Telecom Data Engineering Challenges Quiz

For data ingestion, technologies such as Apache Kafka, Apache NiFi, and Amazon Kinesis can be considered for real-time and scalable data ingestion from various sources.

For data processing, tools like Apache Spark, Apache Flink, and Hadoop MapReduce can be considered for parallel processing and analysis of large volumes of data.

For data storage, technologies like Hadoop Distributed File System (HDFS), Apache HBase, and Amazon S3 can be considered for scalable and distributed storage of large volumes of data.

<p>For data retrieval, technologies such as Apache Hive, Apache Druid, and Elasticsearch can be considered for querying and retrieving data for analytics and reporting.</p> Signup and view all the answers

<p>Scalability can be ensured by using technologies like container orchestration systems (e.g., Kubernetes) for managing and scaling application containers, and by implementing distributed data processing and storage systems that can horizontally scale as the data volume grows.</p> Signup and view all the answers

<p>Fault tolerance can be ensured by implementing data replication across multiple nodes, using technologies with built-in fault tolerance mechanisms (e.g., Apache Hadoop), and incorporating monitoring and alerting systems to detect and respond to failures in real-time.</p> Signup and view all the answers

<p>High availability can be ensured by deploying the architecture across multiple availability zones in cloud providers, using load balancers to distribute traffic, implementing auto-scaling to handle traffic spikes, and leveraging technologies with built-in high availability features (e.g., cloud-based storage services with replication and redundancy).</p> Signup and view all the answers

<p>Including cloud-based storage and compute provides benefits such as elasticity to scale resources based on demand, cost-effectiveness by paying only for the resources used, and managed services that offload the operational overhead of maintaining infrastructure.</p> Signup and view all the answers

<p>Implementing containerization systems like Docker and Kubernetes provides advantages such as portability, scalability, resource efficiency, and easier management of application deployment and updates.</p> Signup and view all the answers