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Description
Astera Dataprep is an innovative data preparation tool that leverages AI and a chat-based interface, allowing users to effortlessly clean, transform, and prepare raw data for various purposes such as analysis, reporting, and integration by simply using natural language commands, thus removing the barriers of coding and technical expertise; users articulate their requirements in everyday language, and the system executes tasks like merging, filtering, deduplicating, reshaping, and transforming data in real time, all while providing an interactive preview reminiscent of Excel for easier visualization of modifications. The platform is capable of connecting to numerous data sources, including spreadsheets, CSV files, database tables, and cloud storage solutions, enabling users to consolidate data from multiple origins within a single workspace, identify and rectify data quality challenges such as missing values and duplicates instantaneously, thereby ensuring reliable and accurate outputs. Additionally, users have the option to save their data preparation processes as reusable workflows, automate regular updates through scheduled jobs, and seamlessly export the cleaned data to various analytics or business intelligence applications for further analysis. This functionality significantly enhances productivity and streamlines workflows, making data management a more efficient and user-friendly experience.
Description
Enhance your analytics, data migration, and master data management (MDM) projects with the SAP Agile Data Preparation tool. This application allows you to efficiently convert your data into actionable insights, streamlining your access to and understanding of data shapes, thus increasing your productivity and agility beyond your expectations. The Cloud Service's Usage Metric is measured by the number of Users, defined as individuals who prepare, manage, and oversee data sets or perform data stewardship tasks within the service. Each subscription requires customers to purchase an annual foundation subscription, which comes in increments of 64 GB of memory per year, with a maximum capacity of 512 GB annually. This structured approach ensures that organizations can scale their data needs effectively while maintaining high performance and efficiency.
API Access
Has API
API Access
Has API
Integrations
Acterys
Amazon Aurora
COBOL
Data Secure
Google Sheets
IBM Db2
JSON
MariaDB
Microsoft Excel
Microsoft SharePoint
Integrations
Acterys
Amazon Aurora
COBOL
Data Secure
Google Sheets
IBM Db2
JSON
MariaDB
Microsoft Excel
Microsoft SharePoint
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Astera
Country
United States
Website
www.astera.com/products/astera-data-prep/
Vendor Details
Company Name
SAP
Founded
1972
Country
Germany
Website
assets.cdn.sap.com/agreements/product-use-and-support-terms/cls/en/sap-agile-data-preparation-supplement-english-v2-2016.pdf
Product Features
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Product Features
Data Cleansing
Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface