๐ง๐ต๐ฒ ๐ฏ๐๐ถ๐น๐ฑ๐ถ๐ป๐ด ๐ฏ๐น๐ผ๐ฐ๐ธ๐ ๐ผ๐ณ ๐๐ ๐ฎ๐ป๐ฑ ๐ฒ๐๐๐ฒ๐ป๐๐ถ๐ฎ๐น ๐ฝ๐ฟ๐ผ๐ฐ๐ฒ๐๐๐ฒ๐:
– Collect: Data from sensors, logs, and user input.
– Move/Store: Build infrastructure, pipelines, and reliable data flow.
– Explore/Transform: Clean, prep, and detect anomalies to make the data usable.
– Aggregate/Label: Add analytics, metrics, and labels to create training data.
– Learn/Optimize: Experiment, test, and train AI models.
๐ง๐ต๐ฒ ๐น๐ฎ๐๐ฒ๐ฟ๐ ๐ผ๐ณ ๐ฑ๐ฎ๐๐ฎ ๐ฎ๐ป๐ฑ ๐ต๐ผ๐ ๐๐ต๐ฒ๐ ๐ฏ๐ฒ๐ฐ๐ผ๐บ๐ฒ ๐ถ๐ป๐๐ฒ๐น๐น๐ถ๐ด๐ฒ๐ป๐:
– Instrumentation and logging: Sensors, logs, and external data capture the raw inputs.
– Data flow and storage: Pipelines and infrastructure ensure smooth movement and reliable storage.
– Exploration and transformation: Data is cleaned, prepped, and anomalies are detected.
– Aggregation and labeling: Analytics, metrics, and labels create structured, usable datasets.
– Experimenting/AI/ML: Models are trained and optimized using the prepared data.
– AI insights and actions: Advanced AI generates predictions, insights, and decisions at the top.
๐ช๐ต๐ผ ๐บ๐ฎ๐ธ๐ฒ๐ ๐ถ๐ ๐ต๐ฎ๐ฝ๐ฝ๐ฒ๐ป ๐ฎ๐ป๐ฑ ๐ธ๐ฒ๐ ๐ฟ๐ผ๐น๐ฒ๐:
– Data Infrastructure Engineers: Build the foundation โ collect, move, and store data.
– Data Engineers: Prep and transform the data into usable formats.
– Data Analysts & Scientists: Aggregate, label, and generate insights.
– Machine Learning Engineers: Optimize and deploy AI models.
๐ง๐ต๐ฒ ๐บ๐ฎ๐ด๐ถ๐ฐ ๐ผ๐ณ ๐๐ ๐ถ๐ ๐ถ๐ป ๐ต๐ผ๐ ๐๐ต๐ฒ๐๐ฒ ๐น๐ฎ๐๐ฒ๐ฟ๐ ๐ฎ๐ป๐ฑ ๐ฟ๐ผ๐น๐ฒ๐ ๐๐ผ๐ฟ๐ธ ๐๐ผ๐ด๐ฒ๐๐ต๐ฒ๐ฟ. ๐ง๐ต๐ฒ ๐๐๐ฟ๐ผ๐ป๐ด๐ฒ๐ฟ ๐๐ผ๐๐ฟ ๐ณ๐ผ๐๐ป๐ฑ๐ฎ๐๐ถ๐ผ๐ป, ๐๐ต๐ฒ ๐๐บ๐ฎ๐ฟ๐๐ฒ๐ฟ ๐๐ผ๐๐ฟ ๐๐.
