DIDatabase Insightsindatabaseinsights.hashnode.dev·5d ago · 7 min readAutomating the Mundane: 5 Database Tasks Every Growing IT Team Should Stop Doing ManuallyAsk most DBAs what they should be spending their time on, and you'll hear architecture, query tuning, capacity planning, and performance optimization. Now check their backlog: it’s full of schema comp00
CYchetan yadavinlevelupcareers.hashnode.dev·6d ago · 17 min readHeterogeneous Migration Pitfalls: Data Type and Collation TrapsExecutive Summary Heterogeneous migration fails in the details that no summary report flags. The schema converts, the row counts match, the cutover runbook gets its green check, and three days later f00
CYchetan yadavinlevelupcareers.hashnode.dev·Jul 27 · 18 min readHomogeneous Migration in Oracle 19c to 23ai: Full WalkthroughExecutive Summary A homogeneous migration — same engine, Oracle to Oracle — feels like the safe kind. No endianness conversion, no schema translation, no ora2pg type-mapping surprises. The data model 10
STSagar Thosarinunscriptedthoughts.hashnode.dev·Jun 14 · 3 min readTo the People Nobody Notices Until Something BreaksBetter late than never :) While extracting some old files from a retired PC, I stumbled upon this write-up. Reading it again reminded me why I had written it in the first place. What follows was wri10
STSagar Thosarinsagarthosar.hashnode.dev·Jun 5 · 13 min readOracle 26ai — Setting Up Data Guard Per Pluggable Database (DGPDB) From ScratchLevel: Advanced DBAReading time: ~20 minutes Introduction Traditional Oracle Data Guard protects the entire CDB — if you want to failover, everything moves together. But in a multitenant environment w00
SKSoumyajeet Khuntiainsqldbcraft.hashnode.dev·May 23 · 3 min readSQL Server Index Rebuild vs Reorganize — What Every DBA Should KnowIndexes are one of the most important and complex components in SQL Server. From DBAs and software engineers to technical managers, everyone working with databases should have a basic understanding of00
STSagar Thosarinsagarthosar.hashnode.dev·May 20 · 19 min readOracle to AWS PostgreSQL: The Migration Gotchas Nobody Puts in the RunbookThe full load finished - Row counts matched -DMS showed zero errors. The team went home feeling like the hard part was over. By 9 AM, the application was throwing errors nobody had seen before. Querie00
UUllmaninitsantiago.hashnode.dev·Feb 21 · 10 min readChapter 3: 데이터 가공을 위한 SQL6강. 여러 개의 값에 대한 조작 1. 여러 값 비교하기 분기별 매출 증감 판정 CASE 문을 사용해 분기별 매출 증감을 '+', '-', ' '로 표시 SIGN() 함수: 양수(1), 0, 음수(-1) 반환 SELECT year, q1, q2, CASE WHEN q1 < q2 THEN '+' WHEN q1 = q2 THEN ' ' ELSE '-' END AS judge_q1_q2, ...00
UUllmaninitsantiago.hashnode.dev·Feb 21 · 14 min readChapter 5: 사용자를 파악하기 위한 데이터 추출11강. 사용자 전체의 특징과 경향 찾기 사용자 속성과 행동 패턴을 분석하여 서비스 개선에 활용하는 방법 1. 사용자의 액션 수 집계하기 액션과 관련된 지표 집계 UU (Unique Users): 중복 없이 집계된 사용자 수 사용률 (usage_rate): 특정 액션 UU / 전체 UU 1인당 액션 수: 액션 수 / 액션 UU WITH stats AS ( SELECT COUNT(DISTINCT session) AS total_uu ...00
UUllmaninitsantiago.hashnode.dev·Feb 21 · 9 min readChapter 4: 매출을 파악하기 위한 데이터 추출9강. 시계열 기반으로 데이터 집계하기 시계열 데이터를 다양한 관점에서 집계하여 매출 추이를 분석하는 방법 1. 날짜별 매출 집계하기 매출 집계의 기본: 날짜별 매출과 평균 구매액 집계 SELECT dt, COUNT(*) AS purchase_count, SUM(purchase_amount) AS total_amount, AVG(purchase_amount) AS avg_amount FROM purchase_log...00
