By Sid Adelman
The definitive best-practices advisor to company data-management strategy.You can now not deal with firm information "piecemeal. to maximise the enterprise price of your info resources, you want to outline a coherent, enterprise-wide information approach that displays all of the methods you trap, shop, deal with, and use information.In this ebook, 3 popular information administration specialists stroll you thru growing the optimum info approach in your association. utilizing their confirmed strategies, you could lessen and upkeep expenses, and rein in out-of-control info spending. you could construct new structures with much less possibility, larger caliber, and increase facts entry. better of all, you could how to combine new functions that help your key enterprise objectives.Drawing on actual firm case reviews and confirmed most sensible practices, the writer workforce covers every thing from goal-setting via dealing with safeguard and function. you will how to: * establish the genuine dangers and bottlenecks you face in providing data-and the suitable suggestions * combine company info and enhance its caliber, so it may be used extra largely and successfully * Systematically safe firm facts and shield client privateness * version info extra successfully and take complete good thing about metadata * pick out the DBMS and information garage items that healthy most sensible into your total plan * easily accommodate new enterprise Intelligence (BI) and unstructured info purposes * enhance the functionality of what you are promoting database purposes * Revamp your company to streamline day by day info administration and decrease expense * facts technique is necessary for everybody who must deal with firm information extra efficiently-from database architects to DBAs, technical employees to senior IT decision-makers.
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Extra info for Data Strategy
Data Quality "Virtually everything in business today is an undifferentiated commodity, except how a company manages its information. " Bill Gates Everybody wants better quality of data. Some organizations hope to improve data quality by moving data from legacy systems to enterprise resource planning (ERP) and customer relationship management (CRM) packages. Other organizations use data profiling or data cleansing tools to unearth dirty data, and then cleanse it with an extract/transform/load (ETL) tool for data warehouse (DW) applications.
This is equivalent to saying that the primary key is the same for the supertype and its subtypes. For example, the account number of a person's checking account is the same account number, regardless of whether it identifies the supertype ACCOUNT or the subtype CHECKING ACCOUNT. ♦ All business attributes of a subtype must be unique to that subtype only. For example, the data element Interest Rate is applicable to savings accounts, but not checking accounts, and must therefore reside on the subtype SAVINGS ACCOUNT.
Give specific examples that they will be familiar with and care about. Tie your findings to the bottom line of the company's profit and loss statement. • Get sponsorship Data integration initiatives can be sustained only with strong executive sponsorship. You have to secure at least one sponsor, preferably several. The sponsor must be a business person not just the CIO or CTO who is heavily committed to the data integration project. He or she should be a senior executive who is well respected and influential in your organization.