<prompt> Etsa mokhoa oa ho boloka le ho fumana lintlha tse ngata.nan  <response>: Instruction in English: Design a system for storing and retrieving large amounts of data. . Response in English: The following steps outline a system for storing and retrieving large amounts of data:1. Determine the data requirements- Firstly, consider the type, format, and structure of the data that needs to be stored, as well as the expected size of the dataset. Additionally, it is also necessary to evaluate how frequently the data will be accessed, and whether it will need to be modified.2. Choose an appropriate storage solution - Based on the data requirements, select a proper storage solution that is capable of efficiently storing and retrieving large datasets. Some of the popular choices include distributed file systems e.g., HDFS, cloud storage providers e.g., Amazon S3, and NoSQL databases e.g., Cassandra.3. Establish a data management strategy - Establish a standardized approach for how data will be ingested, processed, and managed. Mapping out the data lifecycle and setting up a plan for data retention, backup, and recovery is an essential step in ensuring data integrity and availability.4. Set up a scalable infrastructure - Depending on the expected growth of the dataset, it is important to consider implementing an infrastructure that can scale up or down as the demand for storage and computational resources changes. Leveraging cloud-based solutions can help in managing the infrastructure efficiently.5. Implement efficient data retrieval mechanisms - Ensure that the system is capable of quickly and efficiently retrieving data as per user requirements. This involves setting up indexing, caching, and shard-ing strategies that can help speed up data retrieval operations.6. Monitor and optimize performance - Continuously monitoring the systems performance and identifying potential bottlenecks is essential in ensuring that the system can efficiently store and retrieve large amounts of data. Regular performance tuning exercises can help in keeping the system optimized.In summary, designing an effective system for storing and retrieving large amounts of data involves considering the data requirements, selecting an appropriate storage solution, establishing a data management strategy, setting up a scalable infrastructure, implementing efficient data retrieval mechanisms, and continuously monitoring and optimizing the systems performance. . Response in Sesotho: Mehato e latelang e hlalosa mokhoa oa ho boloka le ho fumana lintlha tse ngata: 1. Etsa qeto ea litlhoko tsa data- Taba ea pele, nahana ka mofuta, sebopeho le sebopeho sa data e lokelang ho bolokoa, hammoho le boholo bo lebelletsoeng ba dataset. . Ho feta moo, ho boetse hoa hlokahala ho lekola hore na data e tla fumaneha hangata hakae, le hore na e tla hloka ho fetoloa. 2. Khetha tharollo e loketseng ea polokelo - Ho itšetlehile ka litlhoko tsa data, khetha tharollo e nepahetseng ea polokelo e khonang ho boloka le ho fumana li-dataset tse kholo ka katleho. Tse ling tsa likhetho tse tsebahalang li kenyelletsa litsamaiso tsa lifaele tse ajoang mohlala, HDFS, bafani ba polokelo ea leru mohlala, Amazon S3, le database tsa NoSQL mohlala, Cassandra. 3. Theha leano la taolo ea data - Theha mokhoa o tloaelehileng oa hore na data e tla kenngoa joang, e sebetsoe le ho laoloa joang. Ho etsa mapa oa bophelo ba data le ho theha moralo oa ho boloka data, bekapo, le ho hlaphoheloa ke mohato oa bohlokoa ho netefatsa botšepehi le ho fumaneha ha data. 4. Theha scalable infrastructure - Ho itšetlehile ka kholo e lebelletsoeng ea dataset, ho bohlokoa ho nahana ka ho kenya tsebetsong mekhoa ea motheo e ka nyolohang kapa ea theoha ha tlhokahalo ea polokelo le lisebelisoa tsa computational li fetoha. Ho sebelisa litharollo tse thehiloeng marung ho ka thusa ho laola lisebelisoa tsa motheo ka katleho. 5. Kenya tsebetsong mekhoa e metle ea ho khutlisa data - Netefatsa hore sistimi e khona ho fumana data kapele le ka nepo ho latela litlhoko tsa mosebelisi. Sena se kenyelletsa ho theha indexing, caching, le maoala a shard-ing a ka thusang ho potlakisa tsebetso ea ho khutlisa data. 6. Ho beha leihlo le ho ntlafatsa tsebetso - Ho beha leihlo tsebetso ea sistimi khafetsa le ho tseba mathata a ka bang teng ho bohlokoa ho netefatsa hore sistimi e khona ho boloka le ho fumana lintlha tse ngata. Ho ikoetlisa khafetsa ho ka thusa ho boloka sistimi e ntlafalitsoe. Ka bokhutšoanyane, ho theha mokhoa o sebetsang oa ho boloka le ho fumana lintlha tse ngata ho kenyelletsa ho nahana ka litlhoko tsa data, ho khetha tharollo e nepahetseng ea polokelo, ho theha leano la tsamaiso ea data, ho theha mekhoa ea mekhoa e metle, ho kenya tsebetsong mekhoa e metle ea ho khutlisa data, le ho tsoela pele ho beha leihlo le ho ntlafatsa. tshebetso ya tsamaiso. 