The Evolution of Data and Database Migration Large scale projects such as the merging of multiple sites, green IT initiatives, virtualization projects, database server consolidation and the cycle of technology refreshes are common in the database world. A common theme throughout all of these is the migration of data. From a database management perspective, data migration has traditionally been treated as an exception to normal operations. Data migration also seems to coincide with unforeseen difficulties that lead to extended downtime and the need to cancel, roll back and defer the activity. In larger environments, data migration is no longer an intermittent distraction but a regular activity that expends an increasing number of organization hours. As with apparently everything else related to infrastructure, there are many technology options from which to choose. Selecting the correct approach is highly dependent on infrastructure limitations, data and platforms types, and time constraints and staff capabilities. No longer is the best practice the use of scripts, when there are many commercially available software packages that can ease this task. According to Rob Karel, principal analyst with Cambridge, Massachusetts based Forrester Research Inc., using the custom scripting approach for migrating data to today's data-centric applications leaves one fatal flaw. (Smalltree) "A custom script is not going to do anything about garbage data, it's just going to move it," Karel explained. (Smalltree)
Data Analytics has significantly grown in less than two years, this quick growth has caused the company to evaluate the IT environment and its ability to support the growth and secure the data of the company. The CEO is expecting the company to grow 60% over the next two years; with the success of the company it has been determined that a change to the current IT environment and infrastructure must occur to better support the employees and the customer base.
File transfers requires to be scheduled for data to be moved to a central database or data warehouse. This by far involves an Extract, Transform and Load (ETL) workflow as data is usually gathered from different types of database. Once the data is brought to a central database, to determine patterns in the data queries are scheduled from a variety of users using various applications. The frequency of the queries varies from business to business – it can be continuous, once a day or hourly. And of course, as data gets added to the database and moved to new databases, there is the routine task of database management that needs to occur.
Some faculties and departments are already using Oracle applications in their day-to-day operations. As time goes by, more and more information users will be working with an application based on Oracle database technology. If you get the opportunity to be a member of an application development team, you will become familiar with the workings of Oracle and relational databases. Other users may have to learn about this popular database management system through their own experience. This article is for our readers who, as of yet, have no access to Oracle databases but have a yearning for learning what they're all about.
Ans: When a data mart replaces data warehouse, data marts can be used for analysis purposes and it would be much less expensive to work with data mart but then they can be used only for specific business unit or department. When a data mart is used to complement a data warehouse it has the benefit of using the consis...
Data warehousing is a difficult system and has to have the capability deliver quality data. An operational database is one which is used by organizations to run its day to day database activities. They are designed to handle rapid transaction processes with systematically updates. Velocity is important to operational databases. They are most commonly operated by office staff, and are on the order of megabytes of data to gigabytes. Database consistency checks and constraints are rigidly enforced. They contain the latest technology necessary to operate organizational functions.
More firms and industries are adopting cloud computing because of its flexibility as well as convenience. The health care industry on the other hand has been very slow when it comes to the adoption of this new trend. However, gradually many hospitals as well as clinics have been able to recognize the benefits of cloud computing and most of them have embraced this new technology to revolutionize their procedures. In the 21st century, it is extremely hard and challenging for physicians to keep track of all the data that exists from the patient records to insurance information. The traditional system is often a burden as one has to transfer physical files from one facility to another. This process is tiresome and cumbersome; it also wastes time and money that could have otherwise been put into other productive uses (Spagnoletti 12). The cloud storage systems often allow organizations to place data on each and every centralized electronic system that can be accessed anytime from anywhere and anytime. The healthcare industry often has to deal with large amounts of data, and the cloud services often help them to manage as well as access health records effectively in order to provide patient care in an effective and efficient manner.
In today’s society, technology has become more advanced than the human’s mind. Companies want to make sure that their information systems stay up-to-date with the rapidly growing technology. It is very important to senior-level executives and board of directions of companies that their systems can produce the right and best information for their company to result in a greater outcome and new organizational capabilities. Big data and data analytics are one of those important factors that contribute to a successful company and their updated software and information systems.
Data marts are classified in two categories. Dependent data marts draw data from a center data warehouse, sometimes known as enterprise data warehouse, where as independent data marts draw data from operational systems or external sources. For the purpose of this presentation, we are promoting the use of dependent data marts because of the benefits of the Extraction-Transformation-and Loading (ETL) process is much similar in that the data is already clean, summarized, and loaded into the data warehouse. The ETL process consists of mainly identification of the subset of relevant data and moving it to the data mart. With independent data marts on the other hand, the ELT process has to be managed in its entirety, meaning that the data has to be staged every time to be normalized, integrated, and in dimensional formats. (Ariyachandra & Watson, 2012) For these reasons, I am advocating building dependent data marts to maximize performance and to increa...
[7] Elmasri & Navathe. Fundamentals of database systems, 4th edition. Addison-Wesley, Redwood City, CA. 2004.
"Although fully searchable text could, in theory, be retrieved without much metadata in the future, it is hard to imagine how a complex or multimedia digital object that goes into storage of any kind could ever survive, let alone be discovered and used, if it were not accompanied by good metadata" (Abby Smith). Discuss Smith's assertion in the context of the contemporary information environment
of multiple types of end users. The data is stored in one location so that they
System performance is one of the most critical issues faced by companies dealing with vast amounts of data. Companies use database systems and their applications to store, retrieve and handle this data.
The last decade can be marked as a period of significant changes in the business world. Being accustomed to utilize computers as a powerful tool with its office applications such as Microsoft Word and Excel. In the 1990s office workers first faced the opportunity to share information using the Internet (McNurlin, 2009). However, the situation became even more different with the transition to the third millennium. With a further development of information technologies, the majority of big enterprises had to reconstitute their business processes and to make the transition to the Internet economy. Enterprise resource planning (ERP), supply-chain management (SCM), customer relationship management (CRM) software and the variety of other information systems became essential components of the new economy. It can be expected, that all these complex solutions were designed to bring great benefits for different sides of the corporate activity, in particular, decisions made by top-managers are expected to become nearer to the ideal, customer service is to be improved and collaboration more prolific. Nevertheless, to ensure the desired results it should be taken into account that the key concept of these reorganizations is an information or a data, dealing with which can be a serious issue, and wide utilizing of the data warehouses in contemporary organizations confirms this fact.
The Database Management System (DBMS) is software that enables the users to define, create, maintain and control the access to the database. It is a software that interact with the user’s applications programs and it database. Meanwhile, information retrieval system is a system that involved the activity that the systems obtain the information. The obtaining information action need the information from it resources.
In our world, people rely heavily on the power of technology every day. Kids are learning how to operate an iPad before they can even say their first word. School assignments have become virtual, making it possible to do anywhere in the world. We can receive information from across the world in less than a second with the touch of a button. Technology is a big part of our lives, and without it life just becomes a lot harder. Just like our phones have such an importance to us in our daily lives, database management systems are the same for businesses. Without this important software, it would be almost impossible for companies to complete simple daily tasks with such ease.