Google BigQuery

What differentiates Google BigQuery from other similar products?

The best option, which can save a ton of time, is offered by Google Cloud BigQuery, which also helps with building ML models using only SQL queries. The capability to import data from CSV and other sources is one of its outstanding features. We enjoy working with it.

What is your favorite aspect of this product?

Google Cloud BigQuery is among the most effective options for the data warehouse process. Because it is so easy to use, even a beginner can utilize the device in one sitting. The ability to build ML models using a query is one of its better features and one that I really liked. It makes it very simple to manage large and complex searches.

What do you dislike most about this product?

Bigquery bases its estimation of the cost of a query on the volume of data that has to be processed, hence, it is easy to make costly searches without recognizing it. The number of rows returned by the query will not change, even if I limit it. The new Bigquery SQL editor's autocomplete feature occasionally produces unwanted outcomes.

What recommendations would you give to someone considering this product?

It was first and foremost a fantastic tool that met all of our demands. For our employees, it makes it very easy to manage extensive and complicated searches, and one of its best features, and a feature I particularly like is the capability to build machine learning models using a query. I wish to suggest this to you on their behalf.

What differentiates Google BigQuery from other similar products?

Google BigQuery is well-liked on the front end because it is cost-effective and easy to use, but when it comes to execution, it is an enterprise data warehouse that is totally serverless, has integrated ML and BI is cross-cloud compatible and expands with all of our business data. We can access and use our data wherever it is by using BigQuery, which eliminates the need for a separate repository to store data.

What is your favorite aspect of this product?

I was able to easily analyze data from the many clouds in a secure, quick, and convenient manner using the Google BigQuery platform, and I was able to disseminate only the outputs that were required and of high quality using a single user interface. With the help of this wonderful technology, we can now dramatically streamline our research, learn new things about spatial data, and build entirely new business potential.

What do you dislike most about this product?

The UI did not particularly appeal to me; in my opinion, it should be more understandable, simple to use, customizable, and logical. Except for it, the query quality is excellent and all other operations go without a hitch. I want to design our dashboards as rapidly as possible based on the needs that are currently a little overwhelming.

What recommendations would you give to someone considering this product?

BigQuery is a tool that can be helpful for massive data as its name implies. Since everything can be done inside the BigQuery Platform with a single touch, using manual ML models is no longer necessary to transform large amounts of raw data into profitable analytics. In contrast to competitors, it provides a less complex yet effective data analysis store that will help business expansion and earnings.

What differentiates Google BigQuery from other similar products?

Although data models design and sharing are both feasible through the user interface, I would also like a new feature that would allow me to directly compare analytical data to other outputs. Outside of Google Cloud, add-ons also require improvement. Even though we had an analytical data store, we've been fighting a data disaster at work for years because it was hard to implement and we weren't sure how to use it correctly. Google BigQuery has eliminated the hassle of data maintenance while also transforming our messy data into valuable business insights. It has established itself as our big data's analytical data store.

What is your favorite aspect of this product?

I am a data expert, and I found it useful in that it allowed me to quickly develop and execute machine learning models on our source data at a wider scale inside the Google BigQuery infrastructure, cutting my working time in half. It is a win-win situation because it is faultless, sophisticated, and fairly priced.

What do you dislike most about this product?

Even while the present techniques are effective, some of my clients would rather receive simple warnings when their payment goes over a specific threshold. It occasionally frustrates me that there are so few heuristic options, like grouping and reformatting, because I can't always find what I'm looking for.

What recommendations would you give to someone considering this product?

Any data expert working on a platform other than Google BigQuery is, in my opinion, missing out on the true quality and value of their data. I advise them to compare the effectiveness and results of both analytical data platforms; they will be astounded by Google BigQuery's features and functionality. Its reasonable pricing makes it accessible to even tiny businesses.