You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 donor
【Schema】
# Table: donations
[
(donationid:TEXT, Primary Key, Examples: [000000a91a14ed37bef82e125c102e77]),
(projectid:TEXT, Examples: [ffffac55ee02a49d1abc87ba6fc61135]),
(donor_acctid:TEXT, Examples: [22cbc920c9b5fa08dfb331422f5926b5]),
(donor_city:TEXT, Examples: [Peachtree City, Rockville, Salem]),
(donor_state:TEXT, Examples: [GA, MD, IN]),
(donor_zip:TEXT, Examples: [30269, 20853, 47167]),
(is_teacher_acct:TEXT, Examples: [f, t]),
(donation_timestamp:DATETIME, Examples: [2011-08-25 14:27:34.807000]),
(donation_to_project:REAL, Examples: [42.5, 26.83, 55.35]),
(donation_optional_support:REAL, Examples: [7.5, 4.73, 0.0]),
(donation_total:REAL, Examples: [50.0, 31.56, 55.35]),
(dollar_amount:TEXT, Examples: [10_to_100, under_10, 100_and_up]),
(donation_included_optional_support:TEXT, Examples: [t, f]),
(payment_method:TEXT, Examples: [no_cash_received, creditcard, paypal]),
(payment_included_acct_credit:TEXT, Examples: [f, t]),
(payment_included_campaign_gift_card:TEXT, Examples: [t, f]),
(payment_included_web_purchased_gift_card:TEXT, Examples: [f, t]),
(payment_was_promo_matched:TEXT, Examples: [f, t]),
(via_giving_page:TEXT, Examples: [f, t]),
(for_honoree:TEXT, Examples: [f, t]),
(donation_message:TEXT)
]
# Table: projects
[
(projectid:TEXT, Primary Key, Examples: [00001ccc0e81598c4bd86bacb94d7acb]),
(teacher_acctid:TEXT, Examples: [42d43fa6f37314365d08692e08680973]),
(schoolid:TEXT, Examples: [c0e6ce89b244764085691a1b8e28cb81]),
(school_ncesid:TEXT, Examples: [063627006187, 483702008193, 410327000109]),
(school_latitude:REAL, Examples: [36.57634, 32.911179, 45.166039]),
(school_longitude:REAL, Examples: [-119.608713, -96.72364, -122.414576]),
(school_city:TEXT, Examples: [Selma, Dallas, Colton]),
(school_state:TEXT, Examples: [CA, TX, OR]),
(school_zip:INTEGER, Examples: [93662, 75243, 97017]),
(school_metro:TEXT, Examples: [urban, rural, suburban]),
(school_district:TEXT, Examples: [Selma Unified Sch District]),
(school_county:TEXT, Examples: [Fresno, Dallas, Clackamas]),
(school_charter:TEXT, Examples: [f, t]),
(school_magnet:TEXT, Examples: [f, t]),
(school_year_round:TEXT, Examples: [f, t]),
(school_nlns:TEXT, Examples: [f, t]),
(school_kipp:TEXT, Examples: [f, t]),
(school_charter_ready_promise:TEXT, Examples: [f, t]),
(teacher_prefix:TEXT, Examples: [Mrs., Mr., Ms.]),
(teacher_teach_for_america:TEXT, Examples: [f, t]),
(teacher_ny_teaching_fellow:TEXT, Examples: [f, t]),
(primary_focus_subject:TEXT, Examples: [Literature & Writing, Literacy, Social Sciences]),
(primary_focus_area:TEXT, Examples: [Literacy & Language, History & Civics, Math & Science]),
(secondary_focus_subject:TEXT, Examples: [College & Career Prep]),
(secondary_focus_area:TEXT, Examples: [Applied Learning, Literacy & Language, Math & Science]),
(resource_type:TEXT, Examples: [Books, Technology, Other]),
(poverty_level:TEXT, Examples: [highest poverty, high poverty, moderate poverty]),
(grade_level:TEXT, Examples: [Grades 6-8, Grades PreK-2, Grades 3-5]),
(fulfillment_labor_materials:REAL, Examples: [30.0, 35.0, 9.0]),
(total_price_excluding_optional_support:REAL, Examples: [555.81, 296.47, 430.89]),
(total_price_including_optional_support:REAL, Examples: [653.89, 348.79, 506.93]),
(students_reached:INTEGER, Examples: [32, 22, 17]),
(eligible_double_your_impact_match:TEXT, Examples: [f, t]),
(eligible_almost_home_match:TEXT, Examples: [f, t]),
(date_posted:DATE, Examples: [2014-05-12])
]
# Table: essays
[
(projectid:TEXT, Examples: [ffffc4f85b60efc5b52347df489d0238]),
(teacher_acctid:TEXT, Examples: [c24011b20fc161ed02248e85beb59a90]),
(title:TEXT, Examples: [iMath]),
(short_description:TEXT),
(need_statement:TEXT),
(essay:TEXT)
]
# Table: resources
[
(resourceid:TEXT, Primary Key, Examples: [0000037fecc4461faf0e49328ae66661]),
(projectid:TEXT, Examples: [ffffc4f85b60efc5b52347df489d0238]),
(vendorid:INTEGER, Examples: [430, 82, 767]),
(vendor_name:TEXT, Examples: [Woodwind and Brasswind]),
(project_resource_type:TEXT, Examples: [Technology, Supplies, Other]),
(item_name:TEXT),
(item_number:TEXT, Examples: [249995.001, BB11216668, VX748]),
(item_unit_price:REAL, Examples: [149.0, 148.0, 69.95]),
(item_quantity:INTEGER, Examples: [4, 1, 2])
]
【Foreign keys】
donations.projectid=projects.projectid
resources.projectid=projects.projectid

    【Question】
    Among the technology items, what percentage of them are from Best Buy for Business? Provide the date of the project related to those items. technology items refers to project_resource_type = 'Technology'; from Best Buy for Business refers to vendor_name = 'Best Buy for Business'; percentage refers to DIVIDE(count(case when vendor_name = 'Best Buy for Business'),count(projectid))

    【Evidence】
    technology items refers to project_resource_type = 'Technology'; from Best Buy for Business refers to vendor_name = 'Best Buy for Business'; percentage refers to DIVIDE(count(case when vendor_name = 'Best Buy for Business'),count(projectid))

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT CAST(SUM(CASE WHEN T1.vendor_name = 'Best Buy for Business' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.projectid) FROM resources AS T1 INNER JOIN projects AS T2 ON T1.projectid = T2.projectid WHERE T1.project_resource_type = 'Technology' UNION ALL SELECT DISTINCT T1.date_posted FROM projects AS T1 INNER JOIN resources AS T2 ON T1.projectid = T2.projectid WHERE T2.vendor_name = 'Best Buy for Business' AND T2.project_resource_type = 'Technology'