Knoldus Blogs

Google Cloud Platform: Migrating Data to New Schemas on Big Query Using Dataflow

February 1, 2023February 14, 2023AI, GCP, ML, AI and Data EngineeringApache Beam, BigQuery, Data, Data Migration, Dataflow, Google Cloud, Pipelines, python

Reading Time: 6 minutes Migrating data on Google Cloud BigQuery may seem like a straightforward task, until you run into having to match old data to tables with different schemas and data types. There are many approaches you can take to moving data, perhaps using SQL commands to transform the data to be compatible with the new schema. However, SQL has limitations as a programming language, being a query-centric Continue Reading

Dynamic Schema & Data Loading Into BigQuery

July 1, 2022July 5, 2022Studio-DevOpsBigQuery

Reading Time: 3 minutes BigQuery is a fully managed enterprise data warehouse that helps you manage and analyze your data with built-in features like machine learning, geospatial analysis, and business intelligence. BigQuery’s serverless architecture lets you use SQL queries to answer your organization’s biggest questions with zero infrastructure management. BigQuery’s scalable, distributed analysis engine lets you query terabytes in seconds and petabytes in minutes. Scope – Dynamic schema & Continue Reading

Spring Cloud GCP And BigQuery: A Way Large Dataset Handle

June 22, 2022June 22, 2022Java, Spring, spring boot, Spring Cloud, Spring Cloud Gateway, Spring Cloud GCPBigQuery, java, Spring Cloud GCP

Reading Time: 5 minutes Introduction In this example, we are going to cover how to load data into the BigQuery table and query the table using GCP console and API. We will use Spring Cloud GCP to make our application ready for accessing the Google Cloud Platform services. Spring Cloud GCP and BigQuery Spring Cloud GCP and BigQuery is a library that provides support for Google Cloud Platform (GCP) Continue Reading

Spring GCP BigQuery

May 14, 2022May 17, 2022Cloud, GCP, Java, Spring, spring boot, Spring Cloud GCPBigQuery, Spring Cloud GCP

Reading Time: 3 minutes BigQuery is Google’s fully managed, petabyte scale, low cost analytics data warehouse. It’s Serverless, highly scalable, and cost-effective multicloud data warehouse designed for business agility. BigQuery Benefits Gain insights with real-time and predictive analytics– Query streaming data in real time and get up-to-date information on all your business processes. Predict business outcomes easily with built-in machine learning–without the need to move data. Access data and Continue Reading

How to Fetch the Data from Bigquery with Java

April 29, 2022April 29, 2022Test Automation Studioautomation testing, BigQuery, Testing

Reading Time: 2 minutes BigQuery is a managed data warehouse and is part of the Google Cloud Platform. so in this blog, we can learn how to fetch the data from bigquery with java. BigQuery Jobs Jobs are actions that BigQuery runs on your behalf to load data, export data, query data, or copy data. When you want to run a query or transfer data from one dataset to another, you send a job description Continue Reading

BigQuery: Querying nested arrays

March 29, 2022March 29, 2022Big Data and Fast Data, Cloud, Database, GCP, NoSql, SQLBig Data Analytics, BigQuery, data analysis, query, sql

Reading Time: 2 minutes In a previous blog, we had seen BigQuery facilitate efficient data warehouse schema design. BigQuery supports the nested & repeated columns. We can use a combination of ARRAY and STRUCT data types to define our schema in BigQuery. It enables to denormalize data efficiently in single table. In this blog, for the same schema of sales data, we will execute a few DML operations on nested array fields. Schema In Continue Reading

BigQuery: Efficient Data Warehouse Schema Design

March 29, 2022March 29, 2022Big Data and Fast Data, Cloud, Database, GCP, NoSqlBig Data, Big Data Analytics, Big Data Storage, BigQuery, cloud data warehouse, schema

Reading Time: 3 minutes Conventional data warehouses support data models based on star schema and snowflake schema. In these models, there are a number of fact tables and dimension tables. In order to minimize redundancy it is recommends to split data into multiple tables in . This is a normalization process. Normalization is the technique of eliminating the redundant data. It minimize the insertion, deletion, and update anomalies. It saves the disk Continue Reading

BigQuery: Rescue to the Conventional Data warehouse Problems

March 28, 2022March 28, 2022Big Data and Fast Data, Cloud, Database, GCP, ML, AI and Data EngineeringBigQuery, cloud data warehouse, data analysis, Gcp

Reading Time: 4 minutes The present and future of every industry sector somehow depends on the ability to use the massive amounts of data. Use the data available to drive better product quality at a lower cost. Make favourable business decisions with data. Primarily, for decades, to store a wide variety of massive data and perform analysis on it, using Data Warehouse solutions. Traditional data warehouses designed on-premise specifically Continue Reading

Google BigQuery: An Introduction to Big Data Analytics Platform.

December 8, 2021December 8, 2021Big Data and Fast Data, Cloud, ML, AI and Data Engineering, Studio-ScalaBig Data, Big Data Analytics, BigQuery, Cloud, Google Cloud Platform, Google Cloud Storage, Machine Learning

Reading Time: 6 minutes Hey Folks, Today we going to discuss Google BigQuery, an enterprise data warehouse with built-in machine learning capabilities. Before going to BigQuery, let’s understand what is Google Cloud Platform?Google Cloud Platform is a suite of public cloud computing services offered by Google. The platform includes a range of hosted services for compute, storage and application development that run on Google hardware. Google Cloud protects your data, applications, Continue Reading