Big Data Engineering

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Ten Subject Areas to Cover with Data Warehousing Vendors

Here are ten subject areas that you should discuss with any data warehousing product vendor, no matter which product category (business intelligence tool, middleware tool, or RDBMS, for example) you’re [more…]

Nine Signs of a Successful Data Warehousing Project

Just because everyone gathers in the company cafeteria for cake and plasters the walls with congratulatory banners doesn’t mean that your data warehousing project was a success. This chapter gives you [more…]

Ten Signs of a Data Warehousing Project in Trouble

You can most easily tell that your data warehousing project is in trouble when you don’t have anything to show for your efforts when you thought you would. Try to get some indication that trouble’s brewing [more…]

Ten Mandatory Skills for a Data Warehousing Consultant

A good data warehousing consultant has certain abilities in dealing with people and a knowledge of various aspects of data warehousing. This list lets you in on a few required skills that all data warehousing [more…]

Ten Sources of Up-to-Date Information about Data Warehousing

You probably won’t be surprised to hear that the term up-to-date information about data warehousing means “go look on the Internet.” It’s worth your time to check out the Web sites in this chapter. [more…]

Future Business Intelligence Support Model for Data Warehousing

Currently, business intelligence support is often relegated to is-it-working support — if the system is down, the support personnel get it running again. This support model [more…]

Three Aspects of Collaborative Business Intelligence

Collaborative business intelligence is an environment within which users can easily collaborate and communicate with each other, sharing ideas, information, and decision making within their community. [more…]

Examples from Highly Successful Data Collaboration Solutions

Collaborative business intelligence might look like today’s Internet-based collaborative experience in several ways. The following sections discuss features that are most likely to become commonplace within [more…]

The Vision of Collaborative Business Intelligence

Collaborative business intelligence is real in many consumer situations. eBay, Amazon, and Google all leverage key data to present information to you, the consumer. Companies such as eBay are even contemplating [more…]

Emergence of the Semantic Web

In the world of computer science, semantics are relatively new, especially as relating to data warehousing. Semantics is the study of meaning in communication, including the meaning [more…]

Data Warehousing: What Is a Data Asset?

A data warehouse is a home for your high-value data, or data assets, that originates in other corporate applications, such as the one your company uses to fill customer orders for its products, or some [more…]

Data Warehousing: A Working Definition

So, what’s a data warehouse? In a literal sense, it is properly described through the specific definitions of the two words that make up the term: [more…]

How to Determine the Size for Your Data Warehouse

A common misconception that many data warehouse aficionados hold is that the only good data warehouse is a big data warehouse —an enormously big data warehouse. Many people even take the stance that unless [more…]

Facilitate Business Change with Data Warehousing

Data warehousing involves facilitating change in business processes. In addition to being able to make better, information-driven operational and tactical decisions, you gain insight into key areas that [more…]

Ensure That Your Implementations Are Unique

No two data warehouse implementations are exactly alike. A data warehouse is composed of many different components, each of which can be implemented in several [more…]

Classify Your Data Warehouse

Although you must ensure that your data warehouse fits your own unique needs, some guidelines can help you determine the probable complexity of its environment and structure. One good setup is to use a [more…]

The Data Warehouse Lite

A data warehouse lite is a no-frills, bare-bones, low-tech approach to providing data that can help with some of your business decision-making. No-frills means that you put together, wherever possible, [more…]

The Data Warehouse Deluxe

You’ll most likely focus most of your data warehousing-related activities on the data warehouse deluxe environment, as shown in this figure. Data from many different sources converge in these “real” data [more…]

Data Sources and Business Intelligence Tools for Data Warehouse Deluxe

You won’t be lucky enough to find any single-source environments when you’re building a data warehouse deluxe. Now, you have a whole new set of problems that you must deal with, including the ones in this [more…]

Data Extraction, Movement, and Loading for Data Warehouse Deluxe

Data warehouse deluxe implementations are big — and getting bigger all the time. Implementations that use hundreds of gigabytes (a gigabyte equals 1 billion bytes) and even terabytes [more…]

The Data Warehouse Supreme

Today’s state-of-the-art data warehouse typically looks like a complicated data warehouse deluxe. The data warehouse of tomorrow, though — the data warehouse supreme — will look quite different. There [more…]

Data Sources and Business Intelligence Tools for Data Warehouse Supreme

Because of the wide breadth of subject areas in a data warehouse supreme, it has numerous data sources. The good news: Because many of the sources are external to your own warehousing environment, you [more…]

Data Extraction, Movement, and Loading for Data Warehouse Supreme

A data warehouse has large-scale data distribution and advanced technologies that can integrate various “run the business” systems, improving the overall quality of the data assets across business information [more…]

Data Marts Sourced by a Data Warehouse

Many data warehousing experts would argue that a true data mart is a “retail outlet,” and a data warehouse provides its contents, as shown in this figure. [more…]

Top-Down, Quick-Strike Data Marts

Sometimes, you just don’t have a data warehouse from which to get data for your data mart, so you have to source the data from applications yourself. In many [more…]

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