Data & AI

Data & AI Offerings and Practices

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Data & AI by Mind Map: Data & AI

1. Offerings

1.1. Data Strategy & Governance

1.1.1. Data Governance Practices and Frameworks

1.1.2. Data Catalog

1.1.3. Data Linage & Provenance

1.1.4. Data Security & Privacy

1.1.5. Data Culture & Democratization

1.1.6. Data Management Practices

1.1.6.1. MDM

1.1.6.2. Hub & Spoke

1.2. Data Readiness

1.2.1. Data Architecture

1.2.2. Data Engineering

1.2.3. Data Quality

1.2.4. Data Platforms

1.2.4.1. Relational DBs

1.2.4.1.1. SQL Development

1.2.4.1.2. Stored Procedures

1.2.4.1.3. Database Administration

1.2.4.1.4. Database Design and Implementation

1.2.4.2. Legacy Big Data

1.2.4.3. Modern Data Platform

1.2.4.3.1. Azure

1.2.4.3.2. GCP

1.2.4.3.3. Databricks

1.2.4.3.4. Snowflake

1.2.4.3.5. AWS

1.2.4.4. Customer Data Platform

1.2.4.4.1. Segment

1.2.4.4.2. SalesForce

1.2.4.4.3. GCP

1.3. Analytics & AI Solutions

1.3.1. Advanced Analytics

1.3.1.1. Reports

1.3.1.2. Dashboards

1.3.1.3. Self-Service Analytics

1.3.2. ML

1.3.2.1. Predictive Models

1.3.2.2. Diagnostic Models

1.3.2.3. Optimization / Prescription Models

1.3.3. Cognitive AI

1.3.3.1. Vision

1.3.3.1.1. OCR

1.3.3.2. Speech

1.3.3.3. NLU and NLP

1.3.4. Gen AI and LLMs

1.3.4.1. Chatbots

1.3.4.2. RAGS

1.3.4.3. AI Agents

1.4. AI @ Scale

1.4.1. MLOps

1.4.2. AI Democratization

1.4.3. AI Data Readiness

2. Practices

2.1. AI

2.1.1. Data Science

2.1.2. ML Engineers

2.1.3. AI Engineers

2.2. Analytics

2.2.1. BI & Analytics Developers

2.2.2. Analytics Engineers

2.3. Data Management

2.3.1. Data Engineers

2.3.2. Data Governance Specialists

2.3.3. SQL Developers

2.3.4. DBAs