Database Design and Analysis The following database project will create an educational attainment demand forecast for the state of California for years greater than 2010 The demand forecast is the expected number of population who have obtained a certain level of education The population is divided into age groups and education attainment is divided into different levels The population of each group is estimated for each year up to year 2050 Implement the following steps to obtain and educational demand forecast for the state of California That info in on CSV files we have to download, so below are the column names for each of the two tables we have to create Categories of CSV files are as follows educational attainment Year, Age, Gender, Educational Attainment, Personal Income, Population Count pop proj fips, county, year, age, pop female, pop male, pop total Write a query to select the total population in each age group Use the query from Step 6 as a subquery to find each type of education attained by the population in that age group and the fraction of the population of that age group that has that educational attainment Label the fraction column output as coefficient For instance, the fraction of the population in age group 00 17 who has an education attainment of Bachelor's degree or higher is 0 0015, which is the coefficient Create a demographics table from the SQL query from Step 7 Create a query on the pop proj table which shows the population count by date year and age Use that query from Step 9 as a subquery and join it to the demographics table using the following case statement demographics age case when temp pop age 18 then '00 to 17' when temp pop age 64 then '65 to 80 ' else '18 to 64' end temp pop is an alias for the subquery Use the following calculation for the demand output round(sum(temp pop total pop demographics coefficient)) as demand Output the demand grouped by year and education level Write each query you used in Steps 1 5 in a text file If a query produced a result set, the list then first ten rows of each row set after the query Bundle your lessons learned report and your query results text file into a single zip file and submit that zip file as your final portfolio

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Database Design and Analysis The following database project will create an educational attainment demand forecast for the state of California for years greater than 2010.

Database Design and Analysis

The following database project will create an educational attainment demand forecast for the state of California for years greater than 2010. The demand forecast is the expected number of population who have obtained a certain level of education. The population is divided into age groups and education attainment is divided into different levels. The population of each group is estimated for each year up to year 2050. Implement the following steps to obtain and educational demand forecast for the state of California. That info in on CSV files we have to download, so below are the column names for each of the two tables we have to create.

Categories of CSV files are as follows-

educational_attainment- Year, Age, Gender, Educational Attainment, Personal Income, Population Count

pop_proj- fips, county, year, age, pop_female, pop_male, pop_total

Write a query to select the total population in each age group.
Use the query from Step 6 as a subquery to find each type of education attained by the population in that age group and the fraction of the population of that age group that has that educational attainment. Label the fraction column output as coefficient. For instance, the fraction of the population in age group 00 - 17 who has an education attainment of Bachelor's degree or higher is 0.0015, which is the coefficient.
Create a demographics table from the SQL query from Step 7.
Create a query on the pop_proj table which shows the population count by date_year and age.
Use that query from Step 9 as a subquery and join it to the demographics table using the following case statement:

demographics.age = case when temp_pop.age < 18 then '00 to 17' when temp_pop.age > 64 then '65 to 80+' else '18 to 64' end

temp_pop is an alias for the subquery. Use the following calculation for the demand output:

round(sum(temp_pop.total_pop * demographics.coefficient)) as demand

Output the demand grouped by year and education level.

Write each query you used in Steps 1 5 in a text file. If a query produced a result set, the list then first ten rows of each row set after the query. Bundle your lessons learned report and your query results text file into a single zip file and submit that zip file as your final portfolio.