Saving Time and Money The Future of Data For the CIO.

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Saving Time and Money The Future of Data For the CIO

 The least expensive parts of your system are that way because they are uniform, reusable, and reliable, such as the relational database management systems (RDBMS).  With traditional design, the most expensive parts are custom-built, not reusable, and only become reliable with time and work. Most of your system is done this way.

 Using Equal Format Data, more of your system will be less expensive, and more uniform, reusable, and reliable.  Less of your system needs to be custom-built.

Let’s look at the projected costs in a major system consolidation, updating and merging two legacy systems together, lasting 24 months with a cost of $5 million. TaskTime ScheduleCost System Criteria Design$600 K Data Design$600 K Data System Implementation$700 K Form / Report Design$600 K Form / Report Implementation$2,000 K Installation$500 K Total24 Months$5,000 K

TaskTime ScheduleSaveCost System Criteria Design16%$500 K Data Design33%$400 K Data System Implementation57%$300 K Form / Report Design16%$500 K Form / Report Implementation10%$1,800 K Installation20%$400 K Total18 Months22%$3,900 K Let’s look at the same project design using an equal format system. Thanks to a reusable design, many tasks can be started earlier, with common forms, reports, and functionality saving more time and money.

 Traditional design patterns take all of the data and break it up into separate tables in a customizing process called “normalization”.  This process is designed to gain flexibility and save space, but it becomes more complex as the number of tables often climb to hundreds in each database.

In a traditional design, a value is given meaning by its position in a table. This has a number of expensive side effects: This Old Table  All tables are custom.  Interactions with custom tables are also custom.  Complexity is used to gain flexibility and save space.  More table design and conversion work is required to handle future changes.

In the new EFD design pattern, the old table is broken into small pieces of Equal Format Data, with the meaning attached to the value.

 Equal Format relational tables are uniform and can be used on almost any relational server. This preserves prior knowledge and improves learning curves.  Uniform tables lead to uniform functionality, allowing more reusable code. This improves reliability and security.

 The uniformity of Equal Format systems allows data to be partitioned, paralleled, and distributed, in a scalable manner.  Equal Format containers support data registries and dictionaries.

Upfront advantages:  Quicker development time using off-the-shelf components  Quicker development time when developers and project segments are more independent  Reliable, tested table design and code reduces debugging  Uses your current database servers, preserving corporate investment Long-term benefits:  A standard table structure improves learning curves and simplifies maintenance  Future enhancements are easier with a design already capable of handling future needs  Data dictionaries and registries are easier to create and maintain, maximizing the searching, mining, merging, and distribution of data  Less vendor dependence

Important characteristics:  Holds any data model, eliminating the need for object or specialty databases  Uses your SQL-based database server, i.e. Oracle, IBM DB2, Microsoft SQL Server  More flexible and scalable than XML Storage systems  Can be merged into existing systems  Great for retrievable archives Unique capabilities:  Preserves and tracks all data changes with non-destructive modifications  Holds a “snapshot” of any time- state of the database  Rollbacks can be controlled for changes made during a particular timeframe, by a person, or any other criteria of your definition  Compares two databases for differences

 Master Data Storage  Messaging Systems  Data Warehousing, Data Marts, and Data Mining  Security, Auditing, Quality Control  Merging Legacy Information  Facility Data and PLM Data  Engineering Project Management  Product Catalog Data  Development Infrastructure EFD Analysis PLM Facilities CAD Planning Purchasing EFD

+1 (734) voice +1 (734) fax The Future of Data Datura, LLC PO Box 498 Howell, MI USA