SUPPLY CHAIN

various Data Warehouse, Database Data, and data mart marts and data warehouses address distinct use cases and therefore there are major differences in the ways they are used and built. The first difference is that data warehouse size is more than 100 GB while data mart has size is than 100GB (Mandal & Maji, 2016). The second
difference is that a data warehouse holds all organizational data while a data mart holds a single business line due to its small size. The third difference is data warehouse has hundreds of data sources whereas a data mart has only few sources of data sources. The fourth difference is data warehouse uses strategic decision-making types whereas data mart uses tactical decision-making types.

MORBIDITY AND MORTALITY

Differences between Data Base and Data Warehouse

Database stores information about one of your business in real time, which is the main task of your organization to process regular transactions. Databases use online transaction processing to quickly insert, replace and update online transactions, while online analytic treatment is used by the data warehouse to quickly analyze large volumes of data. Secondly, databases are optimized for maximum efficiency and speed updates, while data warehouses are
optimized for a low number of complex issues (Stoole, 2016). Third difference is that databases usually process transactions and is also possible to perform data and analyze them whereas data warehouses are designed to perform complex analytical questions on large datasets which are multi-dimensional. Another thing about databases is that they support thousands of users, while databases support only a limited number of users. Finally, databases process everyday transactions for one company, while data storage is used for analytical and business reporting
purposes.

Financial Concepts Evaluation

Question 2

The goal of the data warehouse described in the architecture of business information systems and work is to build an integrated decision-making architecture supporting the decisions made in businesses, evaluate current conditions with business intelligence, and take safe, quick, and right future decisions. A data mart drives business intelligence and analytics to lead departmental decisions. With special targets in mind, teams will exploit focused data
perspectives (Ţole, 2016). The data stores are conventional business intelligence tools, which mainly work on structured data in relational database applications. The knowledge of the business is also organized. When data are supplied via a data virtualization server in a suitable standardized format from unstructured data sources, traditional business intelligence tools are better than ever.

Question 3

The Data warehouse is going to be cloud-based. What was unthinkable just a decade ago is no onger the working fact that businesses now turn to power and store their data warehouses in the cloud. It will be adaptive, offering real-time as well as historical perspective. A data warehouse can enable artificial intelligence (AI) and learn from the machine in order to achieve performance (Ţole, 2016). , AI will also enhance the operation and capabilities of data warehouses. Data management by the use of data virtualization is being expanded into new analytical environments by combining multiple data warehouses to provide virtual information, data virtualization can enhance both traditional ETLs and data replication processes (Rikhardsson & Yigitbasioglu 2018).