Google BigQuery

What differentiates Google BigQuery from other similar products?

BigQuery stores data in columnar manner which is unlike any Database which helps in faster analysis of data and faster query runs. The query fired on tables is distributed across different nodes and query results are computed parallelly.

What is your favorite aspect of this product?

The Machine Learning capability of BigQuery is something that I like the most. Just by running a few SQL queries we can build and train an ML model without having to write any Python code. Another good feature is that we can schedule our queries to run and the results to be presented as part of dashboards/reports can be quickly computed using BI Engine

What do you dislike most about this product?

There is one bug while loading data of STRING type in BigQuery. If all the columns in the data are of string data type then BigQuery is not able to detect the column names on its own.

What recommendations would you give to someone considering this product?

BigQuery is one of the leading Data Warehousing tool and is a very efficient service provided by GCP. It can be easily connected with Data Integration and Analytical tools and it works seamlessly with almost every tool available in the market

What differentiates Google BigQuery from other similar products?

BigQuery works well with other platforms, such as Knime, and can be linked to other data visualization or manipulation software. Furthermore, it is simple to use with multiple users and teams, and creating areas for users of various levels or types is simple.

What is your favorite aspect of this product?

BigQuery is used for data exploration by BI tools. It also serves as our primary data warehouse. It includes both raw and aggregated data. By running scheduled queries on it, this is also used for aggregation. I like how quickly we can quickly build dashboards, control data visibility permissions, plug in new data sources, automate alarms, and easily schedule data processing jobs by leveraging the power of BigQuery.

What do you dislike most about this product?

Few ETL tools provide robust connectors for loading and retrieving data from Google BigQuery. I can't run multiple queries in the same console because I frequently want to compare the results immediately.

What recommendations would you give to someone considering this product?

Google BigQuery has significantly increased our analytical capabilities while also propelling our company forward. BigQuery works well with other Microsoft and Google products, as well as data visualization software such as PowerBI, Tableau, and MicroStrategy.

What differentiates Google BigQuery from other similar products?

Scalability, ease of setup and use, and no need to worry about infrastructure make it an extremely powerful tool. BQML and federated query are useful features that save a lot of time when bringing data into a data warehouse in a traditional environment.

What is your favorite aspect of this product?

I tried so many tools in our organization before utilizing it but none of them work according to our needs I love BigQuery which crossed my expectations. We use BigQuery to aggregate data from multiple systems and create datasets for data analysis that aid in decision making, visualizing the status of business processes, and automating decisions and notifications based on highly customizable criteria.

What do you dislike most about this product?

We're constantly reaching our maximum slot usage, which means some queries won't run or we'll hit concurrent slot usage, which means some queries will time out and not retrieve data. This is one of the most difficult problems we have.

What recommendations would you give to someone considering this product?

When dealing with extremely large amounts of data, Google BigQuery comes in handy. We don't have to pay for hardware, so it's much cheaper than on-site data storage. In comparison to other query tools we've used, running queries is simple and quick. I would strongly suggest Google BigQuery.