iStrat Support Services - Data Services

P How much history should you bring forward? All of it, none of it, or some of it? How do you determine where to draw the line?
P Should the remaining data be archived, and if so, how much of it? What are the available choices?
P What are the costs of the various alternatives? What risks are inherent in each of these options?
P How do you differentiate between static and dynamic data? How do decisions regarding static and dynamic data affect the overall       schedule?
P How much of the legacy data will require parsing or concatenation, and how will this affect the end users ability to relate to the data?
P Will the data hierarchy remain the same or does it need to change to fit into the new environment? If changed, what is the impact on       the business (tagging, drawings, procedures, related databases, etc)?
P Does all of the necessary data exist today, and if not, what new data will need to be created? What options exist for generating this       data, and what are the relative costs and benefits of each?
P What and where are the sources of the data? Is the data readily available? Are there multiple sources for the same or similar data, and       if so, which data sources represent the best available data? What format is the data in today?
P What is the current quality of the data? Given that some level of data clean-up will be required, how do you identify what data is most       critical for clean-up? What are the available tools for accomplishing that clean up?
P What are the advantages and disadvantages of working with a data clean up outsourcer?
P Going forward, who will maintain the data? What data services key performance indicators are required?




In terms of delivering value to your operations, there are few areas of an implementation effort that are either more critical or of greater risk than the effective conversion of data from legacy systems. Data Clean-Up, Conversion and Archiving are typically the most time-consuming aspects of any project. When it comes time to plan for the future of these key data assets, there are a multitude of questions that must be asked and answered. Included in these key questions are the following:
P How much history should you bring forward? All of it, none of it, or some of it? How do you determine where to draw the line? P Should the remaining data be archived, and if so, how much of it? What are the available choices? P What are the costs of the various alternatives? What risks are inherent in each of these options? P How do you differentiate between static and dynamic data? How do decisions regarding static and dynamic data affect the overall schedule? P How much of the legacy data will require parsing or concatenation, and how will this affect the end users ability to relate to the data? P Will the data hierarchy remain the same or does it need to change to fit into the new environment? If changed, what is the impact on the business (tagging, drawings, procedures, related databases, etc)? P Does all of the necessary data exist today, and if not, what new data will need to be created? What options exist for generating this data, and what are the relative costs and benefits of each? P What and where are the sources of the data? Is the data readily available? Are there multiple sources for the same or similar data, and if so, which data sources represent the best available data? What format is the data in today? P What is the current quality of the data? Given that some level of data clean-up will be required, how do you identify what data is most critical for clean-up? What are the available tools for accomplishing that clean up? P What are the advantages and disadvantages of working with a data clean up outsourcer? P Going forward, who will maintain the data? What data services key performance indicators are required? Looking ahead to production, you also need to take the following into consideration when converting your data: P What are your report writing requirements? How do you go about establishing the priorities for report writing? P Will you need reports based on real time data, or can you live with batch reports? What are the relative advantages and disadvantages of either? P What are the potential technology impacts for report generation?

iStrat has worked with many customers to answer those questions and develop an effective Data Services strategy. We realize that the data in your company represents one of your most important assets - it contains not only the historical knowledge of the company, but also represents your intellectual property. iStrat will work with you to ensure the data hierarchy established exactly aligns to and supports your core business processes, and work with you to navigate the often murky waters of data clean up, conversion, and archiving. The highly skilled professionals at iStrat can assist you in developing a realistic, workable Data Conversion strategy and reduce the risks associated with this critical path activity. iStrat can also assist you with the actual extraction, conversion, clean up, testing, and archiving of your mission-critical corporate data where deemed appropriate.

Results - With iStrat Data Services expertise supporting your Mission Critical Projects, we'll safeguard one of your most important corporate assets today and in the future!


	Data Services