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Average Ratings 0 Ratings
Description
Genie Code is an advanced AI tool designed specifically for data teams, providing the capability to analyze, construct, and manage intricate data workflows within the Databricks environment. This intelligent agent autonomously orchestrates and implements multi-step tasks while adjusting to the unique data and governance frameworks of an organization, boasting specialized skills in data engineering, data science, machine learning, and business intelligence. Leveraging the metadata, semantics, and governance of Unity Catalog, Genie Code can pinpoint authoritative tables, metrics, and assets, comprehend dependencies among various data and AI systems, and adhere to established access restrictions. In the realm of data science, it excels in locating and cleansing data, scrutinizing datasets, validating hypotheses, and producing easily shareable reports. For machine learning processes, it handles feature engineering, model training and assessment, deployment, endpoint setup, and fine-tuning performance. Additionally, data engineers can utilize natural language to streamline ETL processes, enhance query performance, and construct Spark Declarative Pipelines, making their workflows more efficient and user-friendly. Overall, Genie Code empowers data teams to work more effectively and innovate rapidly in their data-driven initiatives.
Description
Zipher is an innovative optimization platform that autonomously enhances the performance and cost-effectiveness of workloads on Databricks by removing the need for manual tuning and resource management, all while making real-time adjustments to clusters. Utilizing advanced proprietary machine learning algorithms, Zipher features a unique Spark-aware scaler that actively learns from and profiles workloads to determine the best resource allocations, optimize configurations for each job execution, and fine-tune various settings such as hardware, Spark configurations, and availability zones, thereby maximizing operational efficiency and minimizing waste. The platform continuously tracks changing workloads to modify configurations, refine scheduling, and distribute shared compute resources effectively to adhere to service level agreements (SLAs), while also offering comprehensive cost insights that dissect expenses related to Databricks and cloud services, enabling teams to pinpoint significant cost influencers. Furthermore, Zipher ensures smooth integration with major cloud providers like AWS, Azure, and Google Cloud, and is compatible with popular orchestration and infrastructure-as-code (IaC) tools, making it a versatile solution for various cloud environments. Its ability to adaptively respond to workload changes sets Zipher apart as a crucial tool for organizations striving to optimize their cloud operations.
API Access
Has API
API Access
Has API
Integrations
Databricks
Amazon Web Services (AWS)
Apache Airflow
Azure Data Factory
Google Cloud Platform
Microsoft Azure
SQL
Slack
Terraform
dbt
Integrations
Databricks
Amazon Web Services (AWS)
Apache Airflow
Azure Data Factory
Google Cloud Platform
Microsoft Azure
SQL
Slack
Terraform
dbt
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
Databricks
Founded
2013
Country
United States
Website
www.databricks.com/product/genie/code
Vendor Details
Company Name
Zipher
Founded
2023
Country
United States
Website
zipher.cloud/