- \n
- Define rules, link them to business processes and make sure your data comply to internal policies and regulations<\/li>\n<\/ul>\n<\/div>\n<\/div>\n
[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
HOPEX Information Architecture Home Page<\/h4>\n
[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14372″ img_size=”full” alignment=”center”][vc_column_text]\n \n \n <\/span>\n <\/span>\n\nTiles provide shortcuts to frequently used features and are customizable by end-users<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Key Features<\/h4>\n
[\/vc_column_text][vc_empty_space height=”30px”][vc_row_inner][vc_column_inner width=”1\/3″][vc_column_text css=”.vc_custom_1596768055304{padding-top: 10px !important;padding-right: 10px !important;padding-bottom: 20px !important;padding-left: 10px !important;background-color: #111924 !important;}”]<\/p>\n
Architect data<\/strong><\/span><\/p>\n
[\/vc_column_text][vc_column_text]<\/p>\n
- \n
- Automatically generate a data dictionary<\/li>\n
- Build a business glossary of enterprise terms<\/li>\n
- Design physical, logical and conceptual data models<\/li>\n
- Automatically connect technical data to business data<\/li>\n<\/ul>\n
[\/vc_column_text][\/vc_column_inner][vc_column_inner width=”1\/3″][vc_column_text css=”.vc_custom_1596768072831{padding-top: 10px !important;padding-right: 10px !important;padding-bottom: 20px !important;padding-left: 10px !important;background-color: #111924 !important;}”]<\/p>\n
Trace data<\/strong><\/span><\/p>\n
[\/vc_column_text][vc_column_text]<\/p>\n
- \n
- Map data lineage and describe the transformations that happen to the data<\/li>\n
- Link data to applications and processes to understand data usage<\/li>\n
- Assess data quality through the six dimensions of data quality<\/li>\n
- Categorize data based on its sensitivity<\/li>\n<\/ul>\n
[\/vc_column_text][\/vc_column_inner][vc_column_inner width=”1\/3″][vc_column_text css=”.vc_custom_1596768085206{padding-top: 10px !important;padding-right: 10px !important;padding-bottom: 20px !important;padding-left: 10px !important;background-color: #111924 !important;}”]<\/p>\n
Govern data<\/strong><\/span><\/p>\n
[\/vc_column_text][vc_column_text]<\/p>\n
- \n
- Assign data governance roles<\/li>\n
- Define collaborative workflows<\/li>\n
- Describe rules required by regulatory bodies<\/li>\n
- Reference regulations including BCBS 239 and Solvency II to ensure compliance<\/li>\n
- Tie rules to business processes to ensure their enforcement<\/li>\n<\/ul>\n
[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Three Layers of Data Modelling<\/h4>\n
[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14375″ img_size=”full” alignment=”center”][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Initialize Data Dictionary<\/h4>\n
[\/vc_column_text][vc_column_text]Generate a data dictionary by extracting information from data source via ODBC[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14376″ img_size=”full” alignment=”center”][vc_column_text]\n \n \n <\/span>\n <\/span>\n\nReverse engineer arac\u0131 veritabanlar\u0131n\u0131 sorunsuz bir \u015fekilde reverse edebilmek i\u00e7in veriler do\u011frudan ODBC \u00fczerinden al\u0131r.<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Create SQL Code<\/h4>\n
[\/vc_column_text][vc_column_text]Create SQL code based on physical items of the HOPEX repository (database, table, column) to a target DBMS format.[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14377″ img_size=”full” alignment=”center”][vc_column_text]\n \n \n <\/span>\n <\/span>\n\nDatabase parameters can be customized either at a global level, or at a detailed level on a column or primary key, depending on the target DBMS.<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Data Lineage<\/h4>\n
[\/vc_column_text][vc_column_text]Describe the transformations that happen to the data. Data lineage diagrams include:<\/p>\n
- \n
- Applications, as well as technologies for external systems.<\/li>\n
- Data origin, processing type, control measurement and subject.<\/li>\n
- Different types of flows: standard and data flows (used when some new Data appear)<\/li>\n
- Definition of where applications are used and by who.<\/li>\n<\/ul>\n
[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14378″ img_size=”full” alignment=”center”][vc_column_text]\n \n \n <\/span>\n <\/span>\n\nMap data lineage to understand how data is transformed<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Data Lineage Initialization<\/h4>\n
[\/vc_column_text][vc_column_text]Based on the data flows existing in the repository, data lineage diagrams can be automatically initialized from a graph report[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14379″ img_size=”full” alignment=”center”][vc_column_text]\n \n \n <\/span>\n <\/span>\n\nGraph report for the data usage of a business concept<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Lineage between business and technical data<\/h4>\n
[\/vc_column_text][vc_column_text]Understand how a business concept and a technical data are tied each other[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14381″ img_size=”full” alignment=”center”][vc_column_text]\n \n \n <\/span>\n <\/span>\n\nEnables users to view links between business glossary and data dictionary<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Data Usage in Applications<\/h4>\n
