![]() ![]() Also, since the analysts only know SQLite queries, they may not be well-versed in a production database. Essentially, this is like creating a "data production" user whose job it is is to always write new and existing data to the table.įuthermore, even though it wasn't according to the spec, we know that the IHW team's analysts just run read queries on the data. This is to make sure that someone who might get a hold of this user does not issue a destructive command. With a table set up, it's now time to create a user on the Postgres database that can insert, update, and read the data but not delete. User that can update, read, and insert into a table of the data.Table that contains the fields detailed in the CSV file.Database for the IHW to store their tables.Your job is to show that you can create a database that will accomplish the following requirements: This is much different than previous Guided Projects as you will be using your own notebook and your own Python environment instead of Dataquest's. In this Guided Project, you will be using the local installed version of Postgres you installed from the previous project. Pressure - Atmospheric pressure of the hurricaneīasin - The basin the hurricane is located Wind_kts - Wind speed in knots per second Long - Longitude of the recorded location Their CSV file contains the following fields: fid - ID for the row To understand what you will be working on, they have sent you a CSV file. Then, each analyst uses a local SQLite engine to store the CSV, run their queries, and send their results around.įrom what they have told you, you might be thinking that this is an inefficient way of sharing data. From what they've told you, it seems that their method of sharing the data with their data anaylsts has been to save a CSV file on their local servers and have every data analyst pull the data down. ![]() They have asked you, someone with experience in databases, to help work with their team to productionize their services.Īccepting the job, their team tells you that they have been having trouble sharing data across the teams and keeping it consistent. Because of the increase in public awareness of hurricanes, they are required to be more diligient with the analysis of historical hurricane data they share across the organization. Recently, the International Hurricane Watchgroup (IHW) has been asked to update their analysis tools. ![]()
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