1.Mostly 90% of the cases companies using BI tools get profited by using the reports created by these tools.For example Suppose I have daily transactional data of a store selling various products along with the customer details.By using Business Intelligence tools over this data this raw data can be converted into various decision making reports and it may benifit the store as well as the company for a particular product as in following ways
a) Forecasting: With the data collected above and analysing it by various BI tools one can forecast the position of their product in coming time, for example by using BI tools we can compute the number of units of a particular product being sold in a particular month and suppose the resultant reports are showing us a downtrend of the sales i.e the sale is descreasing every month .To prevent the loss in future the company can make a decision either to reduce the units manufacturing or to add some feature into it to make it good .In this way we can do forecasting of the products which in turn can lead us company’s good risk management
b) Strategic decisions: By doing the analysis on our previous data we can also compute which products are frequently sold together .For example from our raw data by using BI on it we can make out that a toothbrush is frequently getting sold whenever a toothpaste gets sold .From this result the company can start various offers on the combo pack of it or even can start various advertisements to showcase both of them together which in turn can increase sales of the comapny.
2.) For a small Business BI is not recommended because it comes with a good amount of cost .Since Business Inteligence is a full flow from capturing data to generating reports.Each step in the flow costs a considerable amount of cost.
The most vital step of any Business Intelligence process is data ,as this is the foundation to any BI process.If the data to be considered is local i.e we have to do analysis of our own data then this part can be little cost effective but if we have to see the market trends then the data required is not local ,it has to purchased from other sources and purchasing data can cost a very huge amount of money depending on criticality of data.
After getting data it needs to be processed through various tools like data cleaning tools ,ETL tools,data refining tools and finally reporitng tools. Each tool comes with its own price and can vary from the company to company providing it.For example for a mid level company a BI tool kit can range from 1000$ to 2100$.Moreover there are some hidden costs also like Customization cost,data storage cost, resources and time ,training cost and maintaince cost.
3.) More amount of data is always more useful for decision making purposes .Usually in datawarehousing and for decision making reports we always analyse a large amount of data because it has to show us the trends .We cant make a strategy based on a month’s data.For a better BI implementation large amount of data is must.Taking ahead previous example of store’ transactional data ,we cant stop a product manufacturing by seeing the downtrend of 2 or 3 months .Since this a very critical decision for a company to stop their product it has to be solid reason and proof behind it for which we have to consider more data to genreate the reports.
In lower level also while deciding the prices of products we have to take into consideration years of data and not days or months.