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What is SAS Data Loader for Hadoop?

Easily import or retrieve your data from Hadoop and data lakes, ensuring it's ready for report generation, visualizations, or in-depth analytics—all within the data lakes framework. This efficient method enables you to organize, transform, and access data housed in Hadoop or data lakes through a straightforward web interface, significantly reducing the necessity for extensive training. Specifically crafted for managing big data within Hadoop and data lakes, this solution stands apart from traditional IT tools. It facilitates the bundling of multiple commands to be executed either simultaneously or in a sequence, boosting overall workflow efficiency. Moreover, you can automate and schedule these commands using the public API provided, enhancing operational capabilities. The platform also fosters collaboration and security by allowing the sharing of commands among users. Additionally, these commands can be executed from SAS Data Integration Studio, effectively connecting technical and non-technical users. Not only does it include built-in commands for various functions like casing, gender and pattern analysis, field extraction, match-merge, and cluster-survive processes, but it also ensures optimal performance by executing profiling tasks in parallel on the Hadoop cluster, which enables the smooth management of large datasets. This all-encompassing solution significantly changes your data interaction experience, rendering it more user-friendly and manageable than ever before, while also offering insights that can drive better decision-making.

What is AWS Lake Formation?

AWS Lake Formation simplifies the creation of a secure data lake within a matter of days. A data lake functions as a centralized repository that is both curated and secured, allowing for the storage of all data types, whether they are in their original format or processed for analysis. By leveraging a data lake, organizations can break down data silos and integrate diverse analytics to uncover insights that lead to better business decisions. Nonetheless, the traditional approaches to setting up and managing these data lakes can be quite labor-intensive, complex, and lengthy. This includes tasks such as gathering data from multiple sources, monitoring data flows, setting up partitions, enabling encryption while managing keys, launching transformation jobs, and evaluating their performance. Moreover, it requires reformatting data into a columnar structure, eliminating duplicates, and ensuring related records are properly linked. Once the data is in the data lake, it becomes vital to enforce fine-grained access controls for the datasets and to maintain a comprehensive audit trail across various analytics and machine learning (ML) platforms over time. As organizations continue to prioritize data-driven strategies, the importance of efficiency and security offered by solutions like AWS Lake Formation grows significantly, making it an essential tool for modern data management. Ultimately, effective data lake management not only enhances operational workflows but also empowers organizations to harness their data for strategic advantages.

Media

Media

Integrations Supported

Hadoop
Impala
Microsoft 365
Microsoft Power BI
SAS Analytics for IoT
SAS Anti-Money Laundering
SAS Business Intelligence
SAS Business Rules Manager
SAS Customer Intelligence
SAS Data Management
SAS Data Quality
SAS Energy Forecasting
SAS MDM

Integrations Supported

AWS App Mesh
Amazon Athena
Amazon EMR
Amazon Redshift
Amazon S3
Amazon SageMaker Feature Store
Velotix

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

SAS

Date Founded

1976

Company Location

United States

Company Website

www.sas.com/en_us/software/data-loader-for-hadoop.html

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/lake-formation/

Categories and Features

Data Preparation

Not specified

Categories and Features

Data Lake

Not specified

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