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How do you test analytical application?

Importance of testing Analytical Applications: Accuracy: Testing ensures that the application accurately provides the results that it is intended to produce. This is important because these applications are used to make critical business decisions. Performance : Testing can identify any performance issues, such as slow processing times or data retrieval, which can impact the overall efficiency of the application. Scalability : As the volume of data processed by analytical applications increases, it's important to ensure that they can scale to handle the increased load. Testing can identify any scalability issues early on. Reliability : Testing can ensure that the application is reliable and produces consistent results over time. This is important for maintaining trust in the results produced by the application. Usability : Testing can identify any usability issues, such as poor navigation or unclear instructions, which can negatively impact the user experience and limit the adopti...
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Why do we need NoSQL over SQL and how do we choose the best database for the project?

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In this article we will learn about databases RDBMS and NoSQL. What is a Database? Database is Structured, provides Random access that will help us to search data quickly based on index, having low latency and provides ACID properties. source: Google images ACID properties: A tomicity : The data will be transfer either full or none will be transferred.  Example: When you transfer money online using netbanking , either full amount should be transferred or none should be transferred. C onsistency : Data should be consistent. I solation : If multiple people are working in same bank / doing transfers at the same time, the there should be a sequencing/locking mechanism D urability : Whenever there is a database failure, the system should be up and running to save the data. Why do the companies want NoSQL over SQL? NoSQL databases offer many benefits over relational databases.  NoSQL databases have flexible data models, scale horizontally, have incredibly fast queries, and are ...
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When to choose data warehouse over database?

  The decision between a database and a data warehouse will depend on your specific needs and use case. Deciding between a database and a data warehouse largely depends on the specific needs of your organization and the type of data you're working with. Some of the factors for consideration are: Ø  Data Volume : When you have large volume of data (e.g., terabytes or more), then better to go for a data warehouse as data warehouses are optimized for handling large amounts of data. Databases are designed to handle smaller amounts of data. Ø  Data Complexity : If you are working with complex data that requires advanced querying and analysis, then, a data warehouse will be a better choice. Data warehouses can handle complex queries and data modelling. Databases may not be equipped to handle the same level of complexity. Ø  Data Integration : If you need to integrate data from multiple sources, a data warehouse may be the better choice. Data warehouses are designed to hand...
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