<prompt> Etsa moralo oa ho fetola data e latelangLintlha tsa lebenkele la korosari  <response>: Instruction in English: Develop a scheme to shift the following data . Response in English: Shifting grocery store data can be achieved through several methods depending on the desired outcome. Here is one possible scheme:1. Identify the format and structure of the data: The first step is to understand the format in which the data is stored and how its structured. Is it in a spreadsheet, database, or is it unstructured data?2. Determine the destination format: Identify the format in which the data needs to be shifted. For instance, if the data is currently in a spreadsheet, it could be shifted to a database management system or an inventory management software.3. Evaluate the compatibility: Evaluate if the destination system is compatible with the source data format. If not, you may need to convert the data to an intermediate format before shifting it.4. Prepare the data: Its essential to clean and normalize the data before transferring it. This step involves removing any inconsistencies, duplications or errors in the data.5. Map the data: Identify how the data maps from the source to the destination system. For example, how do the columns and rows in the spreadsheet translate to the fields in the database?6. Transfer the data: This could be done through an automated process using an ETL Extract, Transform, Load tool, or manually by exporting and importing the data between the source and destination systems.7. Test and validate: Once the data has been shifted, its crucial to test and validate it to ensure that it has been transferred correctly and that there are no errors or missing data. . Response in Sesotho: Ho fetola lintlha tsa lebenkele la korosari ho ka finyelloa ka mekhoa e mengata ho latela sephetho se lakatsehang. Mona ke morero o le mong o ka khonehang: 1. Hlalosa sebopeho le sebopeho sa data: Mohato oa pele ke ho utloisisa mokhoa oo boitsebiso bo bolokiloeng ka oona le kamoo bo hlophisitsoeng kateng. Na e ka hara spreadsheet, database, kapa ke data e sa hlophisoang? 2. Etsa qeto ea sebopeho sa sebaka: Hlalosa mokhoa oo data e lokelang ho fetoloa ka eona. Ka mohlala, haeba data e ntse e le ka hara spreadsheet, e ka fetisetsoa tsamaisong ea tsamaiso ea database kapa software ea tsamaiso ea thepa. 3. Lekola tšebelisano: Hlahloba hore na tsamaiso ea sebaka seo u eang teng e lumellana le mokhoa oa data oa mohloli. Haeba ho se joalo, ho ka na ha hlokahala hore u fetolele data ho sebopeho sa bohareng pele u e fetola. 4. Lokisetsa ya data: Ho bohlokoa ho hloekisa le ho tloaeleha ya data pele e fetisetsa. Mohato ona o kenyelletsa ho tlosa ho se lumellane hofe kapa hofe, ho pheta-pheta kapa liphoso ho data. 5. Mapa oa data: Hlalosa hore na data e etsa limmapa joang ho tloha mohloling ho ea ho sistimi ea moo e eang teng. Ka mohlala, litšiea le mela e ka hara spreadsheet li fetolela joang likarolong tse polokelong ea boitsebiso? 6. Fetisetsa lintlha: Sena se ka etsoa ka mokhoa o ikemetseng o sebelisa sesebelisoa sa ETL Extract, Transform, Load, kapa ka letsoho ka ho romela le ho kenya data pakeng tsa mohloli le mekhoa ea moo e eang teng. 7. Teko le ho netefatsa: Hang ha data e se e fetotsoe, ho bohlokoa ho e hlahloba le ho e netefatsa ho netefatsa hore e fetisitsoe ka nepo le hore ha ho na liphoso kapa lintlha tse sieo. 