Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
AWS Lake Formation is a service designed to streamline the creation of a secure data lake in just a matter of days. A data lake serves as a centralized, carefully organized, and protected repository that accommodates all data, maintaining both its raw and processed formats for analytical purposes. By utilizing a data lake, organizations can eliminate data silos and integrate various analytical approaches, leading to deeper insights and more informed business choices. However, the traditional process of establishing and maintaining data lakes is often burdened with labor-intensive, complex, and time-consuming tasks. This includes activities such as importing data from various sources, overseeing data flows, configuring partitions, enabling encryption and managing encryption keys, defining and monitoring transformation jobs, reorganizing data into a columnar structure, removing duplicate records, and linking related entries. After data is successfully loaded into the data lake, it is essential to implement precise access controls for datasets and continuously monitor access across a broad spectrum of analytics and machine learning tools and services. The comprehensive management of these tasks can significantly enhance the overall efficiency and security of data handling within an organization.
Description
Qlik Compose for Data Warehouses offers a contemporary solution that streamlines and enhances the process of establishing and managing data warehouses. This tool not only automates the design of the warehouse but also generates ETL code and implements updates swiftly, all while adhering to established best practices and reliable design frameworks. By utilizing Qlik Compose for Data Warehouses, organizations can significantly cut down on the time, expense, and risk associated with BI initiatives, regardless of whether they are deployed on-premises or in the cloud. On the other hand, Qlik Compose for Data Lakes simplifies the creation of analytics-ready datasets by automating data pipeline processes. By handling data ingestion, schema setup, and ongoing updates, companies can achieve a quicker return on investment from their data lake resources, further enhancing their data strategy. Ultimately, these tools empower organizations to maximize their data potential efficiently.
API Access
Has API
Yes
API Access
Has API
No
Integrations
AWS App Mesh
Yes
Amazon Athena
Yes
Amazon DataZone
Yes
Amazon EMR
Yes
Amazon Redshift
Yes
Amazon S3
Yes
Amazon SageMaker Feature Store
Yes
BLUE Software
No
Collate
Yes
EZConvertBI
No
Integrations
AWS App Mesh
No
Amazon Athena
No
Amazon DataZone
No
Amazon EMR
No
Amazon Redshift
No
Amazon S3
No
Amazon SageMaker Feature Store
No
BLUE Software
Yes
Collate
No
EZConvertBI
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/lake-formation/
Vendor Details
Company Name
Qlik
Founded
1993
Country
United States
Website
www.qlik.com/us/products/qlik-compose-data-warehouses
Product Features
Product Features
Data Warehouse
Ad hoc Query
No
Analytics
Yes
Data Integration
Yes
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No