I difficulties in managing data exponential increase

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high data quality) is becoming increasingly difficult. I. Difficulties in Managing Data Exponential increase in data : Data are increased exponentially. The historical data must be stored for long time and new data are created and stored rapidly. Data are increased not only in terms of the number or amount of data, but also in terms of the size of data due to the advanced technology in multimedia and broadband communication. Scattered Data : Data are scattered all over the organizations and used by people from many departments. Data are stored in many different machines in various formats. Diverse Sources : Data come from different sources. Some come from internal sources (such as corporate database) and others come from external sources (clients, commercial databases, government databases, and government reports). Some data are created by personal sources (such as opinions in blogs). Some examples of data sources Credit card swipes: credit card purchasing data is created when a credit card is used to purchase goods and services. This data can be used to analyze customers’ spending patterns. RFID (Radio-frequency identification) tags: is the use of an object applied to or incorporated into a product, animal, or person for the purpose of identification and tracking using radio waves. RFID is used in enterprise supply chain management to improve the efficiency of inventory tracking and management. As such, the use of RFID generate inventory tracking data, which can be used in many different departments of organizations (operations, logistics, and marketing). Digital video surveillance E-mails, Blogs, Wikis, podcasts, videocasts 2 2 Excerpt from Gallaugher textbook ( ) 2
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Clickstream data which is generated when users visit a website and click on the links on the websites. It provides a trail of the users’ activities on the website which is used to understand user’s browsing pattern and can be used to predict user behavior. Radiology scans create image (e.g. X-ray, CT scanner) and video (ultrasound) data. Data decay : Data decay over time. For example, the contact information of people can be easily outdated because some people move but do not update their contact information. Companies change their names or go out of business. Employees can be promoted, fired, or move to other companies. Unstructured data : many of newly created data are not structured. Data in blogs, podcasts, videocasts, and wireless sensors (digital images, video clips, sound packets, and mp3 files) are the example of un-structured data. These data cannot easily be represented in a traditional text-based computer record. In addition, data security, quality and integrity are becoming very important. Since legal requirements with regards to data are different among countries and industries and keep changing, a business has to ensure that its data security, quality and integrity are as per the applicable standards.
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