What is Data Management? What are some of the difficulties that organizations face when managing data? How can data warehousing, online transactional databases and data mining assist with these difficulties?
May 18, 2014
Kendra L Thompson
ITEC 6111: Information Technology in the Organization
Professor Mello Star
Just as cars need fuel, so does organizations, when it comes to data it serves as fuel to many organizations. Without the use of data, organizations would probably “go under” pretty quickly, since mainly every process within the organization is dependent on its data. Data is a mission-critical because it (Control, 2008): Influences the decision making process
Gives risk management power
Offer understanding into products, services, markets, counterparties and customers With that in mind, organizations should always cease to ensure that their data is eagerly managed. With the market changing, the process of data management is becoming more complex and the capacity of data to be managed is steadily increasing, this is sometimes referred to as “big data”. Big data is used in understanding organizations and their decision making process; when decisions are made, they are based on complex data transactions which have become difficult to the system that are using basic database and warehouse management systems (Vael, 2013). This causes many data management difficulties such as an increase in data, immature decision making, legal issues and data securing and integrity to name a few, but they can easily be reduced or resolved by the use of the following:
1. Data warehousing, allows organizations to generate and combined a view of its readiness data for analysis, reporting and decision making
2. Online Transactional Databases, utilize applications that manage changing data, performing real-time data transactions.
3. Data mining, the practice of encapsulating analyzed data from various perspectives into useful information. In data warehousing, data is extracted from various sources as it is produced, making it easier and efficient for queries to be run over the data; it is then revolved into information for reporting for all levels of employees throughout the organization to understand, present and record (Lam, 2012). Data warehousing has help organizations with minimizing it’s increased in data along with data being stored in different formats as well as data scattered across the organization; by allowing employees to have access to data at their fingertips, it has revolutionized the way organizations make decisions. Online transactional databases has proven to be the most efficient way meet today’s organizational requirements such as high availability, high performance and scalability (Mellanox, 2013).
Online transactional databases are used to assist with data reliability and relevancy; this process reduces the organization process execution time as well as storage cost. Data mining is predominantly used by organizations and companies with a sturdy consumer focus, mainly retail, communication, marketing and financial organizations. With data mining, retailers are able to use the data to develop products and promotions to target specific customer segments. Data mining is made up of five major components: Extract, alter and load transaction data on the data warehousing system Manage and store the data in a multi-dimensional database system Allow business analysts and technology professionals to have access to data Utilize application system to analyze data.
Present data in a easily read format, such as tables and graphs With data mining, organizations are able to transfer data without worry about legal issues arising; it also reduces the risk of data privacy and integrity (Alexander, 2014).
In conclusion, data management is important to any organizational structure and it is a vital part of the company’s growth and development. With the difficulties that organizations face with managing their data, they can look at the use of online transactional databases, data warehouses, and data mining. Although it may not solve the issue completely; it sure will reduce the number of issues and its impact to the organization.
Alexander, D. (2014). Data Mining.
Control, A. (2008). Asset Control. Retrieved 05 18, 2014, from What Is Data Management: http://www.asset-control.com/data_management/what_is_data_management.html Lam, V. (2012). Information Builders. Retrieved 05 18, 2014, from Data Warehousing (Data Warehouse) : http://www.informationbuilders.com/data-warehousing Mellanox. (2013). Mellanox Technologies. Retrieved 05 18, 2014, from Online Transaction Database: http://www.mellanox.com/page/online_transaction_database Vael, M. (2013, June). ComputerWeekly.com. Retrieved 05 18, 2014, from How to manage big data and reap the benefits: http://www.computerweekly.com/opinion/How-to-manage-big-data-and-reap-the-benefits
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