Enterprise Data Warehouse
An Enterprise data warehouse (EDW) is a mass data storage unit used for a business or company (an enterprise). In the same way a regular data warehouse stores data, cleanses it, and transforms it, so does an Enterprise warehouse. The difference between an original data warehouse and an Enterprise warehouse is that the Enterprise storage serves as a central storage unit—whereas an original data warehouse stores data for only a certain portion of a business network.
Enterprise data warehouse architecture refers to the components of an enterprise data warehouse. The architecture of a home refers to the materials used to make it: wood, siding, roofing, glass windows, screen doors, steps, brick underpinning, etc. In the same way, data architecture refers to the elements that constitute the centralized data storage unit for a business or company. There are five necessary elements for an Enterprise architecture:
- Single version of data
- Multiple subject areas
- Normalized Design
- Mission-Critical Environment
- Scalability across several dimension
Businesses should have a single version of data. Most businesses have numerous operations that must run in order for the business to stay alive. To keep the information centralized and well-contained, there should only be one data storage unit for all of the company information. Next, a business should have multiple subject areas. A business cannot run only billing operations but no payment operations—or an ordering operation but no shipping operation. Businesses should have clearly-defined operations, each distinct from one another, that all run at the same time. The running of several applications at once is what keeps the business at the top of its game.
Normalized design refers to the architecture of the Enterprise storage unit. Enterprise storage units are centralized and distinct from individual data warehouses. Data warehouses usually come with either a snowflake or star schema, while enterprise storage units do not. According to the Enterprise data warehouse definition, Enterprise storage units are more complex data networks than data warehouses; the last thing an Enterprise storage needs is a complex structure—this will only add to the complexity of the system and make it harder for businesses to maintain their data storage. Instead, complex storage units such as Enterprise storage units should have a more simple structure, such as a normalized design.
A mission-critical environment is also a significant component of an EDW. A mission-critical environment has all the preventive security measures in place to keep the data network from being destroyed by a virus, hacking incident, etc. Three major types of preventive measures include (1) high availability features, (2) business continuance features (failover, disaster recovery), and (3) security features.
The last major component of an EDW is its scalability across several dimensions. Scalability refers to the freedom of computer users to have their questions answered. Scalability has often been defined by the amount of data a network has, but scalability also involves queries. Computer users ask questions online every day about life, how things work; some even ask questions about things that most individuals would not even think about. It is these “freedom queries” that computer applications must be ready to handle.
There are a few enterprise data warehouse jobs available for someone interested in this field of labor: Database administrator (DBA), exact-translate-load developer (ETL), business intelligence developer (BI), solution architect, and data warehouse salesmen. The database administrator is in charge of ensuring the data warehouse runs smoothly. The extract-translate-load developer (ETL) prepares the data that are placed within the computer makes its way to the data storage unit. The ETL developer prepares raw data to enter the storage unit. He or she extracts the necessary data, translates it or converts it into proper form, and then loads the applications on computers for computer users.
The business intelligence developer sees to it that business decisions are made by way of charts, graphs, and other tangible report forms. He or she develops programs that will provide more insight into business issues so as to call business employees to rethink decisions they have or are about to make. Solution architects are present at businesses to help them create and run their data warehouses. Data Warehouse salesmen are present at businesses and companies to point out business problems that necessitate the development of a data warehouse and develop tools to solve the business problems.
The HP Enterprise Data Warehouse appliance is a new business partnership between Hewlett-Packard (HP) and Microsoft to create a data storage unit that has faster query times and can store up to 500 terabytes (TB) of information while maintaining quality performance. Its architecture consists of the following elements:
- Client drivers
- Data center monitoring
- ETL Load Interface
- Corporate Backup Solution
- Active/passive control nodes
- Management nodes
- Landing zone
- Backup node
- 11 database nodes (2 sockets per node)
- 10 storage nodes
What are some hot jobs in the enterprise data warehouse sector currently? One hot job is that of data warehouse testing engineer from The Select Group in San Diego, California. The job requires the testing engineer to develop programs that test network operations to see how strong they are. The testing engineer is expected to have at least a bachelor’s degree in Computer Science (CS) and five or more years’ knowledge and experience in data warehousing. Another hot job would be that of enterprise data warehouse architect from Federal Way, Washington. The architect should be skilled in enterprise warehouse architectural design, familiar with both Kimball and Inmon methodologies, prepared for both mentorship and teaching, and metadata management. There are many others out there on Internet job sites.
An enterprise data warehouse should be owned and operated by every business that seeks to handle day-to-day operations of various tasks. A multi-component business needs a multi-component data network.