Enhanced governance and control
Our software enables organisations to improve performance across a range of levels:
More effective use of information
Reduced risk of inadvertent mis-reporting
Lower costs associated with enterprise analytics
Greater consistency of metrics across the enterprise
Enhanced productivity of data teams
Improved context for users
Supports complex data architectures
Sources metadata from disparate applications
Automation supports optimisation of analytics apps
Key Drivers and Use Cases
Automated metadata capture and active monitoring of data assets underpins the capabilities of Metonomy software in the support of enterprise analytics governance.
Complex data architectures require a range of controls to monitor and regulate data as it flows through an organisation to the point of use or consumption. Metadata management is a cornerstone to making data fabric or mesh viable.
Improved control is achieved through the identification of anomalies across disparate applications, tracking usage over time and determining the degree of similarity and potential duplication between elements.
The use of software in conjunction with processes, policies and people with specific skills provides a foundation for improved data governance.
Manual analysis of analytics applications is often time-consuming, frequently repetitive and always inefficient. Automation enables data teams to be more effective in optimising existing applications and more productive when migrating to new.
Enriching asset metadata with annotations relating to purpose, ownership or other categories and types provides context to output. Context is necessary for people to be able to understand the nature of the information they are accessing and to use it appropriately.
Automation provides efficiencies throughout the project lifecyle:
Assessment & Inception
Automated metadata capture from source applications. Analysis based on usage and similarity / duplication to support proposed scope for delivery.
Information reviewed with stakeholders to refine scope, e.g. for each application: # of assets used in most recent 18 months (if available), # of assets that have < 90% similarity (or whatever the threshold to be sufficiently unique). Factors such as business priority of assets (e.g. regulatory) and key business processes to be supported also need to be considered.
Identification of data sets that are needed to support in-scope dashboards, reports, analyses & alerts.
The process of defining scope will be evidence-based, the result of consultation with key stakeholders and undertaken more efficiently via automation than would be the case otherwise.
In-scope assets to be tagged and tracked, e.g. assign status and resource for as-is application.
Metadata acquired from analytics assets as they are developed in the target environment. Information is assgned to support delivery such as status and responsible resources.
To-be assets analysed for accuracy through development and test activities.
Captured metadata & applied annotations used to produce progress reports based on as-is and to-be asset status.
To-be analytics assets enriched with contextual metadata, e.g. purpose, owner, SME, verification.
Operations, Support & Maintenance
Annotations used to certify status of analytics assets, e.g. self-service dashboard approved by central IT team.
Analysis module used to search, explore and inspect assets for any issue reported.
Comparison and Usage modules employed to monitor asset inventory and identify & address emerging report sprawl.
Contextual metadata applied and maintained, e.g. ensure complete for new assets; owners & SMEs change over time.
Impact of proposed change on analytics assets assessed efficiently via automation.
Metadata are acquired from applications via Connectors using the most appropriate method supported by the host vendor for the product, e.g. web services REST APIs, SOAP, SDKs or XML. A range of connectors is available for product suites provided by software companies including Oracle BI, Microsoft, SAP, IBM, Qlik, Tableau and others.
We prioritise development of additional connectors based on the needs of our clients.
Vendor Product Product Module
IBM Cognos ReportNet
JasperSoft JasperReports iReports
Microsoft Power BI Dashboard Power BI Files
Microsoft Power BI Report Server Power BI Application Elements
Microsoft Power BI Report Server Power BI Catalog Items
Microsoft Power BI Service Power BI Application Elements
Microsoft Power BI Service Activity Events
Microsoft SQL Server Integration Services Packages
Microsoft SQL Server Reporting Services Reports
Microsoft SQL Server Database Engine
Oracle Business Intelligence Enterprise Edition BI ACL
Oracle Business Intelligence Enterprise Edition BI Analysis
Oracle Business Intelligence Enterprise Edition BI Dashboard Prompts
Oracle Business Intelligence Enterprise Edition BI Dashboard
Oracle Business Intelligence Enterprise Edition BI Publisher
Oracle Business Intelligence Enterprise Edition BI Server
Qlik Qlik Sense Qlik Sense Desktop
Qlik Qlik View Qvw Documents
SAP BusinessObjects Data Foundation Layer
SAP BusinessObjects Universe
SAP BusinessObjects Web Intelligence Reports
Salesforce Tableau Tableau Desktop
Salesforce Tableau Tableau Server + Online
Eclipse BIRT / Actuate Report
CSV JSON XML