Distributor Sales

Distributor sales also termed as indirect sales or secondary sales that happen between the distributor and retailer often get untracked. Many companies invest a good amount of money and resources in recording the Primary sales (Company to the distributors) but doesn't care much about the secondary or the distributor sales.

Distributor sales is useful to track and do a more deeper market analysis, projections and reliable forecasts, resulting in taking better decisions for companies growth. Distributor sales also termed as sales per point of distribution.

Market sales data

Considering the tough competition among companies almost in all the industries today, one of the key to becoming a leader is in-depth coverage of your market and the ability to get data from the bottom of the market like retailer, sub-distributors etc. Most of the ERP's don't actually cover this kind of data. They are mostly concerned about the primary sales (Company to Distributor) but miss-out on secondary sales (Distributor to Retailer)

A Secondary sales tracking information that gets from the Distributor/retailer level enhances the companies Business Intelligence capabilities and benefits them in taking right decision at the right time.

Eliminating Join Query

For many people trying to optimize the performance of their queries the JOIN clause is one of the biggest bottle necks. In RDBMS an SQL JOIN combines records from two or more tables in a database. The result can be saved as a table or used as is. A JOIN is a means for combining fields from two tables by using values common to each other. These queries can get real complex and are infamous for consuming huge amount of time. Eliminating Join query is real tough in RDBMS though you may have some ways of doing that but it will again result in taking more time.
One of the option to consider is using a Schemaless database where as there are no tables in the first place so there isn't any question of joining the tables itself. Using Join or not, Queries that involve complex set of results will not have any effect on the performance and will be executed as any other ordinary query. The structure of the database itself eliminates Join query completely.

Eliminating Data Modeling

In a Software Development Life Cycle Data Modeling is a stage where once the requirements are completely gathered they are represented using Data modeling techniques and conceptual data models are made. The implementation of these conceptual data models is the logical data modeling. However, systems and interfaces often cost more than they should, to build, operate, and maintain. They may also constrain the business rather than support it. They lack the ability to grow along with the business needs and even if they do it takes a huge amount of time and resources to map the changing requirements.

Another way to over come this problem where the systems can evolve along with the business and its less cumbersome to make a change is using a schemaless database where there is no concept of Data Modeling as there is no schema itself. This gives the power and agility for a system to perform and adapt to the changing ways of the business.

Semantic Storage

Sir Tim Berners-Lee's vision of the Web as a universal medium for data, information, and knowledge exchange. In which the meaning (semantics) of information and services is defined, making it possible to understand and satisfy the requests of people and machines.

There have been many initiatives in this regard, one of them is using Resource Descriptive Framework (RDF) model or the Metadata Data Model. It is based upon the idea of making statements about resources in the form of subject-verb-object expressions. These expressions are known as triples in RDF terminology. The subject denotes the resource, and the verb denotes traits or aspects of the resource and expresses a relationship between the subject and the object. Brainwave Technology's Semantic Database uses the RDF model and is a complete schemaless database.





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