8 Page paper due in 10 hours Sharply ( No Plagiarism Please)
RUNNING HEAD: ORGANIZATIONAL PROBLEMS 1
Running Head: Organizational Problem 2
ORGANIZATIONAL PROBLEMS
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Introduction
I was privileged to work with several companies but I noticed a challenge in my previous company. It was facing data warehouse challenges, it had problem in tracing the ongoing operations and historical performance. This made it difficulty in giving business users and analysts' information regarding annual and quarterly sales, business trends and customer behavior. Regardless of the emergency of big data technologies such as Hadoop, the organization had not realized the need to analyze and capture data from different sources so as to remain relevant in the business environment. In coming up with the data warehouse the organization would need to analyze the two options available, that is the departmental or enterprise- wide (Dishek Mankad 2014).
The data warehouse concept is generally simple, reasons being that data can regularly be extracted from the systems of operation that provide support to the business are then copied to a system that is specialized. The data warehouse would then be utilized for reporting and analysis via business intelligence, portals, analytical tools, reporting and dashboards.
A number of conditions indicated that the organization was in great need of a data warehouse; it was faced with difficulties when it came to effective reporting concerning business activities because the data could not be easily availed. Different groups and departments would copy data separately in spreadsheets that are inconsistent with one another. There was a lack of surety concerning data accuracy which made business managers and corporate executives to question the report's veracity. Reports against databases of production took too long to process leading to extension of transaction data.
With a data warehouse that is properly implemented, it will be easy for the organization to answer some questions accurately, such as to why things are the way they are. Data availability is improved by warehousing because data collection is from disparate sources and locations in a repository that is central. Workflows of operation became quite efficient because the activity of analysis is put into a separate system. In the process of moving so as to end up in the warehouse, data is transformed, cleansed and evaluated; this translates into quality information in their reports which are extracted from the warehouse.
Their various easy ways, in which new customers can be “bought”, the first method is through advertising where the entrepreneur confidence those customers will get value for their money. It not only helps in passing messages to the targeted customers, but it’s also an opportunity to showcase the value that the customers will enjoy. For instance, the use of a television will be the most expensive method, but if basing of the target is done on programming as opposed to networks and channels.Where ads are placed in an outlet that is more specific such as "Cooking with Joe” opposed to a cooking network campaign. Radio is another alternative where programming and formats can be targeted selectively.
Literature review
Research literature was obtained from Dishek Mankad, Preyash Dholakia, Dahemi-Anand. Disk Mankad argued that the industry of warehousing is a booming one with many research problems that are interesting. He discussed on the usage and design of a warehouse, he availed a number of approaches to the process of data warehouse usage and design as well as the involved steps. The construction of a warehouse can utilize a bottom-down approach, top down approach or combine the two approaches. His findings indicated that business productivity is enhanced by warehouse because a business organization is in a position to efficiently and quickly gather information that gives the organization an accurate description. The data warehouse will again facilitate the management of customer relationship because it offers a consistent view in relation to the view across all business lines, all markets and all departments. Data warehouse brings about the reduction of cost, by tracking exceptions, patterns and trends over a long duration. An analysis framework for a business will first require that one first knows the business needs. Constructing a complex and large information system is similar the construction of a complex and large house in which the builder and architect differ in their views. Their views are then combined to come up with a framework that is complex representing implementer’s information, builder – driven, bottom- top or business- driven and the top- down (Dishek Mankad, 2013).
Preyash Dholakia based his research inoverviewing the existing use and the art state of warehouse usage and state in presenting data.Discussions were held regarding the framework of business analysis for the design of warehouse process and the multidimensional mining of data. The data warehousing idea is quite simple, it’s very crucial to have data warehouse prepared Appling the right process and design methodology. The reason being that warehousing provides users with summarized, organized and data that is in large amounts. This provides opportunity for mining of data. Apart from recording details regarding any transaction, warehouse in addition stores the transaction summary, according to every item for every summarized or each branch to summarized data of higher level which lay a strong base for a data mining that is successful. Of most importance, deletion of data from the warehouse is never done and that updating of the warehouse is done when in offline state. For this reason, data warehouses are given the view of read-only databases, which offers the user satisfaction by providing query response analysis in a short time. Again the need for a management technique that is advanced does not arise as the case with operational applications. Given a read-only mode is the manner in which data warehouse operates, its solution, which is provided in a specific logical design is quite different from those applied in the operational databases. For example, the implementation of data warehouse relational is that normalization of tables can be done up to the partial normalized table which improves performance.
