After collecting and transforming your cleaned data centrally in the cloud, you can start analysing. Data analytics provides insights that can help you drive better business decisions such as:
Standard analytics
requires some basic knowledge of structured query language (SQL), focuses mostly on two types of analytics:
Machine learning - based analytics
Analytics using machine learning might require a data analyst or data scientist, unlocks new analytics such as
Set up your data warehouse in seconds and start to query your data immediately. Google BigQuery runs blazing-fast SQL queries on gigabytes to petabytes of data and makes it easy to join public or commercial datasets with your data. Eliminate the time-consuming work of provisioning infrastructure and reduce your downtime with a serverless infrastructure that handles all ongoing maintenance, including patches and upgrades. BigQuery uses simple ANSI-compliant SQL and provides ODBC and JDBC drivers to make integration with your data fast and easy.
Get insights from your data faster without needing to copy or move it. Google BigQuery gives you a full view of all your data by seamlessly querying data stored in BigQuery’s managed columnar storage, Cloud Storage, Cloud Bigtable, Sheets, and Drive. BigQuery integrates with existing ETL tools like Informatica and Talend to enrich the data you already use. BigQuery supports favourite BI tools like Tableau, MicroStrategy, Looker, and Data Studio out of the box, so anyone can easily create stunning reports and dashboards. Automatically ingest and visualise Google Ads and marketing data using BigQuery Data Transfer Service to set up a high-powered marketing data warehouse in just a few clicks.
Build, test, and operationalise custom machine learning models using familiar SQL and greatly simplify the model-building process with automated feature engineering, model selection, and hyper tuning steps. Store trained models inside BigQuery and share effortlessly with stakeholders for seamless collaboration.
Build machine learning models in minutes instead of days or weeks directly inside BigQuery without the need to extensively sample the data or move it out of the data warehouse for training. Optionally, BigQuery ML can automatically update the trained ML models based on changes in the underlying data, saving time from manually retraining models.
Use the power of BigQuery’s serverless architecture and the power of Google Cloud to train ML models on petabyte-scale data in minutes — a fraction of the time compared to conventional systems. Enable data analysts and citizen data scientists in your organisation to collaborate and build ML solutions easily. BigQuery ML empowers you to make mission-critical predictive analytics solutions without compromise.
