The storage stage focuses on persisting data to an appropriate storage system. Processing and analyzing is about transforming data into a form suitable for analysis. Exploring and visualizing focuses on testing hypotheses and drawing insights from data.
Understand the characteristics of streaming data. Streaming data is a set of data that is sent in small messages that are transmitted continuously from the data source. Streaming data may be telemetry data, which is data generated at regular intervals, and event data, which is data generated in response to a particular event. Stream ingestion services need to deal with potentially late and missing data. Streaming data is often ingested using Cloud Pub/Sub.
Understand the characteristics of batch data. Batch data is ingested in bulk, typically in files. Examples of batch data ingestion include uploading files of data exported from one application to be processed by another. Both batch and streaming data can be transformed and processed using Cloud Dataflow.
Know the technical factors to consider when choosing a data store. These factors include the volume and velocity of data, the type of structure of the data, access control requirements, and data access patterns.
Know the three levels of structure of data. These levels are structured, semi-structured, and unstructured. Structured data has a fixed schema, such as a relational database table. Semi-structured data has a schema that can vary; the schema is stored with data. Unstructured data does not have a structure used to determine how to store data.
Know which Google Cloud storage services are used with the different structure types. Structured data is stored in Cloud SQL and Cloud Spanner if it is used with a transaction processing system; BigQuery is used for analytical applications of structured data. Semi-structured data is stored in Cloud Datastore if data access requires full indexing; otherwise, it can be stored in Bigtable. Unstructured data is stored in Cloud Storage.
Know the difference between relational and NoSQL databases. Relational databases are used for structured data whereas NoSQL databases are used for semi-structured data. The four types of NoSQL databases are key-value, document, wide-column, and graph databases.
Review Questions
You can find the answers in the appendix.
1 A developer is planning a mobile application for your company’s customers to use to track information about their accounts. The developer is asking for your advice on storage technologies. In one case, the developer explains that they want to write messages each time a significant event occurs, such as the client opening, viewing, or deleting an account. This data is collected for compliance reasons, and the developer wants to minimize administrative overhead. What system would you recommend for storing this data?Cloud SQL using MySQLCloud SQL using PostgreSQLCloud DatastoreStackdriver Logging
2 You are responsible for developing an ingestion mechanism for a large number of IoT sensors. The ingestion service should accept data up to 10 minutes late. The service should also perform some transformations before writing the data to a database. Which of the managed services would be the best option for managing late arriving data and performing transformations?Cloud DataprocCloud DataflowCloud DataprepCloud SQL
3 A team of analysts has collected several CSV datasets with a total size of 50 GB. They plan to store the datasets in GCP and use Compute Engine instances to run RStudio, an interactive statistical application. Data will be loaded into RStudio using an RStudio data loading tool. Which of the following is the most appropriate GCP storage service for the datasets?Cloud StorageCloud DatastoreMongoDBBigtable
4 A team of analysts has collected several terabytes of telemetry data in CSV datasets. They plan to store the datasets in GCP and query and analyze the data using SQL. Which of the following is the most appropriate GCP storage service for the datasets?Cloud SQLCloud SpannerBigQueryBigtable
5 You have been hired to consult with a startup that is developing software for self-driving vehicles. The company’s product uses machine learning to predict the trajectory of persons and vehicles. Currently, the software is being developed using 20 vehicles, all located in the same city. IoT data is sent from vehicles every 60 seconds to a MySQL database running on a Compute Engine instance using an n2-standard-8 machine type with 8 vCPUs and 16 GB of memory. The startup wants to review their architecture and make any necessary changes to support tens of thousands of self-driving vehicles, all transmitting IoT data every second. The vehicles will be located across North America and Europe. Approximately 4 KB of data is sent in each transmission. What changes to the architecture would you recommend?None. The current architecture is well suited to the use case.Replace Cloud SQL with Cloud Spanner.Replace Cloud SQL with Bigtable.Replace Cloud SQL with Cloud Datastore.
6 As a member of a team of game developers, you have been tasked with devising a way to track players’ possessions. Possessions may be purchased from a catalog, traded with other players, or awarded for game activities. Possessions are categorized as clothing, tools, books, and coins. Players may have any number of possessions of any type. Players can search for other players who have particular possession types to facilitate trading. The game designer has informed you that there will likely be new types of possessions and ways to acquire them in the future. What kind of a data store would you recommend using?Transactional databaseWide-column databaseDocument databaseAnalytic database
7 The CTO of your company wants to reduce the cost of running an HBase and Hadoop cluster on premises. Only one HBase application is run on the cluster. The cluster currently supports 10 TB of data, but it is expected to double in the next six months. Which of the following managed services would you recommend to replace the on-premises cluster in order to minimize migration and ongoing operational costs?Cloud Bigtable using the HBase APICloud Dataflow using the HBase APICloud SpannerCloud Datastore
8 A genomics research institute is developing a platform for analyzing data related to genetic diseases. The genomics data is in a specialized format known as FASTQ, which stores nucleotide sequences and quality scores in a text format. Files may be up to 400 GB and are uploaded in batches. Once the files finish uploading, an analysis pipeline runs, reads the data in the FASTQ file, and outputs data to a database. What storage system is a good option for storing the uploaded FASTQ data?Cloud BigtableCloud DatastoreCloud StorageCloud Spanner
9 A genomics research institute is developing a platform for analyzing data related to genetic diseases. The genomics data is in a specialized format known as FASTQ, which stores nucleotide sequences and quality scores in a text format. Once the files finish uploading, an analysis pipeline runs, reads the data in the FASTQ file, and outputs data to a database. The output is in tabular structure, the data is queried using SQL, and typically queries retrieve only a small number of columns but many rows. What database would you recommend for storing the output of the workflow?Cloud BigtableCloud DatastoreCloud StorageBigQuery
10 You are developing a new application and will be storing semi-structured data that will only be accessed by a single key. The total volume of data will be at least 40 TB. What GCP database service would you use?BigQueryBigtableCloud SpannerCloud SQL
11 A group of climate scientists is collecting weather data every minute from 10,000 sensors across the globe. Data often arrives near the beginning of a minute, and almost all data arrives within the first 30 seconds of a minute. The data ingestion process is losing some data because servers cannot ingest the data as fast as it is arriving. The scientists have scaled up the number of servers in their managed instance group, but that has not completely eliminated the problem. They do not wish to increase the maximum size of the managed instance group. What else can the scientists do to prevent data loss?Write data to a Cloud Dataflow streamWrite data to a Cloud Pub/Sub topicWrite data to Cloud SQL tableWrite data to Cloud Dataprep
12 A software developer asks your advice about storing data. The developer has hundreds of thousands of 1 KB JSON objects that need to be accessed in sub-millisecond times if possible. All objects are referenced by a key. There is no need to look up values by the contents of the JSON structure. What kind of NoSQL database would you recommend?Key-value databaseAnalytical databaseWide-column databaseGraph database
13 A