BigQuery is a server-less and cost-effective enterprise-grade data warehouse that operates across clouds and scales to the size of your data. It also comes including BI, machine-learning and AI included.
BigQuery is a fully-managed enterprise data warehouse that lets you analyze and manage your data by incorporating features such as geospatial analytics, machine learning along with business intelligence. BigQuery’s serverless design lets you make use of SQL queries to tackle your company’s most pressing questions without the need for infrastructure management. BigQuery’s distributed, scalable analytics engine allows you to search Terabytes in a matter of seconds or petabytes in minutes.
BigQuery offers maximum flexibility because it separates the computing engine that analyzes your data from the storage options. It is possible to store the data and then analyze it in BigQuery or make use of BigQuery to evaluate the location of your data. Federated queries allow you to take data from outside sources, and streaming can support continuous updates to data. Highly efficient tools such as BigQuery ML and BI Engine help you understand and analyze the data.
One of the biggest issues facing Technology Leaders today is keeping up with the latest technology and processes advancement. Infrastructure and technologies that are outdated cause systemic inflexibility which is exacerbated by skills shortages and excessive cost of ownership for systems, which reduces the efficiency by 50 percent (according to a study). Application Modernization offers the advantages of competitiveness and agility in business processes that are based on the latest technology and structures to reduce risks and reduce the total expense of owning.
Migrate confidently with expert design guidance and a proven methodology Flexible scaling without compromising performance
Reduce TCO eith flexible pricing bundies and services
Accelerate time to value with rapid POC and iterative offload
Simplify complexity with partner support and out of the box migration tools
A Customer with huge datasets in Amazon RDS wanted to use the same datasets for reporting purposes but to build a single report it was taking more than 2hrs and they wanted multiple reports with an option to change the filters in runtime.
Migrated the data from Amazon RDS to GCP BigQuery. Reduced reporting time from 2hrs to 15 secs with near real-time data with a lag of 15 minutes.
Assessment
Created Script for Schema Creation
Created Script for One-time migration
Created Airflow DAGs for Change Data Capture
Created Dashboards in Looker Studio (earlier Google Data Studio)
Assessment
Created Script for Schema Creation
Created Script for One-time migration
Created Airflow DAGs for Change Data Capture
Created Dashboards in Looker Studio (earlier Google Data Studio)