Analytics Chap 3

When developing a data warehouse, what are the most important risks and issues to consider and avoid?

- Starting with the wrong sponsorship chain - Setting expectations that you cannot meet - Engaging in politically naïve behavior - Loading the warehouse with information just because it is available - Believing that data warehousing database design is the same as transactional database design - Choosing a data warehouse manager who is technology oriented rather than user oriented - Focusing on traditional internal record-oriented data and ignoring the value of external data and of text, images, and, perhaps, sound and video - Delivering data with overlapping and confusing definitions - Believing promises of performance, capacity, and scalability - Believing that your problems are over when the data warehouse is up and running - Focusing on ad hoc data mining and periodic reporting instead of alerts

What is a cube? What do drill down, roll up, and slice and dice mean?

A cube in OLAP is a multidimensional data structure that allows fast analysis of data Drill down - is a specific OLAP technique whereby the user navigates among levels of data ranging from the most summarized to the most detailed Roll up - involves computing all of the data relationships for one or more dimensions. To do this, a computational relationship or formula might be defined. Slice - is a subset of a multidimensional array corresponding to a single set for one of the dimensions not in the s Dice - is a slice on more than two dimensions of a data cube.

What skills should a DWA possess?

IT, solid business insight, familiarity with business decision-making processes, and excellent communication skills

Explain the importance of metadata.

Metadata describes data containing specific information like type, length, textual description and other characteristics.

What are the key similarities and differences between a two-tiered architecture and a three-tiered architecture?

The Two-tier architecture is divided into two parts: 1) Client Application (Client Tier) 2) Database (Data Tier) Three-tier architecture typically comprise a presentation tier, a business or data access tier, and a data tier. Three layers in the three tier architecture are as follows: 1) Client layer 2) Business layer 3) Data layer

What is a data warehouse?

a large store of data accumulated from a wide range of sources within a company and used to guide management decisions.

How does a data warehouse differ from a database?

A type of database that integrates copies of transaction data from disparate source systems and provisions them for analytical use.

What recent technologies may shape the future of data warehousing?

Companies like SAP are working on that right now. With the launch of the BW/4HANA data warehousing solution running on premise and Amazon Web Services (AWS) and others like it, we can see how businesses can combine historical and streaming data for better implementation and deployment of new BI strategies.

What is OLAP and how does it differ from OLTP?

Data stored in a data warehouse can be analyzed using techniques referred to as OLAP, Online Analytical Processing. OLAP is one of the most commonly used data analysis techniques in data warehouses. OLAP is an approach to quickly answer ad hoc questions that require data analysis. OLTP is concerned with the capture and storage of data and is designed to best carry out day-to-day business functions. OLAP is concerned with the analysis of that data and provide answers to business and management queries.

Describe the major components of a data warehouse.

Data warehouse contains the collection of data that are used for decision making and business intelligence. It is a subject-oriented, integrated, time-variant, and non-updateable data.

Describe the three steps of the ETL process

Extraction: selecting data from one or more sources and reading the selected data. Transformation: converting data from their original form to whatever form the DW needs. This step often also includes cleansing of the data to remove as many errors as possible. Load: putting the converted (transformed) data into the DW.

Describe the data warehousing process.

The data warehousing process consists of the following steps: 1. Data are imported from various internal and external sources 2. Data are cleansed and organized consistently with the organization's needs 3. a. Data are loaded into the enterprise data warehouse, or b. Data are loaded into data marts. 4. a. If desired, data marts are created as subsets of the EDW, or b. The data marts are consolidated into the EDW 5. Analyses are performed as needed