Essential Big Data Skill Map: Tools, Languages, and Techniques You Need
Explore a comprehensive big data skill map covering processing frameworks like Spark and Hadoop, databases, programming languages, analytics tools, visualization libraries, AI techniques, algorithms, data structures, and cloud computing services, providing a practical reference for building expertise in modern data engineering.
Big Data Processing Frameworks
Spark : RDD, Spark SQL, Spark Streaming, MLLib
Hadoop : HDFS (distributed file system), MapReduce (computing framework), YARN (resource manager), Pig, Hive (SQL data warehouse), Mahout (machine‑learning library)
Kafka
Storm
ELK: Elasticsearch, Logstash, Kibana
Databases
SQL
MySQL
MongoDB
Cassandra
Redis
SQLite
bsddb
HBase
Programming Languages
Python
R
Ruby
Data Analysis & Mining
MATLAB
SPSS
SAS
Data Visualization
R
D3.js
ECharts
Excel
Artificial Intelligence Techniques
Clustering
Time Series
Recommendation Systems
Regression Analysis
Text Mining
Decision Trees
Support Vector Machines
Bayesian Classification
Neural Networks
Algorithms
Consistency
Paxos
Raft
Gossip
Data Structures
Stack, Queue, Linked List
Hash Table
Binary Tree, Red‑Black Tree, B‑Tree
Graph
Common Algorithms
Sorting (Insertion, Bucket, Heap, Quick)
Maximum Subarray
Longest Common Subsequence
Minimum Spanning Tree
Shortest Path
Matrix Storage and Operations
Cloud Computing
Cloud Services: SaaS, PaaS, IaaS
OpenStack
Docker
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