meta360 is an enterprise scale, industry agnostic, 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, as well as powerful visualization capabilities to easily navigate through metadata content and use the information on the most effective way. meta360 is industry agnostic and can be used as a key component in various data management initiatives, including, but not limited to: data governance,data lineage, metadata management, data quality, MDM, data integration, analytics, etc.
Features:
1) Innovative, matured and proven approach for data governance operationalization
2)Industry agnostic, can be used in various industries (FSI, communications, life science, etc.)
3)Easy to implement – up and running within 6 weeks, even for the large organizations
4)Cloud based (Amazon Cloud) – significantly reduces operational costs
5)Easy content contribution – CSV and JSON file import, manual entry (can be used as primary tool for particular concept types)
6)Exceptional user experience – visually attractive and easy-to-use for both, business and technical users.
6)Responsive, works on all devices
7)meta 360 is built by using MEAN stack

Publicado en: Datos y análisis

meta360 - enterprise data governance and metadata management

  1. 1. meta360 enterprise data governance and metadata tool Copyright ©2016 Global Data Store LLC9/8/2016 #gameChanger #simple #clean #ultrafast #visual #real360view #quickImplementation
  2. 2. 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
  3. 3. 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 Acquisition Integration Store Consumption Technology Architecture
  4. 4. Crossing the Chasm – Authentic Data Management Use Cases Copyright ©2016 Global Data Store LLC 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 Compliance Heavily 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 AnaCredit implementation 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
  5. 5. What is meta360? Copyright ©2016 Global Data Store LLC 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.
  6. 6. meta360 differentiation Copyright ©2016 Global Data Store LLC There are 4 clear differentiators of meta360 Easy to use Easy 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.
  7. 7. meta360 Fundamentals Copyright ©2016 Global Data Store LLC
  8. 8. Concept and Relationship (1/2) Copyright ©2016 Global Data Store LLC 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 Taxonomy Business 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 Business Technology (logical model) Technology (physical data) Governance 1 Rule Application Technology (apps) 2 3
  9. 9. Concept and Relationship (2/2) Copyright ©2016 Global Data Store LLC 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. GlossaryTerm belongs contains Object Concept Subject Concept 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 with Total 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
  10. 10. Content Organization Copyright ©2016 Global Data Store LLC Concept Namespace In 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
  11. 11. Data Governance Approach – Just simple as it is… Copyright ©2016 Global Data Store LLC 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.
  12. 12. meta360 - The Outcome Illustration - Visualization Copyright ©2016 Global Data Store LLC 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.
  13. 13. 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 Copyright ©2016 Global Data Store LLC
  14. 14. Looking for Live DEMO Copyright ©2016 Global Data Store LLC contact us on: meta360@globaldatastore.com

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