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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
At Datametica, our innovative solutions significantly reduce risks and alleviate costs, time, frustration, and anxiety throughout the data warehouse migration process to the cloud. We facilitate the transition of your current data warehouse, data lake, ETL, and enterprise business intelligence systems to your preferred cloud environment through our automated product suite. Our approach involves crafting a comprehensive migration strategy that includes workload discovery, assessment, planning, and cloud optimization. With our Eagle tool, we provide insights from the initial discovery and assessment phases of your existing data warehouse to the development of a tailored migration strategy, detailing what data needs to be moved, the optimal sequence for migration, and the anticipated timelines and expenses. This thorough overview of workloads and planning not only minimizes migration risks but also ensures that business operations remain unaffected during the transition. Furthermore, our commitment to a seamless migration process helps organizations embrace cloud technologies with confidence and clarity.
API Access
Has API
API Access
Has API
Integrations
AWS App Mesh
Amazon Athena
Amazon DataZone
Amazon EMR
Amazon Redshift
Amazon S3
Amazon SageMaker Feature Store
Amazon Web Services (AWS)
Collate
Google Cloud Platform
Integrations
AWS App Mesh
Amazon Athena
Amazon DataZone
Amazon EMR
Amazon Redshift
Amazon S3
Amazon SageMaker Feature Store
Amazon Web Services (AWS)
Collate
Google Cloud Platform
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
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/lake-formation/
Vendor Details
Company Name
Datametica
Founded
2013
Country
India
Website
www.datametica.com
Product Features
Product Features
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control