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A data warehouse differs from OLTP in that the former handles many large and complex queries regarding various rows of a table while the latter retrieves data from single rows. At the same time, a data warehouse is not real time and supports few users at a time compared to OLTP that can support many concurrent users.
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What is the difference between data warehouse testing and conventional testing?
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. Conventional testing is a sort of testing in which the test engineers will check the developed application or its related parts are working accordingly to the expectations of customer or not, from coding phase of SDLC to the end
What difference between data warehouse and traditional database used OLTP?
{| |+ Differences |- | Data warehouse database OLTP database Designed for analysis of business measures by categories and attributes Designed for real time business operations. Optimized for bulk loads and large, complex, unpredictable queries that access many rows per table. Optimized for a common set of transactions, usually adding or retrieving a single row at a time per table. Loaded with consistent, valid data; requires no real time validation Optimized for validation of incoming data during transactions; uses validation data tables. Supports few concurrent users relative to OLTP Supports thousands of concurrent users. |}http://www.geekinterview.com/question_details/15800
Difference between data warehouse and datamart?
A data warehouse has multiple functional areas whereby a centralized organizational unit is responsible for implementing it. On the contrary, data marts focus on particular functional areas hence are simple forms of a data warehouse.
What is the difference between OLAP and data mining?
difference between Data Mining and OLAP
How does Data Warehouse differ from Data Mart?
Data marts are combined into a data warehouse cannot be built alone without considering data marts. Both has equal importance to built proper data warehouse.
What is the difference between data warehouse testing and conventional testing?
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. Conventional testing is a sort of testing in which the test engineers will check the developed application or its related parts are working accordingly to the expectations of customer or not, from coding phase of SDLC to the end
3 Distinguish between data warehouse and a data mart?
A database is a system for storing transactional data (OLTP). A data mart is a repository for analytical data (OLAP). A database is a collection of information about a single topic's various features and activities. Data from many subjects will be stored in a data mart. To learn more about data science please visit- Learnbay.co
What difference between data warehouse and traditional database used OLTP?
{| |+ Differences |- | Data warehouse database OLTP database Designed for analysis of business measures by categories and attributes Designed for real time business operations. Optimized for bulk loads and large, complex, unpredictable queries that access many rows per table. Optimized for a common set of transactions, usually adding or retrieving a single row at a time per table. Loaded with consistent, valid data; requires no real time validation Optimized for validation of incoming data during transactions; uses validation data tables. Supports few concurrent users relative to OLTP Supports thousands of concurrent users. |}http://www.geekinterview.com/question_details/15800
What is the difference between data warehouse testing and traditional software testing?
ETL or Dataware Housing Testing:- 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. Traditional (old) way of software testing: -Requirement -Design -Code & Build -Testing -Maintenance Unfortunately that is an erroneous methodology because the earlier you find an error - the more funds you can save. For example, fixing an error in maintenance is ten times more expensive than fixing it during execution. But many organizations have improved this way of thinking and choose modern way of software testing. In this philosophy testing should take place in every stage.
Difference between data warehouse and datamart?
A data warehouse has multiple functional areas whereby a centralized organizational unit is responsible for implementing it. On the contrary, data marts focus on particular functional areas hence are simple forms of a data warehouse.
What is the difference between online transaction processing and online analytical processing?
OLTP : customer oriented. OLAP : Market oriented OLTP : ER based application oriented concern OLAP : subject oriented concern. Current data : Historical data used for detailed for decesion making Access patterns are short. : COCancelMPLEX
What is the difference between database and data warehouse?
Typically, a database versus a data warehouse, is "OLTP" (online transaction processing). That means that live inserts/updates/deletes happen to the database all the time. A data warehouse is used for statistics and trending. Nighly data feeds from stores are populated into the tables. During the day, no inserts/updates/deletes occur on the database--it is used for data gathering (queries) only.
Why need of separate data warehouse?
3 Main reasons: 1.OLTP systems require high concurrency, reliability, locking which provide good performance for short and simple OLTP queries. An OLAP query is very complex and does not require these properties. Use of OLAP query on OLTP system degrades its performance. 2.An OLAP query reads HUGE amount of data and generates the required result. The query is very complex too. Thus special primitiveshave to provided to support this kind of data access. 3.OLAP systems access historical data and not current volatile data while OLTP systems access current up-to-date data and do not need historical data.
What are the key relationships between data warehouse and data mining?
Data warehouse is the database on which we apply data mining.
What are the types of Databases?
Here are the basic list of Database Types: OLTP : Online Transaction Processing Database - To store LIVE, Real-time data. Example: LIVE Temperature, LIVE Cricket Match data.. OLAP : Online Analytical Processing Database - To store data for Analysis, Forecasts. Example: Weather Forecasts DWH : Data Warehouse Database - To store Old, Historical Data HTAP Hybrid Transactional Analytical Processing Database OLTP + OLAP + DWH. Example : Google Map For more details, pls reach me.
What is the difference between olap and oltp?
Hi, The difference can be highlighted by defining the two entities separately, OLTP: Online Transaction Processing is a system normally used in the regular routine of database or User end Transactions (These Transactions are short Transactions). In OLTP, the data is fully normalized in order to avoid redundancy,Duplication of data etc, for achieving normalization various Joins are used that connects the tables. (without these joins OLTP cannot be fully Normalized). Now move on, OLAP: Online Analytical Processing is a system helpful for analysis purposes, it is used in Business Intelligence for analysis reporting, unlike OLTP it doesn't have too many joins in it because in OLAP it is not required to normalize the data, the basic purpose is to make Facts and Dimensions. <<Specifically for reporting purposes the data retrieval should be faster (The joins make the data processing slow) so the basic need of designing OLAP is to make the reporting system faster.>>
Can you use an OLTP backend database for creating a dashboard?
yes, it is nothing but transactional data
