Business Intelligence
- Text mining is a procedure for acquiring important data from document collections by identification and investigation of fascinating trends. Text mining has varied features, in acquisition of information, the discovery engines looks into the corpus every time a query is created hence it has the ability of getting new relationships and network nodes which were not initially recognized.
Text mining is similarly able to look for “undiscovered public knowledge” which is a set of massive texts which is accessible by the public and hard to actualize. Currently, text mining is not restricted to analyzing existing information (Ho 2009). However, it may be acquired through injecting open-ended tools in surveys. Moreover, text mining is the structures and semi-structured data.
Text mining is composed of three steps; extraction which is the acquisition of information, there is also categorization which is the grouping and is normally controlled by the data and iterative, precisely, certain concepts are proposed depending on the prior outcome of the text tends and there is concept linkage.
The complexities of mining textual data compared to numerical data is based on three aspects; the form of data type which are heterogeneous, the schema of the database being quite unaware and heterogeneous and the size of the records being massive and time wasting to assess.
- The Offco Limited manufactures and sells products. The company has developed well and requires advancement in its operability. The CEO sees negative issues if certain matters are not sorted out. The company is facing certain issues like the freedom of every business unit, decentralized operability, unable to share information to several other business units and systems. The significant benefits that the company acquires from looking into their clients are the competitive business, the behavior change and client development. The ability to note this is vital to organizations. The customer relationship management is an application that extensively handles client correlations. Organizations that are dealt in clients do much better when put in place a responsive technique which shows client value by issuing answers ad willing to precise needs for a person, to a level that they correlate well with others. When one is able to note the typology of the clients, the strategic value which is connected to the clients and the benefits of the client management strategy company, it is possible that the company may acquire benefits from getting acquitted to their clients. This is vital to an organization as it gives it the ability to look into and allocate sufficient resources where they are required. Additionally, the Offco Ltd Company being a data warehouse leaves room for putting to work the customer relationship management in the coming times. The characteristics of the data warehouse are varied among them being;
They are subject oriented; they are grouped according to subjects like goods and sales which offer the management with a picture that involves all and varied it from the operational database that is product oriented and basically handles processes that change the database. There is also integration of data as data is kept, they are hence consistent. In terms of time variance, it is vital as it assists in forecast and decision making. Consequently, the data warehouse is nonvolatile in that users are not able to update or alter data as they are connected to the warehouse (Lapluea 2012). It hence handles data entry.
It is through these features that the data warehouse is a vital back up tool that companies are able to out to work. The benefits that may be accrued may be direct or indirect.
- The quantitative information that is presented by the “Executive Dashboard” is made in comparison to the present and the previous year (Dundas 2012). In the margin variance the previous year is quite unstable with the least being in October 2009 and the highest in February 2010. The present year saw a more stable margin variance. The expenses were quite high the present year than the previous year. However the revenues in the present year was quite year when compared to the previous year. The sales distribution has been higher in North America. Its support expense has been low when compared to the operational expenses. The margin variance is related to the expenses that have been incurred by the sales while inversely related to the revenue acquired. With an increase in the sales cost or expenses it increases the margin variance trend. These impacts negatively on the revenue acquired and vice versa.
Report of the performance of different products
The objective of this report is to focus on the performance of the different products in sales; Ardintic Dl, Elenci DX, Potilo LX and Orena II.
The overview of the sales shows that the audio and video product in January, February and May 2010 were able to reach the set target while in March 2010 the audio and video product were not able to reach the set target of $40, 000. In precise distribution, the January 2010 sales was largely attributed to the sale of Orena II followed by the Ardintic DL while lowly by Elenci DX this was noted to be the same in February, March and April while in May 2010 Ardintic DL and Pontilo LX contributed low sales.
Discussion
The sale of the Audio products was noted to be quite high when compared to the Video products; the audio product having a quotation of 132 to the videos 70. The audio sales are hence more profitable to sale bringing in more revenue approximately $20, 000. This may be attributed to a wide range of things some of them being preference, cost and good promotion mechanism that have been attributed to it. The video sales averaged around $10, 000 it therefore needs leads to a drop in the margin variance.
Conclusion
The level of sales is highly dependent on the margin variance trend which when it is high the margin variance is high and a drop may be attributed to high cost hence low sales.
Reference
Dundas, 2012, Executive DashBoard, acquired from <http://dundas.com/dashboard/online-examples/demos/Executive-Dashboard.aspx>
Ho C, 2009, Merits and characteristics of text mining, acquired from <http://creative-wisdom.com>
Lapluea T, 2012, “Why Enterprise Data Warehouse?”: Data Warehousing Development at Offco Ltd, acquired from <http://warwick.academia.edu/TanapanLapluea/Papers/135092/_Why_Enterprise_Data_Warehouse_Data_Warehousing_Development_at_Offco_Ltd>
