Tiléolúwanimí✨

VA | PM | Automation Specialist (for Finance, Operations, Tech), Data and AI enthusiast

[Tiléolúwanimí✨ @tileoluwanimi]

I am going to be mentally, spiritually, emotionally and financially stable. My health will not suffer and I refuse to come under attack. Nothing missing, nothing broken. I am going to be the best version of myself.

[Tiléolúwanimí✨ @tileoluwanimi]

@richtosho involve

[Tiléolúwanimí✨ @tileoluwanimi]

@Timmysofine It's my turn to go now and they approved this rubbish??
They should just scrap the whole thing.

[Tiléolúwanimí✨ @tileoluwanimi]

@_paullette_03 @moriaes_ @Timmysofine ...and talking about 'betray', man, you betrayed your wife first when you cheated on her

[Tiléolúwanimí✨ @tileoluwanimi]

@_paullette_03 @moriaes_ @Timmysofine Okay, this is wild! Like someone actually sat down, thought about this and typed it out?? A supposed grown man o.

[Ridwan 🇵🇹 @ridwan_on_x]

I started building my personal library since the day I visited my oga @Benn_X1.

For non-technical books, I learnt a trick from him to always carry one with me when going to work. As soon as I get on the train, I put my phone away and take out my book. This way, I read between 5 and 10 pages each day.

I could have chosen just soft copies, but since the day I saw his library and had a feel of the books, it sparked my interest in hard copies. Moreover, reading hard copies is easier than soft copies.

[Tiléolúwanimí✨ @tileoluwanimi]

@Opulent_Maisha Hi, I love reading and I'm so interested in this

[Tiléolúwanimí✨ @tileoluwanimi]

@officialladi_T I applied for Product Management too, I thought they said with zero experience....it got to a point that I started reading the questions out loud and like twice each.
Hoping for the best for us all..

[Tiléolúwanimí✨ @tileoluwanimi]

Haven't been posting here but still crushing my data engineering journey. From basic to complex subqueries in WHERE, SELECT, and FROM clauses. Mastered JOINs, aggregations, calculated fields. I'm currently on RDBMS where real-life entities become tabes 💪🏽💪🏽 #DataEngineering #SQL

[DataVidhya @thedatavidhya]

> The Data Engineering Tree 👇

| |── Introduction to Data Eng.
| ├── What is Data Engineering
| ├── Role of a Data Engineer
| ├── Data Engineer vs Data Scientist vs Analyst
| ├── Types of Data (Structured / Semi / Unstructured)
| ├── Batch vs Streaming Data
| └── Real-world Use Cases

| |── Programming Foundations
| ├── Python
| | ├── Data Types & Control Flow
| | ├── Functions & OOP
| | ├── File Handling
| | └── Error Handling
| ├── SQL
| | ├── CRUD Operations
| | ├── Joins
| | ├── Subqueries
| | ├── Window Functions
| | └── Indexing Basics
| └── Bash / Shell Scripting

| |── Data Modeling
| ├── OLTP vs OLAP
| ├── Normalization
| ├── Denormalization
| ├── Star Schema
| ├── Snowflake Schema
| └── Fact & Dimension Tables

| |── Databases
| ├── Relational Databases
| | ├── PostgreSQL
| | ├── MySQL
| | └── SQL Server
| ├── NoSQL Databases
| | ├── Key-Value (Redis)
| | ├── Document (MongoDB)
| | ├── Columnar (Cassandra)
| | └── Graph (Neo4j)
| └── Data Warehouses
| ├── BigQuery
| ├── Snowflake
| └── Redshift

| |── Data Ingestion
| ├── Batch Ingestion
| | ├─�� CSV / JSON / Parquet
| | └── Database Dumps
| ├── Streaming Ingestion
| | ├── Kafka
| | ├── Kinesis
| | └── Pub/Sub
| └── APIs & Web Scraping

| |── Data Processing
| ├── ETL vs ELT
| ├── Apache Spark
| | ├── RDD
| | ├── DataFrame
| | ├── Spark SQL
| | └── Spark Streaming
| ├── Apache Flink
| ├── MapReduce
| └── Data Transformation Logic

| |── Workflow Orchestration
| ├── Apache Airflow
| | ├── DAGs
| | ├── Operators
| | ├── Scheduling
| | └── Monitoring
| ├── Prefect
| └── Dagster

| |── Storage Systems
| ├── Data Lakes
| | ├── S3
| | ├── GCS
| | └── ADLS
| ├── File Formats
| | ├── CSV
| | ├── JSON
| | ├── Parquet
| | └── Avro
| └── Lakehouse Architecture

| |── Big Data Ecosystem
| ├── Hadoop
| | ├── HDFS
| | ├── YARN
| | └── MapReduce
| ├── Hive
| ├── HBase
| └── Presto / Trino

| |── Data Quality & Validation
| ├── Data Cleaning
| ├── Schema Validation
| ├── Null & Duplicate Handling
| ├── Great Expectations
| └── Data Consistency Checks

| |── Performance Optimization
| ├── Partitioning
| ├── Indexing
| ├── Bucketing
| ├── Caching
| └── Query Optimization

| |── Cloud Platforms
| ├── AWS
| | ├── S3
| | ├── Glue
| | ├── EMR
| | └── Redshift
| ├── GCP
| | ├── BigQuery
| | ├── Dataflow
| | └── Pub/Sub
| └── Azure
| ├── Data Factory
| ├── Synapse
| └── ADLS

| |── Data Security & Governance
| ├── Authentication & Authorization
| ├── IAM
| ├── Encryption (At Rest / In Transit)
| ├── Data Masking
| └── Compliance (GDPR, HIPAA)

| |── Monitoring & Reliability
| ├── Logging
| ├── Alerting
| ├── SLA Management
| ├── Data Drift Detection
| └── Pipeline Failure Handling

| |── Analytics & Consumption
| ├── BI Tools
| | ├── Tableau
| | ├── Power BI
| | └── Looker

[Tiléolúwanimí✨ @tileoluwanimi]

@cruisekotrol @Tech_Eloi Alright, thanks much.

[Tiléolúwanimí✨ @tileoluwanimi]

@buildwithprecio @cowrywise Thank you Precious, sure

[Tiléolúwanimí✨ @tileoluwanimi]

Joined @cowrywise as a Graduate Ambassador

Definitely looking forward to this journey!

[Tiléolúwanimí✨ @tileoluwanimi]

@Dammi_Esq Probably my second and last name, not my first name 😌

[Tiléolúwanimí✨ @tileoluwanimi]

@Ai_Vaidehi Thanks for the resource

[Tiléolúwanimí✨ @tileoluwanimi]

@Ai_Vaidehi SQL

[Tiléolúwanimí✨ @tileoluwanimi]

These past two years, I've learned patience. Pure waiting and praying. It gets to a point where you have this insane faith, like the generals of old you just know God's going to do something. It's a yes or yes.

[Tiléolúwanimí✨ @tileoluwanimi]

@aceofshade_ @cowrywise Thank you 😊

[Vaidehi @Ai_Vaidehi]

Normalization in SQL Notes in 12 Pages 📘
.
.
Bookmark it for future 🧵.
.
.
1/n
.
#sql #database

[Vaidehi @Ai_Vaidehi]

100 SQL Questions with Answers in 59 pages🔥

1/n