Data Platform Rock Star
Felipe Moz learning path to be a Data Platform Rock Start
1. Certifications
1.1. Azure Data Engineer Associate
1.2. Azure AI Engineer Associate
1.3. Azure Data Scientist Associate
1.4. MCSE: Data Management and Analytics
1.5. AWS Certified Solutions Architect – Associate
1.6. AWS Certified SysOps Administrator – Associate
1.7. AWS Certified Big Data – Specialty
1.8. AWS Certified Solutions Architect – Professional
1.9. AWS Certified Machine Learning – Specialty
1.10. Google Professional Cloud Architect
1.11. Google Professional Data Engineer
1.12. Hortonworks HDPCA
1.13. CKA
1.14. EXIN Devops
1.15. LPI (101,102)
2. Soft Skills
2.1. Languages
2.1.1. English Tech
2.1.2. English to understand an indian
2.1.3. English to do a pitch
2.2. Curious
2.2.1. Don't look obvious
2.2.2. Outliers tells more about data
2.2.3. Keep looking always
2.2.4. Join Slack Tech channels
2.3. Self-learning
2.3.1. All apache documents
2.3.2. at least 100h studing every year
2.4. Be friendly, not stupid.
3. Tech Skills
3.1. Database
3.1.1. Vendors
3.1.1.1. Oracle
3.1.1.2. PostgresSQL
3.1.1.3. Mysql
3.1.1.4. MS SQL Server
3.1.1.5. SAP
3.1.2. Modeling
3.1.2.1. 3FN (OLTP)
3.1.2.2. Star-schema (OLAP)
3.1.2.3. Snowflake
3.1.2.4. Concept Model
3.1.2.4.1. Phisical
3.1.2.4.2. Logical
3.1.2.5. Account
3.1.2.6. Semantic Data Modeling
3.1.2.7. ACID vs BASE
3.1.3. NoSQL Modeling
3.1.3.1. DocumentDB
3.1.3.1.1. MongoDB
3.1.3.1.2. Azure Cosmos
3.1.3.2. Wide-collumn
3.1.3.2.1. Cassandra
3.1.3.2.2. HANA
3.1.3.3. Key-value
3.1.3.3.1. Cassandra
3.1.3.3.2. ScyllaDB
3.1.3.4. Graph
3.1.3.4.1. Neo4J
3.1.4. Database Support Skills
3.1.5. NewSQL
3.1.5.1. Vendors
3.1.5.1.1. Memsql
3.1.5.1.2. NDB
3.1.6. Metadata
3.1.6.1. Lineage
3.1.6.2. Data Catalog
3.1.6.3. Business Catalog
3.1.6.4. Reverse Engineering
3.1.6.5. Generalization
3.1.6.6. Association
3.1.6.7. Multiplicity
3.1.6.8. Agregation
3.2. Distributed Systems
3.2.1. Hadoop
3.2.1.1. Compression
3.2.1.1.1. ORC
3.2.1.1.2. Parquet
3.2.1.1.3. No compression
3.2.1.2. Sqoop
3.2.2. Zookeeper Behavior
3.2.2.1. Fense
3.2.2.2. Voting method
3.2.2.3. Voting times
3.2.3. Spark
3.2.3.1. RDD
3.2.3.2. Dataframe
3.2.3.3. SparkQL
3.2.3.4. Pyspark
3.2.3.5. Streaming
3.2.4. Hive
3.2.4.1. LLAP
3.2.4.2. External Table
3.2.5. Mapreduce
3.2.5.1. TEZ
3.2.5.2. without TEZ
3.2.6. Others
3.2.6.1. YARN
3.2.6.2. Queue
3.2.6.3. Livy
3.2.6.4. Kafka
3.3. DataVIz
3.3.1. Query Explanation
3.3.2. Tableau Platform Admin
3.3.3. PowerBI Server Deployment
3.3.4. D3.js
3.3.5. Business Objects
3.3.6. Python Notebook
3.3.6.1. Jupyter
3.3.6.2. Zeppelin
3.4. Operation Systems
3.4.1. Linux
3.4.1.1. Redhat
3.4.1.2. Debian
3.4.1.3. AIX
3.4.1.4. Free-bsd
3.4.2. Windows
3.4.2.1. Server
3.4.3. Forget RISC platforms =)
3.5. ETL
3.5.1. Extract
3.5.2. Transform
3.5.3. Load
3.5.4. Vendors
3.5.4.1. Informatica
3.5.4.2. Talend
3.5.4.3. Pentaho
3.5.4.4. SSIS
3.5.4.5. Data Services
3.5.4.6. Data Quality
3.5.4.7. Information Stewart
3.6. DevOps
3.6.1. CI/CD
3.6.1.1. Jenkins
3.6.2. Version
3.6.2.1. Git
3.6.2.2. SVN
3.6.3. Everything as a code
3.6.3.1. Load balance
3.6.3.2. Reverse proxy
3.6.3.3. Caching server
3.6.3.4. Networking
3.6.4. Automation
3.6.4.1. Ansible
3.6.4.2. Puppet
3.6.4.3. Chef
3.6.4.4. Terraform
3.6.5. Monitoring
3.6.5.1. ELK
3.6.5.2. Splunk
3.6.5.3. Graphana
3.6.6. Docker
3.6.6.1. Registry
3.6.6.2. Composers
3.6.6.3. Orchestration
3.6.6.3.1. Kub8s
3.6.6.3.2. Swarm
3.7. SRE
4. Seeking
4.1. Laws
4.1.1. Data Protection
4.1.2. GDPR
4.1.3. PII
4.1.4. Legal Hackers
4.2. Announcements
4.2.1. Apache Mailing List
4.2.2. Events
4.3. Deepweb
4.3.1. Kernel Leaks
4.3.2. Ubuntu bugs
4.3.3. Kyllin like a rock
4.3.4. anon
4.3.5. Hidden Wiki (for a good proposes)
4.3.6. Duck Duck Go with care
4.4. UN
4.4.1. Social data for good
4.4.2. Blockchain initiatives
4.4.3. Globla KPIs
4.5. Medium
4.5.1. to post
4.5.2. to read
4.5.3. to shit-it
5. Professional Networking
5.1. Linkedin
5.2. Microsoft MVP
5.3. Vendor Events
5.4. Meetups
5.5. Slack
5.6. Hackathons
6. Cloud
6.1. Amazon Web Services
6.1.1. EC2
6.1.2. EMR
6.1.3. VPC & Subnet
6.1.4. Lambda
6.1.5. S3
6.1.6. SQS & SNS
6.1.7. Route53
6.1.8. Machine Learning
6.2. Google Cloud Platform
6.2.1. Compute Engine
6.2.2. Dataproc
6.2.3. Storage
6.2.4. Functions
6.2.5. Machine Learning
6.2.6. Automl
6.3. Azure
6.3.1. Virtual Machines
6.3.2. HDInsight
6.3.3. Virtual Networking
6.3.4. IA
6.3.5. Databricks