1 / 8

Data between applications

Integrity. Data between applications. ADMIN. AIS. HRMS. DONNER. RTAD. CRM. Agenda Overview Proposals Action plan. Integrity

miriam
Download Presentation

Data between applications

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Integrity Data between applications ADMIN AIS HRMS DONNER RTAD CRM

  2. Agenda Overview Proposals Action plan

  3. Integrity Data integrity is data that have a complete or whole structure. All characteristics of the data including business rules, rules for how pieces of data relate, dates, definitions and lineage must be correct for data to be complete. ------------------------------------------------------------------------------------------------------------------------- Integrity is a characteristic of data that means that the data was not tampered with, destroyed, or changed in any way while in transit ------------------------------------------------------------------------------------------------------------------------- Assurance that the data are unchanged from creation to reception. ------------------------------------------------------------------------------------------------------------------------- The verification that a message has not changed in transit. ------------------------------------------------------------------------------------------------------------------------- The assurance that data is accurate, correct and valid. ------------------------------------------------------------------------------------------------------------------------- A measure of accuracy based on error detection. ------------------------------------------------------------------------------------------------------------------------- A NOS function supporting error detection, correction, and data redundancy. ------------------------------------------------------------------------------------------------------------------------- Data integrity, in terms of data and network security, is the assurance that information can only be accessed or modified by those authorized to do so. ... ------------------------------------------------------------------------------------------------------------------------- the assurance that information has not been modified between the time it is sent by the sender and received by the intended recipient. ... ------------------------------------------------------------------------------------------------------------------------- Assures document authenticity. Any changes made to the contents of the document will invalidate the signature.

  4. Rule 1 - Avoid duplicating data (3NF ‘Only the key’) • OIC is here to stay • Challenge – Maintaining data integrity/uniformity/credibility/stability across apps • Why – Duplication of data • Data is stored in more than one application but can be changed or captured in any one. • in different formats - on RTAD, ADMIN, CRM, DONOR, HR and more & stored as 1-10, a-x, words, codes. • With different standards – example HR requires Marital status ‘Remarried’ but Admin etc not. • Different minimum requirements • Current modus operandi • OIC Mapped in middleware on change/capture • Direct update (web services) • Shared data (AIS)

  5. Problem • Data integrity/inaccuracy across applications/db’s • Causes: • No control of changes (per application) • lack/ignorance of change process • Undefined • Responsibility and accountability • rules • Processes • Ignorance/no visibility of impact(does it impact other apps?) • No audit • Some logging of errors by subscribers • Informal follow-up procedures(or none at all) • Little/no user involvement/responsibility • No cross-cutting audits of existing data • Inadequate testing

  6. Common validation • Data changes App1 App2 OIC Table/Data Web Service Common error logging Web Service App3 Err Log DB Service desk (Change Management) Table/Data Err App Call

  7. Applic change/Table value change • App, value Changes OIC Xref (readable version) Impact assessment developer RFC Impact /new /old? Auto process (to be determined) Old (new value) New (attr) CM Consultative process user

  8. Yays? Nays? Action plan

More Related