Need an account? Click here to sign up. Download Free PDF. Devidas K. A short summary of this paper. Download Download PDF. Translate PDF. Business Intelligence is the process of collecting raw data or business data and turning it into information that is useful and more meaningful. The raw data is the records of the daily transaction of an organization such as interactions with customers, administration of finance, and management of employee and so on.
What is Data Warehouse? A data warehouse is a database that is designed for query and analysis rather than for transaction processing. The data warehouse is constructed by integrating the data from multiple heterogeneous sources.
It enables the company or organization to consolidate data from several sources and separates analysis workload from transaction workload.
Data is turned into high quality information to meet all enterprise reporting requirements for all levels of users. What is ETL? ETL stands for Extract-Transform-Load and it is a process of how data is loaded from the source system to the data warehouse. Data is extracted from an OLTP database, transformed to match the data warehouse schema and loaded into the data warehouse database.
Many data warehouses also incorporate data from non-OLTP systems such as text files, legacy systems and spreadsheets. Let see how it works For example, there is a retail store which has different departments like sales, marketing, logistics etc.
Each of them is handling the customer information independently, and the way they store that data is quite different.
The solution is to use a Data warehouse to store information from different sources in a uniform structure using ETL. ETL can transform dissimilar data sets into an unified structure. Later use BI tools to derive meaningful insights and reports from this data. Various types of keys are primary key, alternate key, foreign key, composite key, surrogate key. The data warehouse owns these keys and never allows any other entity to assign them.
Cleaning does the omission in the data as well as identifying and fixing the errors. In addition to these, this system creates meta-data that is used to diagnose source system problems and improves data quality. Identifying data sources and requirements 2. Data acquisition 3. Implement business logics and dimensional Modeling 4. Build and populate data 5. To support your business decision, the data in your production systems has to be in the correct order.
Informatica Data Validation 1 Option provides the ETL testing automation and management capabilities to ensure that production systems are not compromised by the data. Source to Target Such type of testing is carried out to validate whether the data values 2 Testing Validation transformed are the expected data values.
Testing Application Upgrades Such type of ETL testing can be automatically generated, saving substantial test development time.
This type of testing checks whether 3 the data extracted from an older application or repository are exactly same as the data in a repository or new application. Data Completeness To verify that all the expected data is loaded in target from the source, Testing data completeness testing is done. Some of the tests that can be run are 5 compare and validate counts, aggregates and actual data between the source and target for columns with simple transformation or no transformation.
Data Accuracy Testing This testing is done to ensure that the data is accurately loaded and 6 transformed as expected. Data Transformation Testing data transformation is done as in many cases it cannot be Testing achieved by writing one source SQL query and comparing the output 7 with the target.
Multiple SQL queries may need to be run for each row to verify the transformation rules. In order to avoid any error due to date or order number during business process Data Quality testing is done.
Syntax Tests: It will report dirty data, based on invalid characters, character pattern, incorrect upper or lower case order etc. For example: Customer ID Data quality testing includes number check, date check, precision check, data check , null check etc.
Incremental ETL This testing is done to check the data integrity of old and new data with testing the addition of new data. Incremental testing verifies that the inserts and 9 updates are getting processed as expected during incremental ETL process. The objective of ETL testing is to assure that the data that has been loaded from a source to destination after business transformation is accurate. It also involves the verification of data at various middle stages that are being used between source and destination.
ETL mapping sheets: An ETL mapping sheets contain all the information of source and destination tables including each and every column and their look-up in reference tables. ETL mapping sheets provide a significant help while writing queries for data verification.
Change log should maintain in every mapping doc. Validate the source and target table structure against corresponding mapping doc. Source data type and target data type should be same 3.
A great basic tool book for datawarehousing and ETL. Eric and Josh have written a combined 3 books including the forth. Copyright , , Oracle. SAS economic dynamics gandolfo pdf Publishing provides a complete selection of books and electronic products to help.
This ETL architecture describes processing at a logical design level and is tool agnostic. ETL Tools. The case of near real time ETL is discussed in an industrial book WPET V1. June Read other excerpts from data management books in the Chapter Download Library. So which tools, technologies andor approaches can we use for ETL and which. Subsequent book that he is not giving us a cook-book approach to ETL, but. Cowritten by Ralph Kimball, the worlds leading data warehousing authority, whose previous books have sold more than , copies Delivers real-world.
This practical book is a complete guide to installing, configuring, and managing Pentaho Kettle. More Books. ETL is Extrac7ng data from outside sources. Transforming it economics mcqs pdf to fit opera7onal needs.
Translations of various books have been done in Chinese, Dutch, French. ETL integration electronic text. In a high level description of an ETL process, first, the data are extracted from.
Popular books 3 do not mention the ETL triplet at all, although the different parts. See our editors picks for the books economia para ingenieros libro pdf youll want to read this season, from. Sep 5, Reference Book. Download free Databases eBooks in pdf format or read Databases books online.
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