Learning area

Databases

Suppose a maintenance team has years of inspection records. Before we can train a model, we need to know which machine each reading belongs to and what was known at the time. Start with tables and SQL. Then consider an inspection with its own nested details, readings arriving at several sites, or a fault that spreads through connected equipment. Those questions give us reasons to try other ways of storing and querying the records. We will keep asking what each choice makes easier and what we must now manage ourselves.

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Working with relational databases

SQLBotie's maintenance team has years of inspections, equipment details and sensor readings. How can we use those records to answer a specific question without counting the wrong visits or mixing up assets? Begin with a table and a small query, then work toward analytical queries and dependable databases. The lessons also follow the data into machine learning, where the time a record became available matters as much as its value.34 lessons

Storing records around how we use them

NoSQLA technician wants the whole inspection on one screen. A sensor needs to send readings quickly, while the dashboard keeps asking for the latest one. Should all of those jobs store their records in the same way? Work through keys and documents with Botie, then follow what happens when we divide the records among machines or keep several copies. Each choice changes the questions we can answer easily and the failures we need to handle.18 lessons

Asking questions about connections

Graph DatabasesA pump fails. Which equipment depends on it, and which inspection tells us why that connection matters? The answer follows relationships across the records. We will give those relationships a place in the database, learn to query their patterns, and build traversals with Botie. As the graph grows, we will handle repeated routes, conflicting identities and evidence that has gone out of date.14 lessons