In a warehouse, the quality of data is very important; many tools of data mining need to concentrate on cleansed data, consistent and integrated data, which demand preprocessing steps in data transformation, data integration and cleansing of costly data.
The second, fourth and fifth research finding are common in that they try to examine how the history of electricity usage and other inputs can help in planning power needs of business organizations and create room for them to set higher prices. They report that data should actually be included as one of the factors of production, along with capital, labor and land. Their general finding indicates that big data improve the performance of business and that many companies are ready to invest in big data. The findings are that many executives in business organizations have believe that Big Data is a necessary area of investment. Their considerations are that their companies are data driven and that day to day making of decisions and strategy of their business is underpinned by analysis and collection of data. The use of hard analytic information on coming up with management decisions has had a negative impact on many organizations and that the large data volumes collected by many businesses make decision making difficult.
Getting new customers can in a real sense be referred to buying of new customers. This is because, if one realizes the amount they invest in terms of money or time, they will start to make sound decisions on where to put such resources.This practice will be of greater importance to those who own new business, who in most cases not only face means that is more limited, but also fail to get profit as a result of a customer that they have newly acquired until the customer make their 5th of 6th purchase. And so new business owners must be very careful on how they spend their limited resources in an effort to achieve repeated purchase from a customer.
Their various easy ways, in which new customers can be “bought”, the first method is through advertising where the entrepreneur confidence those customers will get value for their money. It not only help in passing messages to the targeted customers, but it’s also an opportunity to showcase the value that the customers will enjoy. For instance, the use of a television will be the most expensive method, but if basing of the target is done on programming as opposed to networks and channels.Where ads are placed in an outlet that is more specific such as "Cooking with Joe” opposed to a cooking network campaign. Radio is another alternative where programming and formats can be targeted selectively. Despite dwindling of newspaper subscribership in the recent years, it is still a reliable method which can be used to attract new customers depending on the market. For instance, if one wants to target people at the age of 55 years and above, niche publications or community papers can be considered since old people use them to get informed (Soukhoroukova et al, 2012).
All the studies I selected were normally distributed, this is because all the factors required to indicate the importance of data warehouse were spread uniformly
Easy and smart ways to get customers include referrals and networking, landing referrals from past business or networking associations is not only a cheap way to pick up businesses that are new. But a method in which customers possessing high retention rates can be picked up, this kind of customers also has the tendency of purchasing a lot within a given time duration and they also act as referral sources for other customers. Teaming up through what can be referred to as an arrangement of “host-beneficiary” is another method. This is together with others methods such as teaming up and strategic alliances (Prahalad, 2013).
In conclusion, there was neither type one error, nor type two error in any of the studies I read. To avoid these errors the researchers developed a clear topic of study and that the variables to be used in the study were simple. This made development of research question easy task and hence avoiding the errors was easy
Reference
Mr. Dishek Mankad, M.C.A., B.R.Patel Institute of Computer Application[MCA Progrm], Dahemi-Anand ,
Correspondence Author – Mr. Dishek Mankad, M.C.A., B.R.Patel Institute of Computer Application[MCA Progrm], Dahemi-Anand , ,
Mr.Preyash Dholakia, M.C.A.,K.S.K.V Kachchh University,Bhuj andGattorna, John. Dynamic supply chains. Pearson Education Limited, 2015.
Prahalad, Coimbatore Krishna, and Venkat Ramaswamy. The future of competition: Co-creating unique value with customers. Harvard Business Press, 2013.
Soukhoroukova, Arina; Martin Spann; Skiera, Bernd (2012):Sourcing, Filtering, and Evaluating New Product Ideas: An Empirical Exploration of the Performance of Idea Markets erschienen in: Journal of Product Innovation Management, 29(1), 100-112