Google Cloud Dataprep Features

Collects, stores, and organizes massive, unstructured data in real time

Facilitates the disseminating of collected big data throughout parallel computing clusters

Creates a repository to collect and store raw data from sensors, devices, machines, files, etc.

Aligns processing and distribution workflows on top of Apache Hadoop

Aligns processing and distribution workflows on top of Apache Hadoop

Facilitates solution to run on and scale to a large number of machines and systems

Curates collected data for big data analytics solutions to analyze, manipulate, and model

Aligns processing and distribution workflows on top of Apache Hadoop

Moves big data collection and processing to the cloud

Processes batch, real-time, and streaming data workloads in singular, multi-tenant, or cloud systems

Provides a wide range of possible data connections, including cloud applications, on-premise databases, and big data distributions, among others

Allows businesses to easily connect to any data source

Offers API connections for cloud-based applications and data sources

Permits profiling of data sets for increased organization, both by users and machine learning

Indexes metadata descriptions for easier searching and enhanced insights

Tools to (re)structure data in a manner that enables quick and accurate insight extraction

Allows self-service joining of tables

Provides the ability to combine data sources into one data set

Allows users and administrators to easily clean data to maintain quality and integrity

Offers collaborative functionality for sharing queries and data sets

Ensures user access management, data lineage, and data encryption

Provides a wide range of possible integrations, including analytics, data integration, master data management, and data science tools

Allows businesses to easily integrate with analytics, data integration, master data management, and data science tools

Operationalizes data workflows to easily scale repeatable preparation needs

Allows users to generate text based on a text prompt.

Use AI to generate content in the form of text, images, videos, etc.

Analyze survey results via statistical testing or crosstabs directly within the software

Software program that continuously adjusts its behavior based on observed data

Automatically retrieve and pull information from documents, websites, images, data sets, and other sources

View and track pertinent metrics to find patterns and gain insights from data

A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users

Track the management and flow of data throughout the organization

Process of extracting, transforming, and loading data

Examine large amounts of data to uncover hidden patterns, correlations, and other insights

Establish guidelines about how much and what kind of data can be stored in the repository