BigQuery WITH & CTE Statements: Syntax & Usage Simplified 101 May 17th, 2024 By Osheen Jain in BigQuery, Data Warehousing The Common table expressions, commonly known as CTEs in SQL Server, is a tool that allows users to design and arrange queries. It has faster development, troubleshooting, and performance improvement.…
How to Set Up BigQuery JDBC Connection – 4 Easy Steps May 17th, 2024 By Dimple M K in BigQuery, Data Warehousing Organizations use Google BigQuery Data Warehouse for analytics and querying large, complex datasets. BigQuery is based on Dremel architecture that divides the query execution into slots. When multiple users are…
Oracle BigQuery Comparison: 11 Critical Differences May 10th, 2024 By Veeresh Biradar in BigQuery, Data Warehousing, Versus Before the database system was invented, data was commonly stored in flat files like text files or CSV files. OracleDB was invented very early with a very large market across…
Apache Druid vs BigQuery: 18 Key Differences May 10th, 2024 By Dimple M K in BigQuery, Data Warehousing, Versus Enterprises need a Data Warehouse to examine data over time and deliver actionable business intelligence. The need to efficiently pull together data from a broad array of ever-evolving data sources…
BigQuery vs Snowflake: Choosing the Right Data Warehouse in 2024 May 10th, 2024 By Sarad Mohanan in BigQuery, Data Warehousing, Snowflake, Versus If you have been looking to find an answer to this question: BigQuery vs Snowflake - Which data warehouse to choose, then you have landed at the right place. We…
Google BigQuery vs Athena: 7 Critical Differences May 10th, 2024 By Nitin Birajdar in BigQuery, Data Warehousing, Versus Today every organization is moving to serverless cloud offerings to solve many of the data-related challenges. The primary issue these companies face occurs while trying to manage vast data repositories.…
Standard SQL vs Legacy SQL BigQuery: The Dialects Simplified 101 May 10th, 2024 By Sarthak Bhardwaj in BigQuery, Data Warehousing, Versus Venturing into Data Science and deciding on a tool to use to solve a given problem can be challenging at times especially when you have a wide array of choices.…
Firebolt vs BigQuery: 6 Comprehensive Differences May 3rd, 2024 By Radhika Sarraf in BigQuery, Data Warehousing, Versus With the data growing at a very fast pace, the requirements to store and process data are also increasing. Businesses use Data Warehouses to store the data. Cloud Data Warehouses…
Redshift vs BigQuery: 7 Critical Differences April 12th, 2024 By Veeresh Biradar in BigQuery, Data Warehousing, Redshift, Versus As analytics in your company graduates from a MySQL/PostgreSQL/SQL Server, a pertinent question that you need to answer is which data warehouse is best suited for you. This blog tries…
BigQuery Timestamp to Date Conversion: Data Transformation December 27th, 2023 By Osheen Jain in BigQuery, Data Warehousing When working with data in BigQuery, you may encounter timestamp fields that you want to convert to simple date values instead. Timestamps in BigQuery are represented as strings in the…
Efficient Data Management with BigQuery INSERT and UPDATE Commands December 20th, 2023 By Sarad Mohanan in BigQuery, Data Warehousing Recent years have witnessed many new platforms and software in the field of data management. With the vast sea of information that is growing daily, most organizations are looking towards…
Simplify Data Handling with BigQuery IFNULL and NULLIF December 13th, 2023 By Muhammad Faraz in BigQuery, Data Warehousing With BigQuery, Google makes it easy to access tons of data with analysis, optimized results, and better performance and availability. It is a serverless database, and there is no infrastructure to…
dbt Incremental BigQuery: A Comprehensive Guide 101 February 28th, 2023 By Manjiri Gaikwad in BigQuery, Data Warehousing It is essential to keep track of the modifications in data at the source to create a single source of truth with centralization. However, updating and adding data to the…
Best Google BigQuery Public Datasets for 2024: 5 Useful Datasets January 8th, 2023 By Orina Mark in BigQuery, Data Warehousing Data is fantastic, but Big Data is even better. With big data, you get a broader scope of research, which ultimately goes a great way in informed decision-making. However, getting…
Databricks vs BigQuery: 5 Critical Differences June 10th, 2022 By Sanchit Agarwal in BigQuery, Data Warehousing, Versus Exponentially growing data and the need to quickly process it to gain valuable insights is an ongoing challenge that most businesses face. An efficient solution is to switch from the…
BigQuery Quantiles & Percentile: Using APPROX_QUANTILES Simplified 101 March 31st, 2022 By Jeremiah in BigQuery, Data Warehousing Quantiles and Percentiles are mathematical techniques related to statistical analysis and machine learning. They are important concepts because, in statistical analysis, most of the distribution of numeric variables that you'll…
How to Setup BigQuery ODBC Connection? 3 Easy Steps March 28th, 2022 By Sanchit Agarwal in BigQuery, Data Warehousing Offering an accelerated and unbeatable query performance, Google BigQuery has become a reliable Cloud Data Warehouse & Analytics solution worldwide. With its on-demand scaling, economical pricing, and the ability to…
BigQuery Time Travel: How to access Historical Data? | Easy Steps March 21st, 2022 By Ishwarya M in BigQuery, Data Warehousing BigQuery is one of the most popular and highly efficient analytics platforms that allow you to store, process, and analyze Big Data. In addition, BigQuery can process over 100 trillion…
BigQuery IAM Management 101: Defining Permissions & Access Controls Simplified March 15th, 2022 By Samuel Salimon in BigQuery, Data Warehousing All of us have heard and seen about Data Breaches and the damage they can cause, both financially and reputationally. As more and more of our decisions are based on…
How to do Exploratory Data Analysis with BigQuery? March 9th, 2022 By Roxana Raducanu in BigQuery, Data Warehousing Exploratory Data Analysis (EDA), also known as Data Exploration, is an approach for the Data Analysis Process that employs various techniques to better understand the data we have. EDA typically…