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Discover metadata in packaged applications

Home | Services | Metadata services | Discover metadata in packaged applications

Unpack, packaged applications!

Begin with the metadata concealed within packaged applications – discover what lies beneath the opacity barrier. Industry-standard ERP & CRM packages from global vendors have large, complex, impenetrable data structures; opaque table & field names which can drain your resources & budget due to:

  • lack of ‘business-friendly’ metadata, variables, table names or data structures;
  • inability to access the data dictionary – unhelpful if you intend to do data cataloguing or inventory;
  • metadata ‘hidden’ behind APIs;
  • many and complex tables (as many as 90,000) make it difficult to locate target metadata without discovery tools;
  • the need to relate, compare & provision data structures to your wider environment e.g. how many fields, in which instances, are called ‘customer’, and how many do you have, want or need?
  • the risk of non-compliance arising from failure to locate or curate personally identifiable data (PII) in complex, big data CRM or ERP systems;
  • data model gaps & inconsistencies stalling migration, consolidation or integration projects;
  • empty cells negatively impacting ETL routines & derailing data migration timelines;
  • the inability to subset the metadata in big data volumes or complex databases into more manageable chunks.

The upside of tackling packaged application metadata first, is that it is designed for applications, not people, and therefore likely to be of the machine-readable variety and easily usable once you can actually find out what’s there.

Data dictionaries, sibling rivalry

Many ERP or CRM packaged applications do not provide helpful, accessible or business-friendly data dictionaries or variable descriptions. The internal data structures and naming-conventions are application- not business-centric. This opacity may be good for security but it can be a time-consuming obstacle if you need to understand their data structures for other projects. Safyr makes it easy to discover not just the metadata, but the dictionaries as well.

You can request a free packaged application data model from Silwood Technology. The following are available:

  1. SAP;
  2. Salesforce;
  3. JD Edwards;
  4. Oracle E-Business Suite;
  5. Peoplesoft;
  6. Siebel;
  7. MS Dynamics AX 2012;
  8. MS Dynamics 365.

Due to the nature of cloud infrastructure, modern CRMs may also have several cloud instances each which you may need to compare, or view – to establish peer or sibling customer data relationships. This is vital if you want a single customer profile across clouds in order to provide your end customer with a unified experience! Safyr helps you compare SalesForce & SAP instances and find out which data you need.

Tool up with Safyr

If you don’t want your metadata discovery to be a generous exercise in billable time, deploy Safyr to reduce the pain of penetrating the opacity barrier in packaged applications.

Specialist tools like Safyr, which offer easy visibility of metadata, significantly reduce the risk of project delays, cost overruns, under-delivery or project cancellation:

  • reducing the time, cost & effort of liberating metadata from packaged applications (by as much as 90%);
  • overcoming the barrier of opaque table & variable names;
  • improving accuracy, usability & compliance;
  • retrieving metadata systematically from the application layer of each package;
  • sub-setting metadata into manageable chunks;
  • shortening time to value in ERP/CRM projects, integration or migration.

Incorvus is a Safyr Reseller partner. Incorvus team brings to bear its extensive experience of industry-standard global technologies and data troubleshooting.

THE BENEFITS OF SAFYR

Safyr® significantly shortens time to value for projects involving ERP metadata.

If your project involves data from standard enterprise ERP and CRM packages, Safyr reduces the time, cost and resources absorbed by ERP metadata discovery by as much as 90% whilst at the same time improving accuracy and compliance.

  • Realise project benefits faster;
  • Reduce cost of source data discovery;
  • Reduce risk of inaccurate data;
  • Reduce risk of non-compliant data.

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