Big Data

Problem

Data is getting larger, more complex, and moving faster than ever — a growth that is largely spurred by the widespread adoption of cloud computing.

With so many computers around the world connecting and transmitting data via the cloud, the challenge for developers is how to harness enormous amounts of data in a meaningful way.

Solution Sketch

[solution or solution sketche(s)]

(batch data processing with Spark; real-time data processing with Kafka; data catalog)

Constraints / Limitations

[limits to approach]

Key OSS Techs

Spark
Kafka
Flink

Example Cloud(s)

[at least two public clouds as examples]
[list services and features used for solutions]

IBM Cloud	GCP	AWS	Azure	Operator
Analytics Engine	Dataproc	EMR	HDInsight	Spark Operator
Event Streams	Pub/Sub	MSK	Event Hubs	Kafka Operator
	Dataproc			Flink Operator
SQL Query	BigQuery	Redshift	Synapse Analytics	n/a

Where to Find More?

Blogs

[list of related videos and articles]

Videos

[list of related videos]

Tutorials

[list of related tutorials]

APIs

Containers