Google Cloud Dataprep Reviews

Administration is Superb on this platform.

Update complexity is a hassle to describe.

Try to improve the requirement analysis for the product.

Cloud data management is a charm in GCloud Dataprep.

Easy to use and understand the transformations. Many different connections are available.

I sometimes have to look up how to do basic functions like adding a new column based on a different function than one that's suggested.

I am transferring, transforming, and joining data from disparate sources.

The simplicity and able to handle large datasets in a timely manner.

It is also very easy to just jump in and put together a quick data flow.

Importing size limitations and integrations with other programs, would be nice to have streaming functions from data prep

I would say if you are using this as a one off analysis tool, it is very good. I use other programs for data extraction and transformations, but I use dataprep mainly when doing a quick analysis of a large data set, or something that I will be running for a few weeks that I don't necessarily want to build a full data pipeline for.

I like Data analyst opportunities for my work.

sometimes it shows some errors, so it is annoying.

It is helpful for a short time data analysis and a 90% correction , so I recommend to others.

Database marketing that I have easily got a solution for this. The benefit of google cloud dataprep is a rapid data ingestion, so it realized it.

Having ever-increasing amounts of data available from relational to sentiments in Twitter feeds to system log files makes being able to wrangle it into a workable form even more pressing. Google Cloud Dataprep makes it easy to get to your data and manipulate it into beneficial information to use for research, machine learning or user interaction via a presentation tool or desktop.

The product is robust and increasing in features monthly which is good but the adoption of new capabilities on such a frequent basis means always having to review the releases for things to be added to existing wrangle recipes to improve their efficiency. Not necessarily a bad thing having too many ways to get and manipulate your data into insight providing forms.

Seeing how I have been wrangling data for over 20 years, the benefit of a feature-rich product to work through developing clean data, prepare research data or just provide daily insights via dashboards is very helpful. The ability to then make the recipes (steps of wrangling the data) available to others and scheduling it themselves lets them take on their data research discovery.

The best part of this product is the fast process and understanding about exploring the data very quick.Because of which I can avoid the time consuming analysis.It is very good in self analyzing the missing values and duplicates as well and save your time.

Its a good product however there are few area of improvements which is like the sort transform is not supported in this product also sharing is also not supported which is a drawback for this product.

Its a user friendly product and since you can use it with same credentials which you already use for google service,It provides with best exploring and preparing function for your data with big query. The reason it is called intelligent data service because it will visually explore clean and prepare those data which is not ready for immediate analysis and its very easy to use product so you will not get bored too and yes its pretty user friendly as well.

There are many business problems this product is solving for example its less time consuming since it analyze many issues itself which includes data transformation and its predicted with each UI input.It provides user with access and prepare data from storage themselves.It makes data handling very easy.

I don't have to learn a new tech language, my data is presented to me in a clear and easy to understand manner. Love the deep integration to the rest of the Google Cloud.

Not enough community support to get my questions answered, not enough Googler's know about this.

Preparing log data for analytics, basic cleansing and parsing. Instead of doing this manually in Google Sheets, Dataprep has automated most of this in a few steps.

Easy visualization of large datasets and easy preprocessing for first time look at a new datasets. Flexible pipeline features. Dataflow visualization. Flexible exporting to other products

On occasion when importing data from gcp buckets (ex csv) it has lost some of my data

Understand SQL commands and data storage option like BigQuery

Machine learning for structured data. Better understanding of our inhouse data.

It is visual. It does not need coding when you are changing and correcting errors in your data. And i usually like products by Google because of their good service. You also can use any size of data.

I haven't seen anything in the program that I dislike yet.

I started liking this program. It is good to give it a shot if you are working with different types of data sets.

As a GCP user, the synchronization between flat files, cloud buckets and BigQuery makes for very efficient access to data. We are a small team so having a full ETL tool at our disposal without the heavy engineering resource requirements is a big win.

Exporting and sharing wrangles is not easy. This creates a risk in that certain jobs or wrangles are limited to a single user vs multiple users.

I would recommend this to any team who needs assistance with cleaning up data for analysis. It's a great tool for analysts and non-technical users who are comfortable with test and learn from the very intuitive workflow.

We process 100s of GB of Doubleclick Data Transfer data each week and the data is not always present a in format we need. Dataprep has given us a scalable tool that we can process and activate on log level data more efficiently. Cleaning small datasets are made more efficient so its great for small jobs that are repeated regularly.