Big data is the massive amount of data available to organizations. Because of its volume and complexity it is not easily managed or analyzed by many business intelligence tools. Tools for big data can help with the volume of the data collected, the speed at which that data becomes available to an organization for analysis, and the complexity or varieties of that data.
Google Cloud Big Data and Machine Learning Fundamentals introduce participants to the capabilities of the Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants get an overview of the Google Cloud and a detailed view of the data processing and machine learning capabilities.
- Data analysts, Data scientists, Business analysts getting started with Google Cloud
- Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports
- Executives and IT decision makers evaluating Google Cloud for use by data scientists
- Identify the purpose and value of the key Big Data and Machine Learning products on Google Cloud
- Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud
- Employ BigQuery and Cloud Datalab to carry out interactive data analysis
Here are some Google Cloud Big Data Services :
Google Cloud BigQuery
BigQuery lets you store and query datasets holding massive amounts of data. The service uses a table structure, supports SQL, and integrates seamlessly with all GCP services. You can use BigQuery for both batch processing and streaming.
Google Cloud Dataflow
Dataflow offers serverless batch and stream processing. You can create your own management and analysis pipelines, and Dataflow will automatically manage your resources. The service can integrate with GCP services like BigQuery and third-party solutions like Apache Spark.
Google Cloud BigTable
Bigtable is a fully-managed NoSQL database service built to provide high performance for big data workloads. Bigtable runs on a low-latency storage stack, supports the open-source HBase API, and is available globally.
P2L offers a course on Google Cloud Big Data and Machine Learning Fundamentals. If you are interested in taking this course, please contact us here.