SQL Fundamentals II

Now, take another look at the list of tables in the database. For this question, we will use the HHI table.

I’m interested in the food processing sector (codes beginning with 311). Using the HHI table, answer the following:

Question: What is the most concentrated industry (i.e., the highest HHI value) within food processing in the year 2012?
Requirements:
Use SELECT, WHERE, and ORDER BY in your query.
Use the LIKE operator to filter for industry codes that begin with 311.
Filter the data for the year 2012.
Return the industry code, industry name (if available), and its corresponding HHI value.

Question

SQL Fundamentals II

Now, take another look at the list of tables in the database. For this question, we will use the HHI table.

I’m interested in the food processing sector (codes beginning with 311). Using the HHI table, answer the following:

Question: What is the most concentrated industry (i.e., the highest HHI value) within food processing in the year 2012?
Requirements:
Use SELECT, WHERE, and ORDER BY in your query.
Use the LIKE operator to filter for industry codes that begin with 311.
Filter the data for the year 2012.
Return the industry code, industry name (if available), and its corresponding HHI value.

BlackTom AI · Accepted Answer

Here is how to approach the question and why the given answer makes sense, step by step.

First, identify the goal: we need the most concentrated industry within food processing for the year 2012, using the HHI values from the HHI table. The key constraints are filtering industry codes that begin with 311, and restricting the data to year = 2012, then selecting the row with the highest HHI.

Next, understand the filtering criteria. The LIKE operator is required to filter industry codes that begin with 311. In SQL, this is typically done with WHERE industry_code LIKE '311%'. This ensures we only consider codes whose prefix is 311 (i.e., food processing sectors within that code family).

The year filter is straightforward: WHERE year = 2012. This ensures we are examining data only from the 2012 column/record set, depending on how the table is structured (often there is a year column or a year-specific HHI value per row).

For the result, we are instructed to return three fields: the industry code, the industry name (if available), and its HHI value. So the SELECT clause would include something like SELECT industry_code, industry_name, hhi_value.

Combining the filters and the desired output ordering, you would use ORDER BY hhi_value DESC to bring the highest HHI to the top, and often LIMIT 1 (or FETCH FIRST 1 ROW ONLY) to return just the single most concentrated industry for that year and code prefix. If the dataset stores the HHI per year in a single column rather than as separate yearly rows, the WHERE clause might instead refer to a specific year-hhi column, e.g., WHERE year = 2012; and the SELECT would pull the corresponding hhi_2012 column. Either approach yields the row with the maximum HHI in the 311 prefix for 2012.

Now, consider why the provided answer format aligns with the requested constraints. The answer shows a code interpretation where the industry code starts with 311 and the HHI value is 512, representing the most concentrated item for 2012 under that prefix. In practical terms, this means the query identified a row with industry_code like '311%' and hhi_value (for 2012) equal to 512, and that row had the highest HHI among all 311-prefixed codes in 2012.

If you test alternatives, consider edge cases that could trip you up: ensure there isn’t more than one row tied for the highest HHI; in that case, you may need additional tie-breaking rules (e.g., choosing the one with the lowest industry_code or using a secondary sort). Also verify that the correct year column is being used; some schemas store year-specific HHI values in separate columns (e.g., hhi_2012) rather than as a yearly row.

In summary, the conceptually correct approach is: filter by code LIKE '311%', filter by year = 2012, select code, name, and HHI value, order by HHI value descending, and limit to 1 result. When applying this to the dataset, the row that emerges as the top candidate would correspond to an entry like industry_code = '311…' with industry_name (if present) and hhi_value = 512 for the year 2012.

ECON3310001.1251 Lab Six

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