HealthcareMetadata

It's more typical to keep older versions of your document inside your current revision (either as JSON or, often, as an attachment). For the JSON case; { "_id":"foo", "_rev":"3-fsfsfsdf", "foo":"current value of foo", "history": { "2": { "foo":"previous version of foo" }, "1": { "foo":"initial version of foo" } } }

t's often simpler to push the full old version of the document into an attachment instead. This pattern is common enough that CouchDB ships with a library, jquery.couch.js, that implements it (in the saveDoc(doc) function).

Ways to implement data versioning in MongoDB

will be used infrequently will be used all at once to present it in a "time machine" fashion there won't be more versions than few hundred to a single record. history won't expire.

My personal approach would be to store diffs. Because the display of these diffs is really a special action, I would put the diffs in a different "history" collection.

Modeling friend of friend relationships in MongoDB

"When a document's stored value for a index key field is an array, MongoDB indexes each element of the array. See the Multikeys page for more information." so to find all of "alex"'s friends I can just do: db.user.find( { 'friends' : '4e77bb3b8a3e000000004f7a'});

There is however Morphia, an Object Document Mapper for MongoDB + Java which closely emulates the JPA model but using MongoDB appropriate semantics

DataNucleus already supports MongoDB, for JPA and JDO, the standardised APIs in Java.

clipseLink is planning support for MongoDB from JPA.

SAP business objects as data source

The only way I know for sure you can connect Business Objects and Webi is using their products.

Toreo Data integrates SAP Business Objects with Tableau so end users can easily access and analyze data.

A data dictionary, or metadata repository, as defined in the IBM Dictionary of Computing, is a "centralized repository of information about data such as meaning, relationships to other data, origin, usage, and format."[1]

“Master Data is your business critical data that is stored in disparate systems spread across your Enterprise.”

Parties: represents all parties the enterprise conducts business with such as customers, prospects, individuals, suppliers, partners, etc. Places: represents the physical places and their segmentations such as geographies, locations, subsidiaries, sites, areas, zones, etc. Things: usually represents what the enterprise actually sells such as products, services, packages, items, financial services, etc. Financial and Organizational: represents all roll-up hierarchies used in many places for reporting and accounting purposes such as organization structures, sales territories, chart of accounts, cost centers, business units, profit centers, price lists, etc.

Transactional Data such as purchase orders, invoices or financial statements, is not usually considered master data since it actually registers a “fact” that happened at a certain point in time.

The choice between deploying relational tables or OLAP cubes is not a trivial matter. Weigh these 34 pros and cons of each approach early in the design of your extract-transform-load system.