𝟭. 𝗱𝗯𝘁 → Transforms raw data into clean, analytics-ready models, ensuring consistent and reliable pipelines.
𝟮. 𝗔𝗽𝗮𝗰𝗵𝗲 𝗦𝗽𝗮𝗿𝗸 → We process massive datasets in batch or streaming mode, making big data analysis lightning fast.
𝟯. 𝗔𝗺𝗮𝘇𝗼𝗻 𝗥𝗲𝗱𝘀𝗵𝗶𝗳𝘁 → A managed cloud warehouse to store and query petabytes of data with minimal effort.
𝟰. 𝗔𝗽𝗮𝗰𝗵𝗲 𝗞𝗮𝗳𝗸𝗮 → Streams millions of events per second, powering real-time dashboards and event-driven systems.
𝟱. 𝗚𝗼𝗼𝗴𝗹𝗲 𝗕𝗶𝗴𝗤𝘂𝗲𝗿𝘆 → We run heavy SQL queries on huge datasets in seconds, without worrying about infrastructure.
𝟲. 𝗦𝗻𝗼𝘄𝗳𝗹𝗮𝗸𝗲 → Scales storage and compute separately, optimising performance and reducing cost.
𝟳. 𝗔𝗽𝗮𝗰𝗵𝗲 𝗙𝗹𝗶𝗻𝗸 → Processes high-speed event streams, enabling real-time insights and instant decision-making.
𝟴. 𝗗𝗮𝘁𝗮𝗯𝗿𝗶𝗰𝗸𝘀 → We use it as a unified platform for data engineering, advanced analytics, and machine learning.
𝟵. 𝗔𝗽𝗮𝗰𝗵𝗲 𝗡𝗶𝗙𝗶 → Automates data ingestion and routing between systems with simple drag-and-drop workflows.
𝟭𝟬. 𝗔𝗽𝗮𝗰𝗵𝗲 𝗔𝗶𝗿𝗳𝗹𝗼𝘄 → Orchestrates and schedules complex ETL pipelines, keeping data flow smooth and reliable.
𝟭𝟭. 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗮𝗯𝗿𝗶𝗰 → Integrates data engineering, science, and BI into one seamless analytics experience.
𝟭𝟮. 𝗧𝗿𝗶𝗻𝗼 → Queries data across multiple sources like a single database, saving time and reducing complexity.
