Archive for November 2011
Data Management
November 26, 2011 | 
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We live in a modern world where all kinds of work and strategic operations depend on the amount of knowledge that can be manipulated, molded, shaped and reshaped in order to get the best of results in any field of activity. But the whole amount of information and knowledge, or data, has to be managed and processed in accordance with the type of result intended in the specific field. Therefore, the necessity of data management has become an important concept in different work arenas. These work arenas include management, research, technical applications, technology, corporate activities, and print media.
Nonetheless, data management has evolved as a discursive field of activity that has become an inevitable development and execution of various policies and information in various fields. To give a definition: data resource management, or simply data management, is the development as well as execution of various policies, practices, and procedures to help an individual or a firm to manage the complete data lifecycle. This definition is extensive and takes into account a number of professions that may or may not have direct or strategic contact with low-level aspects of data management or data resource management, or even data processing, like that of relational database management.
Data management as a discipline that encompasses the various processes of the authentication, substantiation, coordination, rationale, integration, incorporation, and has power over of data rations. It is also made sense in the manner that through data management planning for the proper, suitable and economical attainment of data as well as the management of data assets through a number of formulae and strategies after they are received. There are a number of topics falling in the data management are as follows: a.) data modeling b.) database administration, data warehousing, data movement, data mining, data quality assurance, data security, meta-data management, and c.) strategic data architecture. Software technology in the contemporary world has revolutionized the very nature of data management services.
Posted in Data Management | 
Tags: Applications Technology, Level Aspects, Meta Data Management | 
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The Benefits of Master Data Management
Master Data Management is a methodology for researching and implementing controls and business rules around your data. There are many benefits to implementing Master Data Management (MDM) at your company. MDM can help prevent critical errors, it can help prevent fraud, and it can help make you a smarter and more efficient company.
The first step of Master Data Management is identifying the most critical and important data for your company. Doing this step alone can help shine light within the organization on what is important. MDM can help prevent critical errors because, once controls and business rules are implemented on your critical data, you are less likely to make the mistakes of the past and you help yourself from preventing mistakes in the future. The company is now focused on its critical data, on keeping it clean and accurate, and this mentality is spread across the organization.
The task of identifying the most critical information should not be determined by just one person or one group. This task should be done with the help of people across the organization so that everyone takes ‘ownership’ of the idea that the end result had to do with research and work they put forth. It is important, with MDM, to play the political game so that you have support from others in the organization.
Next, Master Data Management can also help prevent fraud. With the passing of Sarbanes-Oxley which holds executives of public companies accountable for their financial statement, these executives have now placed pressure on the organization to get things right. For many companies, Master Data Management is one of the pieces for ensuring accuracy and preventing fraudulent reporting. Master Data Management creates the rules that would make it difficult to have false or inaccurate data. With the prospect of an executive going to jail should they have falsified financial reports, it is critical that these statements are correct.
Finally, MDM can be used to make your organization smarter and more flexible. By having accurate data for your most important information, you can be sure that your models, projections, and predictions are as accurate as they could be. If you feed bad data into your forecasting models, the results that are output are nothing that could be relied on. By starting with valid data you are much more likely to produce results that your organization can depend on.
There are many benefits to implementing data governance. MDM can help keep your CEO and CFO out of jail, it can help prevent critical and embarrassing mistakes, and it can help your company succeed and thrive well into the future.
Data Management Issues
Now a days, data management is posing a real threat to big corporates, particularly in the IT industry. Some of the very frequent issues in data management and their solution are discussed below.
Scalability:
Scalability is one factor that is sometimes overlooked and is not given the necessary importance to. Its not that only medium sized and large sized organizations need to improve scalability and work on improving it. Even small companies need to look on scalability and the ways to improve production through scalability.
Changing environment:
The environment is changing every day, that too in IT industry the cloud changes very often. The product or service that we have been using last year might be outdated and moved out of market by the latest ones. The trend simply changes and internet makes way for those changes. The growing organizations should keep themselves on track and updated on the changes.
Data recovery:
There should be separate process and backup system available for the data recovery to stop the data loss from causing any damage to the business. Latest software and hardware help in this process.
Data volumes:
The volume of data grows with the volume of the business. The organization should be able to cope themselves up to handle those growing high volume data.
Lack or Inefficient use of resource:
Its not that major issue with respect to data management, but may help in increasing the efficiency of data management for any organization. Proper and efficient resources should be allocated to enhance the data management capacity which in turn helps in production and increase in the output for the company.
Lack of proper Audit system:
The lack in audit system may spoil the proper working environment in any organization. Periodic security audits should happen to make sure the plan and process are in place.
Above mentioned are some of the areas that need to be worked out for efficient data management for an organization.