What is the difference between Yield and return?

Because investors are very concerned with how well their investments are performing or how they are expected to perform, knowing how to gauge such performance is essential. This makes understanding the difference between yield and return important. 

While both terms are often used to describe the performance of an investment, yield and return are not one and the same thing. Knowing what each measure takes into account and recognizing that each considers different time periods is key.

Return, also referred to as "total return", expresses what an investor has actually earned on an investment during a certain time period in the past. It includes interest, dividends and capital gain (such as an increase in the share price). In other words, return is retrospective, or backward-looking. It describes what an investment has concretely earned.

Yield, on the other hand, is prospective, or forward-looking. Furthermore, it measures the income, such as interest and dividends, that an investment earns and ignores capital gains. This income is taken in the context of a certain time period and then annualized, with the assumption that the interest or dividends will continue to be received at the same rate. Yield is often used to measure bond or debt performance; in most cases, total return will not be the same as the quoted yield due to fluctuations in price. 

Basic information on Products in AX 2012

http://mukesh-ax.blogspot.no/2012/06/product-information-management-ax-2012.html

Swapna Kallu's Blog: Understanding Product structure in AX 2012

Swapna Kallu's Blog: Understanding Product structure in AX 2012: Product structure information is a key aspect of producing a manufactured item.  The product structure is typically called a bill of mate...

Understanding Product structure in AX 2012

Product structure information is a key aspect of producing a manufactured item.  The product structure is typically called a bill of material (BOM) in the context of discrete manufacturing, and a formula in the context of process manufacturing.  These terminology differences have a special significance within Microsoft Dynamics AX 2012, since the production type assigned to a manufactured item (of BOM or Formula) impacts software functionality.  The terms BOM approach andformula approach will be used to differentiate the two approaches. 

This article focuses on process manufacturing scenarios, and how to choose between the BOM approach versus formula approach for modeling product structure.  Many scenarios can be modeled using either approach or a combination of the two approaches, so understanding the functional differences is key to making the right choice.   

The two approaches reflect the design history of Dynamics AX, which initially employed the BOM approach and subsequently added the formula approach.The formula approach supports additional functionality for addressing the requirements of process manufacturing, such as co/by-products, catch weight items, substitute ingredients and formula size considerations.  A combination of the two approaches can be used within one product structure, such as a BOM approach for a parent item and the formula approach for a manufactured component (and vice versa). 

OLTP vs. OLAP

 

OLTP vs. OLAP

We can divide IT systems into transactional (OLTP) and analytical (OLAP). In general we can assume that OLTP systems provide source data to data warehouses, whereas OLAP systems help to analyze it.





- OLTP (On-line Transaction Processing) is characterized by a large number of short on-line transactions (INSERT, UPDATE, DELETE). The main emphasis for OLTP systems is put on very fast query processing, maintaining data integrity in multi-access environments and an effectiveness measured by number of transactions per second. In OLTP database there is detailed and current data, and schema used to store transactional databases is the entity model (usually 3NF).

- OLAP (On-line Analytical Processing) is characterized by relatively low volume of transactions. Queries are often very complex and involve aggregations. For OLAP systems a response time is an effectiveness measure. OLAP applications are widely used by Data Mining techniques. In OLAP database there is aggregated, historical data, stored in multi-dimensional schemas (usually star schema).

AX Extended Architecture