[\/vc_column_text][vc_column_text]<\/p>\n
- \n
- View how applications use the data of a data dictionary<\/li>\n
- Connect applications and data through data stores.<\/li>\n<\/ul>\n
[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14382″ img_size=”full” alignment=”center”][vc_column_text]\n \n \n <\/span>\n <\/span>\n\nQuickly understand the impacts of change in a data dictionary<\/em><\/p>\n
\n \n \n <\/span>\n <\/span>\n\nProvides traceability from business glossary, data dictionary and data usage in applications<\/em>\u202f<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Business Process Analysis Integration<\/h4>\n
[\/vc_column_text][vc_column_text]Link data and processes through flows or data stores[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14384″ img_size=”full” alignment=”center”][vc_column_text]The concept \u201cTravel Package\u201d is used in \u201cAccount Management\u201d, \u201cTrack orders on internet\u201d and \u201cResearch\u201d processes<\/em><\/p>\n
\n \n \n <\/span>\n <\/span>\n\nUnderstand where data is used in processes to improve compliance to regulations.<\/em><\/p>\n
\n \n \n <\/span>\n <\/span>\n\nUnderstand the business criticality of a data<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Assess Data Quality<\/h4>\n
[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14495″ img_size=”full” alignment=”center”][vc_empty_space height=”30px”][vc_column_text]<\/p>\n
- \n
- Assess data quality under the six dimensions of data quality including Completeness, Uniqueness, Timeliness, Consistency, Validation and Accuracy.<\/li>\n
- Campaigns can be set up to assess data quality by various stakeholders in the organization<\/li>\n<\/ul>\n
\n \n \n <\/span>\n <\/span>\n\nGet a clear understanding of the data quality in your organization<\/em><\/p>\n
\n \n \n <\/span>\n <\/span>\n\nProceed to remediation plans to improve data quality<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Categorize Data<\/h4>\n
[\/vc_column_text][vc_column_text]<\/p>\n
- \n
- Categorize data based on its sensitivity. Define retention period for each data.<\/li>\n
- This feature is common to HOPEX Privacy Management and HOPEX Information Architecture<\/li>\n<\/ul>\n
[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14496″ img_size=”full” alignment=”center”][vc_column_text]\n \n \n <\/span>\n <\/span>\n\nHelps comply with Privacy Management regulations such as GDPR and CCPA <\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Workflows<\/h4>\n
[\/vc_column_text][vc_column_text]<\/p>\n
- \n
- Set up automated workflows between contributors to validate data models and quickly build a repository of data models<\/li>\n
- Workflows are instantiated by data designers or data owners. All the other data contributors can sign off on the validation steps.<\/li>\n
- Default workflows are for: data lineage, business, logical and Physical data models<\/li>\n<\/ul>\n
[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14387″ img_size=”full” alignment=”center”][vc_column_text]\n \n \n <\/span>\n <\/span>\n\nExample of workflow for the validation of data models<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Manage Data Policies<\/h4>\n
[\/vc_column_text][vc_column_text]<\/p>\n
- \n
- Describe business directives and policies.<\/li>\n
- Some standard regulatory requirements are provided out-of-the-box such as BCBS 239 and Solvency II.<\/li>\n<\/ul>\n
[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14388″ img_size=”full” alignment=”center”][vc_column_text]\n \n \n <\/span>\n <\/span>\n\nBCBS239 regulatory requirements<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]<\/p>\n
Monitor Customizable Dashboards<\/h4>\n
[\/vc_column_text][vc_column_text]<\/p>\n
- \n
- Monitor the level of data assets that are constrained by the articles and sections of regulations such as BCBS 239 or Solvency II<\/li>\n
- Monitor the level of completion of the repository, e.g. the percentage of terms with a definition<\/li>\n
- Monitor the progress of validation workflows for Data Lineage maps and data models<\/li>\n<\/ul>\n
[\/vc_column_text][vc_empty_space height=”30px”][vc_single_image image=”14389″ img_size=”full” alignment=”center”][vc_column_text]\n \n \n <\/span>\n <\/span>\n\nMonitor the level of data constrained by regulatory requirements and the percentage of terms with a definition<\/em>[\/vc_column_text][vc_empty_space height=”70px”][vc_column_text]If we need to summarize HOPEX Information Architecture with a single sentence, information systems managers can ensure the correct use of information, minimize deviations at the level of execution, adapt to a layered approach to business asset science, associate information with corporate view and concept, and data models, assets. is the product that provides the tools they need to get awareness reports that show links between attributes and databases.[\/vc_column_text][vc_empty_space height=”50px”][\/vc_column][vc_column width=”1\/4″ enable_sticky=”true” sticky_offset=”100″ css=”.vc_custom_1474589458588{padding-right: 10% !important;padding-left: 10% !important;}”][vc_empty_space height=”50px”][vc_column_text]<\/p>\n
Enterprise Architecture<\/span><\/h6>\n